Impact of selected personal factors on seasonal variability of recreationist weather perceptions and preferences in Warsaw (Poland).

PubMed

Lindner-Cendrowska, Katarzyna; Błażejczyk, Krzysztof

2018-01-01

Weather and climate are important natural resources for tourism and recreation, although sometimes they can make outdoor leisure activities less satisfying or even impossible. The aim of this work was to determine weather perception seasonal variability of people staying outdoors in urban environment for tourism and recreation, as well as to determine if personal factors influence estimation of recreationist actual biometeorological conditions and personal expectations towards weather elements. To investigate how human thermal sensations vary upon meteorological conditions typical for temperate climate, weather perception field researches were conducted in Warsaw (Poland) in all seasons. Urban recreationists' preference for slightly warm thermal conditions, sunny, windless and cloudless weather, were identified as well as PET values considered to be optimal for sightseeing were defined between 27.3 and 31.7 °C. The results confirmed existence of phenomena called alliesthesia, which manifested in divergent thermal perception of comparable biometeorological conditions in transitional seasons. The results suggest that recreationist thermal sensations differed from other interviewees' responses and were affected not only by physiological processes but they were also conditioned by psychological factors (i.e. attitude, expectations). Significant impact of respondents' place of origin and its climate on creating thermal sensations and preferences was observed. Sex and age influence thermal preferences, whereas state of acclimatization is related with thermal sensations to some point.

Evaluation of a variable speed limit system for wet and extreme weather conditions : phase 1 report.

DOT National Transportation Integrated Search

2012-06-01

Weather presents considerable challenges to the highway system, both in terms of safety and operations. From a safety standpoint, weather (i.e. precipitation in the form of rain, snow or ice) reduces pavement friction, thus increasing the potential f...

Identifying crash-prone traffic conditions under different weather on freeways.

PubMed

Xu, Chengcheng; Wang, Wei; Liu, Pan

2013-09-01

Understanding the relationships between traffic flow characteristics and crash risk under adverse weather conditions will help highway agencies develop proactive safety management strategies to improve traffic safety in adverse weather conditions. The primary objective is to develop separate crash risk prediction models for different weather conditions. The crash data, weather data, and traffic data used in this study were collected on the I-880N freeway in California in 2008 and 2010. This study considered three different weather conditions: clear weather, rainy weather, and reduced visibility weather. The preliminary analysis showed that there was some heterogeneity in the risk estimates for traffic flow characteristics by weather conditions, and that the crash risk prediction model for all weather conditions cannot capture the impacts of the traffic flow variables on crash risk under adverse weather conditions. The Bayesian random intercept logistic regression models were applied to link the likelihood of crash occurrence with various traffic flow characteristics under different weather conditions. The crash risk prediction models were compared to their corresponding logistic regression model. It was found that the random intercept model improved the goodness-of-fit of the crash risk prediction models. The model estimation results showed that the traffic flow characteristics contributing to crash risk were different across different weather conditions. The speed difference between upstream and downstream stations was found to be significant in each crash risk prediction model. Speed difference between upstream and downstream stations had the largest impact on crash risk in reduced visibility weather, followed by that in rainy weather. The ROC curves were further developed to evaluate the predictive performance of the crash risk prediction models under different weather conditions. The predictive performance of the crash risk model for clear weather was better than those of the crash risk models for adverse weather conditions. The research results could promote a better understanding of the impacts of traffic flow characteristics on crash risk under adverse weather conditions, which will help transportation professionals to develop better crash prevention strategies in adverse weather. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Associations between weather conditions and clinical symptoms in patients with hip osteoarthritis: a 2-year cohort study.

PubMed

Dorleijn, Desirée M J; Luijsterburg, Pim A J; Burdorf, Alex; Rozendaal, Rianne M; Verhaar, Jan A N; Bos, Pieter K; Bierma-Zeinstra, Sita M A

2014-04-01

The goal of this study was to assess whether there is an association between ambient weather conditions and patients' clinical symptoms in patients with hip osteoarthritis (OA). The design was a cohort study with a 2-year follow-up and 3-monthly measurements and prospectively collected data on weather variables. The study population consisted of 222 primary care patients with hip OA. Weather variables included temperature, wind speed, total amount of sun hours, precipitation, barometric pressure, and relative humidity. The primary outcomes were severity of hip pain and hip disability as measured with the Western Ontario and McMasters University Osteoarthritis Index (WOMAC) pain and function subscales. Associations between hip pain and hip disability and the weather variables were assessed using crude and multivariate adjusted linear mixed-model analysis for repeated measurements. On the day of questionnaire completion, mean relative humidity was associated with WOMAC pain (estimate 0.1; 95% confidence interval=0.0-0.2; P=.02). Relative humidity contributed < or = 1% to the explained within-patient variance and between-patient variance of the WOMAC pain score. Mean barometric pressure was associated with WOMAC function (estimate 0.1; 95% confidence interval=0.0-0.1; P=.02). Barometric pressure contributed < or = 1% to the explained within-patient variance and between-patient variance of the WOMAC function score. The other weather variables were not associated with the WOMAC pain or function score. Our results support the general opinion of OA patients that barometric pressure and relative humidity influence perceived OA symptoms. However, the contribution of these weather variables (< or = 1%) to the severity of OA symptoms is not considered to be clinically relevant. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Weather elements, chemical air pollutants and airborne pollen influencing asthma emergency room visits in Szeged, Hungary: performance of two objective weather classifications

NASA Astrophysics Data System (ADS)

Makra, László; Puskás, János; Matyasovszky, István; Csépe, Zoltán; Lelovics, Enikő; Bálint, Beatrix; Tusnády, Gábor

2015-09-01

Weather classification approaches may be useful tools in modelling the occurrence of respiratory diseases. The aim of the study is to compare the performance of an objectively defined weather classification and the Spatial Synoptic Classification (SSC) in classifying emergency department (ED) visits for acute asthma depending from weather, air pollutants, and airborne pollen variables for Szeged, Hungary, for the 9-year period 1999-2007. The research is performed for three different pollen-related periods of the year and the annual data set. According to age and gender, nine patient categories, eight meteorological variables, seven chemical air pollutants, and two pollen categories were used. In general, partly dry and cold air and partly warm and humid air aggravate substantially the symptoms of asthmatics. Our major findings are consistent with this establishment. Namely, for the objectively defined weather types favourable conditions for asthma ER visits occur when an anticyclonic ridge weather situation happens with near extreme temperature and humidity parameters. Accordingly, the SSC weather types facilitate aggravating asthmatic conditions if warm or cool weather occur with high humidity in both cases. Favourable conditions for asthma attacks are confirmed in the extreme seasons when atmospheric stability contributes to enrichment of air pollutants. The total efficiency of the two classification approaches is similar in spite of the fact that the methodology for derivation of the individual types within the two classification approaches is completely different.

Weather elements, chemical air pollutants and airborne pollen influencing asthma emergency room visits in Szeged, Hungary: performance of two objective weather classifications.

PubMed

Makra, László; Puskás, János; Matyasovszky, István; Csépe, Zoltán; Lelovics, Enikő; Bálint, Beatrix; Tusnády, Gábor

2015-09-01

Weather classification approaches may be useful tools in modelling the occurrence of respiratory diseases. The aim of the study is to compare the performance of an objectively defined weather classification and the Spatial Synoptic Classification (SSC) in classifying emergency department (ED) visits for acute asthma depending from weather, air pollutants, and airborne pollen variables for Szeged, Hungary, for the 9-year period 1999-2007. The research is performed for three different pollen-related periods of the year and the annual data set. According to age and gender, nine patient categories, eight meteorological variables, seven chemical air pollutants, and two pollen categories were used. In general, partly dry and cold air and partly warm and humid air aggravate substantially the symptoms of asthmatics. Our major findings are consistent with this establishment. Namely, for the objectively defined weather types favourable conditions for asthma ER visits occur when an anticyclonic ridge weather situation happens with near extreme temperature and humidity parameters. Accordingly, the SSC weather types facilitate aggravating asthmatic conditions if warm or cool weather occur with high humidity in both cases. Favourable conditions for asthma attacks are confirmed in the extreme seasons when atmospheric stability contributes to enrichment of air pollutants. The total efficiency of the two classification approaches is similar in spite of the fact that the methodology for derivation of the individual types within the two classification approaches is completely different.

A synoptic approach to weather conditions discloses a relationship with ambulatory blood pressure in hypertensives.

PubMed

Morabito, Marco; Crisci, Alfonso; Orlandini, Simone; Maracchi, Giampiero; Gensini, Gian F; Modesti, Pietro A

2008-07-01

Higher blood pressure (BP) values in cold than in hot months has been documented in hypertensives. These changes may potentially contribute to the observed excess winter cardiovascular mortality. However, the association with weather has always been investigated by considering the relationship with a single variable rather than considering the combination of ground weather variables characterizing a specific weather pattern (air mass (AM)). We retrospectively investigate in Florence (Italy) the relationship between BP and specific AMs in hypertensive subjects (n = 540) referred to our Hypertension Unit for 24-h ambulatory BP monitoring during the period of the year characterized by the highest weather variability (winter). Five different winter daily AMs were classified according to the combination of ground weather data (air temperature, cloud cover, relative humidity, atmospheric pressure, wind speed, and direction). Multiple variable analysis selected the AM as a significant predictor of mean 24-h BP (P < 0.01 for diastolic BP (DBP) and P < 0.05 for systolic BP (SBP)), daytime DBP (P < 0.001) and nighttime BP (P < 0.01 for both SBP and DBP), with higher BP values observed in cyclonic (unstable, cloudy, and mild weather) than in anticyclonic (settled, cloudless, and cold weather) days. When the association with 2-day sequences of AMs was considered, an increase in ambulatory BP followed a sudden day-to-day change of weather pattern going from anticyclonic to cyclonic days. The weather considered as a combination of different weather variables may affect BP. The forecast of a sudden change of AM could provide important information helpful for hypertensives during winter.

Physiological responses of pilots to severe weather flying.

DOT National Transportation Integrated Search

1966-07-01

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

Analyzing Personal Happiness from Global Survey and Weather Data: A Geospatial Approach

PubMed Central

Peng, Yi-Fan; Tang, Jia-Hong; Fu, Yang-chih; Fan, I-chun; Hor, Maw-Kae; Chan, Ta-Chien

2016-01-01

Past studies have shown that personal subjective happiness is associated with various macro- and micro-level background factors, including environmental conditions, such as weather and the economic situation, and personal health behaviors, such as smoking and exercise. We contribute to this literature of happiness studies by using a geospatial approach to examine both macro and micro links to personal happiness. Our geospatial approach incorporates two major global datasets: representative national survey data from the International Social Survey Program (ISSP) and corresponding world weather data from the National Oceanic and Atmospheric Administration (NOAA). After processing and filtering 55,081 records of ISSP 2011 survey data from 32 countries, we extracted 5,420 records from China and 25,441 records from 28 other countries. Sensitivity analyses of different intervals for average weather variables showed that macro-level conditions, including temperature, wind speed, elevation, and GDP, are positively correlated with happiness. To distinguish the effects of weather conditions on happiness in different seasons, we also adopted climate zone and seasonal variables. The micro-level analysis indicated that better health status and eating more vegetables or fruits are highly associated with happiness. Never engaging in physical activity appears to make people less happy. The findings suggest that weather conditions, economic situations, and personal health behaviors are all correlated with levels of happiness. PMID:27078263

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

PubMed

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

2017-01-01

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

Effects of weather on the abundance and distribution on populations of 103 breeding bird species across the United States

NASA Astrophysics Data System (ADS)

Allstadt, A. J.; Gorzo, J.; Bateman, B. L.; Heglund, P. J.; Pidgeon, A. M.; Thogmartin, W.; Vavrus, S. J.; Radeloff, V.

2016-12-01

Often, fewer birds are often observed in an area experiencing extreme weather, as local populations tend to leave an area (via out-migration or concentration in refugia) or experience a change in population size (via mortality or reduced fecundity). Further, weather patterns are often coherent over large areas so unsuitable weather may threaten large portions of an entire species range simultaneously. However, beyond a few iconic irruptive species, rarely have studies applied both the necessary scale and sensitivity required to assess avian population responses over entire species range. Here, we examined the effects of pre-breeding season weather on the distribution and abundances of 103 North American bird species from the late 1966-2010 using observed abundance records from the Breeding Bird Survey. We compared abundances with measures of drought and temperature over each species' range, and with three atmospheric teleconnections that describe large-scale circulation patterns influencing conditions on the ground. More than 90% of the species responded to at least one of our five weather variables. Grassland bird species tended to be most responsive to weather conditions and forest birds the least, though we found relations among all habitat types. For most species, the response was movement rather than large effects on the overall population size. Maps of these responses indicate that concentration and out-migration are both common strategies for coping with challenging weather conditions across a species range. The dynamic distribution of many bird species makes clear the need to account for temporal variability in conservation planning, as areas that are less important for a species' breeding success in most years may be very important in years with abnormal weather conditions.

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

NASA Technical Reports Server (NTRS)

SaintCyr, Chris; Murtagh, Bill

2008-01-01

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

Weather sensitivity for zoo visitation in Toronto, Canada: a quantitative analysis of historical data

NASA Astrophysics Data System (ADS)

Hewer, Micah J.; Gough, William A.

2016-11-01

Based on a case study of the Toronto Zoo (Canada), multivariate regression analysis, involving both climatic and social variables, was employed to assess the relationship between daily weather and visitation. Zoo visitation was most sensitive to weather variability during the shoulder season, followed by the off-season and, then, the peak season. Temperature was the most influential weather variable in relation to zoo visitation, followed by precipitation and, then, wind speed. The intensity and direction of the social and climatic variables varied between seasons. Temperatures exceeding 26 °C during the shoulder season and 28 °C during the peak season suggested a behavioural threshold associated with zoo visitation, with conditions becoming too warm for certain segments of the zoo visitor market, causing visitor numbers to decline. Even light amounts of precipitation caused average visitor numbers to decline by nearly 50 %. Increasing wind speeds also demonstrated a negative influence on zoo visitation.

Variability of E. coli density and sources in an urban watershed.

PubMed

Wu, J; Rees, P; Dorner, S

2011-03-01

The objective of this study was to characterize the variability of Escherichia coli density and sources in an urban watershed, particularly to focus on the influences of weather and land use. E. coli as a microbial indicator was measured at fourteen sites in four wet weather events and four dry weather conditions in the upper Blackstone River watershed. The sources of E. coli were identified by ribotyping. The results showed that wet weather led to sharp increases of E. coli densities. Interestingly, an intense storm of short duration led to a higher E. coli density than a moderate storm of long duration (p<0.01). The ribotyping patterns revealed microbial sources were mainly attributed to humans and wildlife, but varied in different weather conditions and were associated with the patterns of land use. Human sources accounted for 24.43% in wet weather but only 9.09% in dry weather. In addition, human sources were more frequently observed in residential zones (>30% of the total sources), while wildlife sources were dominant in open land and forest zones (54%). The findings provide useful information for developing optimal management strategies aimed at reducing the level of pathogens in urban watersheds.

A resampling procedure for generating conditioned daily weather sequences

USGS Publications Warehouse

Clark, Martyn P.; Gangopadhyay, Subhrendu; Brandon, David; Werner, Kevin; Hay, Lauren E.; Rajagopalan, Balaji; Yates, David

2004-01-01

A method is introduced to generate conditioned daily precipitation and temperature time series at multiple stations. The method resamples data from the historical record “nens” times for the period of interest (nens = number of ensemble members) and reorders the ensemble members to reconstruct the observed spatial (intersite) and temporal correlation statistics. The weather generator model is applied to 2307 stations in the contiguous United States and is shown to reproduce the observed spatial correlation between neighboring stations, the observed correlation between variables (e.g., between precipitation and temperature), and the observed temporal correlation between subsequent days in the generated weather sequence. The weather generator model is extended to produce sequences of weather that are conditioned on climate indices (in this case the Niño 3.4 index). Example illustrations of conditioned weather sequences are provided for a station in Arizona (Petrified Forest, 34.8°N, 109.9°W), where El Niño and La Niña conditions have a strong effect on winter precipitation. The conditioned weather sequences generated using the methods described in this paper are appropriate for use as input to hydrologic models to produce multiseason forecasts of streamflow.

Weather conditions: a neglected factor in human salivary cortisol research?

NASA Astrophysics Data System (ADS)

Milas, Goran; Šupe-Domić, Daniela; Drmić-Hofman, Irena; Rumora, Lada; Klarić, Irena Martinović

2018-02-01

There is ample evidence that environmental stressors such as extreme weather conditions affect animal behavior and that this process is in part mediated through the elevated activity of the hypothalamic pituitary adrenal axis which results in an increase in cortisol secretion. This relationship has not been extensively researched in humans, and weather conditions have not been analyzed as a potential confounder in human studies of stress. Consequently, the goal of this paper was to assess the relationship between salivary cortisol and weather conditions in the course of everyday life and to test a possible moderating effect of two weather-related variables, the climate region and timing of exposure to outdoors conditions. The sample consisted of 903 secondary school students aged 18 to 21 years from Mediterranean and Continental regions. Cortisol from saliva was sampled in naturalistic settings at three time points over the course of a single day. We found that weather conditions are related to salivary cortisol concentration and that this relationship may be moderated by both the specific climate and the anticipation of immediate exposure to outdoors conditions. Unpleasant weather conditions are predictive for the level of salivary cortisol, but only among individuals who anticipate being exposed to it in the immediate future (e.g., in students attending school in the morning shift). We also demonstrated that isolated weather conditions or their patterns may be relevant in one climate area (e.g., Continental) while less relevant in the other (e.g., Mediterranean). Results of this study draw attention to the importance of controlling weather conditions in human salivary cortisol research.

Relationship between turbidity and total suspended solids concentration within a combined sewer system.

PubMed

Hannouche, A; Chebbo, G; Ruban, G; Tassin, B; Lemaire, B J; Joannis, C

2011-01-01

This article confirms the existence of a strong linear relationship between turbidity and total suspended solids (TSS) concentration. However, the slope of this relation varies between dry and wet weather conditions, as well as between sites. The effect of this variability on estimating the instantaneous wet weather TSS concentration is assessed on the basis of the size of the calibration dataset used to establish the turbidity - TSS relationship. Results obtained indicate limited variability both between sites and during dry weather, along with a significant inter-event variability. Moreover, turbidity allows an evaluation of TSS concentrations with an acceptable level of accuracy for a reasonable rainfall event sampling campaign effort.

Weather and place-based human behavior: recreational preferences and sensitivity

NASA Astrophysics Data System (ADS)

de Freitas, C. R.

2015-01-01

This study examines the links between biometeorological variables and the behavior of beach recreationists along with their rating of overall weather conditions. To identify and describe significance of on-site atmospheric conditions, two separate forms of response are examined. The first is sensory perception of the immediate atmospheric surround expressed verbally, which was the subject of earlier work. In the research reported here, on-site observations of behavior that reflect the effects of weather and climate are examined. By employing, independently, separate indicators of on-site experience, the reliability of each is examined and interpreted and apparent threshold conditions verified. The study site is King's Beach located on the coast of Queensland, Australia. On-site observations of atmospheric variables and beach user behavior are made for the daylight hours of 45 days spread over a 12-month period. The results show that behavioral data provide reliable and meaningful indications of the significance of the atmospheric environment for leisure. Atmospheric conditions within the zone of acceptability are those that the beach users can readily cope with or modify by a range of minor behavioral adjustments. Optimal weather conditions appear to be those requiring no specific behavioral adjustment. Attendance levels reflect only the outer limits of acceptability of the meteorological environment, while duration of visit enables calibration of levels of approval in so far as it reflects rating of on-site weather within a broad zone of tolerance. In a broad theoretical sense, the results add to an understanding of the relationship between weather and human behavior. This information is potentially useful in effective tourism management and planning.

Seasonal variation, weather and behavior in day-care children: a multilevel approach

NASA Astrophysics Data System (ADS)

Ciucci, Enrica; Calussi, Pamela; Menesini, Ersilia; Mattei, Alessandra; Petralli, Martina; Orlandini, Simone

2013-11-01

This study analyzes the effect of weather variables, such as solar radiation, indoor and outdoor air temperature, relative humidity and time spent outdoor, on the behavior of 2-year-old children and their affects across different seasons: winter, spring and summer. Participants were a group of 61 children (33 males and 28 females) attending four day-care centers in Florence (Central Italy). Mean age of children at the beginning of the study was 24.1 months ( SD = 3.6). We used multilevel linear analyses to account for the hierarchical structure of our data. The study analyzed the following behavioral variables: Activity Level, Attentional Focusing, Frustration, and Aggression. Results showed a different impact of some weather variables on children’s behavior across seasons, indicating that the weather variable that affects children’s behavior is usually the one that shows extreme values during the studied seasons, such as air temperature and relative humidity in winter and summer. Studying children and their reactions to weather conditions could have potentially wide-reaching implications for parenting and teaching practices, as well as for researchers studying social relationships development.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

Natural turbidity variability and weather forecasts in risk management of anthropogenic sediment discharge near sensitive environments.

PubMed

Orpin, Alan R; Ridd, Peter V; Thomas, Séverine; Anthony, Kenneth R N; Marshall, Paul; Oliver, Jamie

2004-10-01

Coastal development activities can cause local increases in turbidity and sedimentation. This study characterises the spatial and temporal variability of turbidity near an inshore fringing coral reef in the central Great Barrier Reef, under a wide range of natural conditions. Based on the observed natural variability, we outline a risk management scheme to minimise the impact of construction-related turbidity increases. Comparison of control and impact sites proved unusable for real-time management of turbidity risks. Instead, we suggest using one standard deviation from ambient conditions as a possible conservative upper limit of an acceptable projected increase in turbidity. In addition, the use of regional weather forecast as a proxy for natural turbidity is assessed. This approach is simple and cheap but also has limitations in very rough conditions, when an anthropogenic turbidity increase could prove fatal to corals that are already stressed under natural conditions.

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management

USGS Publications Warehouse

Jonas, Jayne L.; Buhl, Deborah A.; Symstad, Amy J.

2015-01-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess 1) the portion of interannual variability of richness and diversity explained by weather, 2) how relationships between these metrics and weather vary among plant assemblages, and 3) which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six datasets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.Read More: http://www.esajournals.org/doi/abs/10.1890/14-1989.1

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management.

PubMed

Jonas, Jayne L; Buhl, Deborah A; Symstad, Amy J

2015-09-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess the portion of interannual variability of richness and diversity explained by weather, how relationships between these metrics and weather vary among plant assemblages, and which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six data sets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.

Weather sensitivity for zoo visitation in Toronto, Canada: a quantitative analysis of historical data.

PubMed

Hewer, Micah J; Gough, William A

2016-11-01

Based on a case study of the Toronto Zoo (Canada), multivariate regression analysis, involving both climatic and social variables, was employed to assess the relationship between daily weather and visitation. Zoo visitation was most sensitive to weather variability during the shoulder season, followed by the off-season and, then, the peak season. Temperature was the most influential weather variable in relation to zoo visitation, followed by precipitation and, then, wind speed. The intensity and direction of the social and climatic variables varied between seasons. Temperatures exceeding 26 °C during the shoulder season and 28 °C during the peak season suggested a behavioural threshold associated with zoo visitation, with conditions becoming too warm for certain segments of the zoo visitor market, causing visitor numbers to decline. Even light amounts of precipitation caused average visitor numbers to decline by nearly 50 %. Increasing wind speeds also demonstrated a negative influence on zoo visitation.

A conceptual weather-type classification procedure for the Philadelphia, Pennsylvania, area

USGS Publications Warehouse

McCabe, Gregory J.

1990-01-01

A simple method of weather-type classification, based on a conceptual model of pressure systems that pass through the Philadelphia, Pennsylvania, area, has been developed. The only inputs required for the procedure are daily mean wind direction and cloud cover, which are used to index the relative position of pressure systems and fronts to Philadelphia.Daily mean wind-direction and cloud-cover data recorded at Philadelphia, Pennsylvania, from January 1954 through August 1988 were used to categorize daily weather conditions. The conceptual weather types reflect changes in daily air and dew-point temperatures, and changes in monthly mean temperature and monthly and annual precipitation. The weather-type classification produced by using the conceptual model was similar to a classification produced by using a multivariate statistical classification procedure. Even though the conceptual weather types are derived from a small amount of data, they appear to account for the variability of daily weather patterns sufficiently to describe distinct weather conditions for use in environmental analyses of weather-sensitive processes.

Nonlinear dynamics of global atmospheric and Earth system processes

NASA Technical Reports Server (NTRS)

Saltzman, Barry

1993-01-01

During the past eight years, we have been engaged in a NASA-supported program of research aimed at establishing the connection between satellite signatures of the earth's environmental state and the nonlinear dynamics of the global weather and climate system. Thirty-five publications and four theses have resulted from this work, which included contributions in five main areas of study: (1) cloud and latent heat processes in finite-amplitude baroclinic waves; (2) application of satellite radiation data in global weather analysis; (3) studies of planetary waves and low-frequency weather variability; (4) GCM studies of the atmospheric response to variable boundary conditions measurable from satellites; and (5) dynamics of long-term earth system changes. Significant accomplishments from the three main lines of investigation pursued during the past year are presented and include the following: (1) planetary atmospheric waves and low frequency variability; (2) GCM studies of the atmospheric response to changed boundary conditions; and (3) dynamics of long-term changes in the global earth system.

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

USGS Publications Warehouse

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

2016-01-01

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

Simulating soybean canopy temperature as affected by weather variables and soil water potential

NASA Technical Reports Server (NTRS)

Choudhury, B. J.

1982-01-01

Hourly weather data for several clear sky days during summer at Phoenix and Baltimore which covered a wide range of variables were used with a plant atmosphere model to simulate soybean (Glycine max L.) leaf water potential, stomatal resistance and canopy temperature at various soil water potentials. The air and dew point temperatures were found to be the significant weather variables affecting the canopy temperatures. Under identical weather conditions, the model gives a lower canopy temperature for a soybean crop with a higher rooting density. A knowledge of crop rooting density, in addition to air and dew point temperatures is needed in interpreting infrared radiometric observations for soil water status. The observed dependence of stomatal resistance on the vapor pressure deficit and soil water potential is fairly well represented. Analysis of the simulated leaf water potentials indicates overestimation, possibly due to differences in the cultivars.

Weather, Climate, and You.

ERIC Educational Resources Information Center

Blai, Boris, Jr.

Information from the American Institute of Medical Climatologists on human responses to weather and climatic conditions, including clouds, winds, humidity, barometric pressure, heat, cold, and other variables that may exert a pervasive impact on health, behavior, disposition, and the level of efficiency with which individuals function is reviewed.…

'Weather Value at Risk': A uniform approach to describe and compare sectoral income risks from climate change.

PubMed

Prettenthaler, Franz; Köberl, Judith; Bird, David Neil

2016-02-01

We extend the concept of 'Weather Value at Risk' - initially introduced to measure the economic risks resulting from current weather fluctuations - to describe and compare sectoral income risks from climate change. This is illustrated using the examples of wheat cultivation and summer tourism in (parts of) Sardinia. Based on climate scenario data from four different regional climate models we study the change in the risk of weather-related income losses between some reference (1971-2000) and some future (2041-2070) period. Results from both examples suggest an increase in weather-related risks of income losses due to climate change, which is somewhat more pronounced for summer tourism. Nevertheless, income from wheat cultivation is at much higher risk of weather-related losses than income from summer tourism, both under reference and future climatic conditions. A weather-induced loss of at least 5% - compared to the income associated with average reference weather conditions - shows a 40% (80%) probability of occurrence in the case of wheat cultivation, but only a 0.4% (16%) probability of occurrence in the case of summer tourism, given reference (future) climatic conditions. Whereas in the agricultural example increases in the weather-related income risks mainly result from an overall decrease in average wheat yields, the heightened risk in the tourism example stems mostly from a change in the weather-induced variability of tourism incomes. With the extended 'Weather Value at Risk' concept being able to capture both, impacts from changes in the mean and the variability of the climate, it is a powerful tool for presenting and disseminating the results of climate change impact assessments. Due to its flexibility, the concept can be applied to any economic sector and therefore provides a valuable tool for cross-sectoral comparisons of climate change impacts, but also for the assessment of the costs and benefits of adaptation measures. Copyright © 2015 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Relative roles of weather variables and change in human population in malaria: comparison over different states of India.

PubMed

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria.

Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India

PubMed Central

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Background Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. Method We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. Results For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. Conclusion The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria. PMID:24971510

Trace fossils, sedimentary facies and parasequence architecture from the Lower Cretaceous Mulichinco Formation of Argentina: The role of fair-weather waves in shoreface deposits

NASA Astrophysics Data System (ADS)

Wesolowski, Lindsey J. N.; Buatois, Luis A.; Mángano, M. Gabriela; Ponce, Juan José; Carmona, Noelia B.

2018-05-01

Shorefaces can display strong facies variability and integration of sedimentology and ichnology provides a high-resolution model to identify variations among strongly storm-dominated (high energy), moderately storm-affected (intermediate energy), and weakly storm-affected (low energy) shoreface deposits. In addition, ichnology has proved to be of help to delineate parasequences as trace-fossil associations are excellent indicators of environmental conditions which typically change along the depositional profile. Shallow-marine deposits and associated ichnofaunas from the Mulichinco Formation (Valanginian, Lower Cretaceous) in Puerta Curaco, Neuquén Basin, western Argentina, were analyzed to evaluate stress factors on shoreface benthos and parasequence architecture. During storm-dominated conditions, the Skolithos Ichnofacies prevails within the offshore transition and lower shoreface represented by assemblages dominated by Thalassinoides isp. and Ophiomorpha irregulaire. Under weakly storm-affected conditions, the Cruziana Ichnofacies is recognized, characterized by assemblages dominated by Thalassinoides isp. and Gyrochorte comosa in the offshore transition, and by Gyrochorte comosa within the lower shoreface. Storm-influenced conditions yield wider ichnologic variability, showing elements of both ichnofacies. Storm influence on sedimentation is affected by both allogenic (e.g. tectonic subsidence, sea-level, and sediment influx) and autogenic (e.g. hydrodynamic) controls at both parasequence and intra-parasequence scales. Four distinct types of parasequences were recognized, strongly storm-dominated, moderately storm-affected, moderately storm-affected - strongly fair-weather reworked, and weakly storm-affected, categorized based on parasequence architectural variability derived from varying degrees of storm and fair-weather wave influence. The new type of shoreface described here, the moderately storm-affected - strongly fair-weather reworked shoreface, features storm deposits reworked thoroughly by fair-weather waves. During fair-weather wave reworking, elements of the Cruziana Ichnofacies are overprinted upon relict elements of the Skolithos Ichnofacies from previous storm induced deposition. This type of shoreface, commonly overlooked in past literature, expands our understanding of the sedimentary dynamics and stratigraphic architecture in a shoreface susceptible to various parasequence and intra-parasequence scale degrees of storm and fair-weather wave influence.

El Niño and human health.

PubMed Central

Kovats, R. S.

2000-01-01

The El Niño-Southern Oscillation (ENSO) is the best known example of quasi-periodic natural climate variability on the interannual time scale. It comprises changes in sea temperature in the Pacific Ocean (El Niño) and changes in atmospheric pressure across the Pacific Basin (the Southern Oscillation), together with resultant effects on world weather. El Niño events occur at intervals of 2-7 years. In certain countries around the Pacific and beyond, El Niño is associated with extreme weather conditions that can cause floods and drought. Globally it is linked to an increased impact of natural disasters. There is evidence that ENSO is associated with a heightened risk of certain vector-borne diseases in specific geographical areas where weather patterns are linked with the ENSO cycle and disease control is limited. This is particularly true for malaria, but associations are also suggested in respect of epidemics of other mosquito-borne and rodent-borne diseases that can be triggered by extreme weather conditions. Seasonal climate forecasts, predicting the likelihood of weather patterns several months in advance, can be used to provide early indicators of epidemic risk, particularly for malaria. Interdisciplinary research and cooperation are required in order to reduce vulnerability to climate variability and weather extremes. PMID:11019461

Effects of weather conditions, light conditions, and road lighting on vehicle speed.

PubMed

Jägerbrand, Annika K; Sjöbergh, Jonas

2016-01-01

Light conditions are known to affect the number of vehicle accidents and fatalities but the relationship between light conditions and vehicle speed is not fully understood. This study examined whether vehicle speed on roads is higher in daylight and under road lighting than in darkness, and determined the combined effects of light conditions, posted speed limit and weather conditions on driving speed. The vehicle speed of passenger cars in different light conditions (daylight, twilight, darkness, artificial light) and different weather conditions (clear weather, rain, snow) was determined using traffic and weather data collected on an hourly basis for approximately 2 years (1 September 2012-31 May 2014) at 25 locations in Sweden (17 with road lighting and eight without). In total, the data included almost 60 million vehicle passes. The data were cleaned by removing June, July, and August, which have different traffic patterns than the rest of the year. Only data from the periods 10:00 A.M.-04:00 P.M. and 06:00 P.M.-10:00 P.M. were used, to remove traffic during rush hour and at night. Multivariate adaptive regression splines was used to evaluate the overall influence of independent variables on vehicle speed and nonparametric statistical testing was applied to test for speed differences between dark-daylight, dark-twilight, and twilight-daylight, on roads with and without road lighting. The results show that vehicle speed in general depends on several independent variables. Analyses of vehicle speed and speed differences between daylight, twilight and darkness, with and without road lighting, did not reveal any differences attributable to light conditions. However, vehicle speed decreased due to rain or snow and the decrease was higher on roads without road lighting than on roads with lighting. These results suggest that the strong association between traffic accidents and darkness or low light conditions could be explained by drivers failing to adjust their speed to the reduced visibility in dark conditions.

Local Infrasound Variability Related to In Situ Atmospheric Observation

NASA Astrophysics Data System (ADS)

Kim, Keehoon; Rodgers, Arthur; Seastrand, Douglas

2018-04-01

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

Panic anxiety, under the weather?

NASA Astrophysics Data System (ADS)

Bulbena, A.; Pailhez, G.; Aceña, R.; Cunillera, J.; Rius, A.; Garcia-Ribera, C.; Gutiérrez, J.; Rojo, C.

2005-03-01

The relationship between weather conditions and psychiatric disorders has been a continuous subject of speculation due to contradictory findings. This study attempts to further clarify this relationship by focussing on specific conditions such as panic attacks and non-panic anxiety in relation to specific meteorological variables. All psychiatric emergencies attended at a general hospital in Barcelona (Spain) during 2002 with anxiety as main complaint were classified as panic or non-panic anxiety according to strict independent and retrospective criteria. Both groups were assessed and compared with meteorological data (wind speed and direction, daily rainfall, temperature, humidity and solar radiation). Seasons and weekend days were also included as independent variables. Non-parametric statistics were used throughout since most variables do not follow a normal distribution. Logistic regression models were applied to predict days with and without the clinical condition. Episodes of panic were three times more common with the poniente wind (hot wind), twice less often with rainfall, and one and a half times more common in autumn than in other seasons. These three trends (hot wind, rainfall and autumn) were accumulative for panic episodes in a logistic regression formula. Significant reduction of episodes on weekends was found only for non-panic episodes. Panic attacks, unlike other anxiety episodes, in a psychiatric emergency department in Barcelona seem to show significant meteorotropism. Assessing specific disorders instead of overall emergencies or other variables of a more general quality could shed new light on the relationship between weather conditions and behaviour.

Fuel age and fire spread: Natural conditions versus opportunities for fire suppression

USGS Publications Warehouse

Halsey, Richard W.; Keeley, Jon E.; Wilson, Kit

2009-01-01

Wildfires are driven and restrained by an interplay of variables that can lead to many potential outcomes. As every wildland firefighter learns in basic training, the ability of a fire to spread is determined by three basic variables: fuel type and condition, weather, and topography. Fire suppression obviously plays a significant role in determining fire spread as well, so firefighter activity becomes an additional variable.

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

DOE PAGES

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.; ...

2018-05-18

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

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

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

Weather, day length and physical activity in older adults: Cross-sectional results from the European Prospective Investigation into Cancer and Nutrition (EPIC) Norfolk Cohort.

PubMed

Wu, Yu-Tzu; Luben, Robert; Wareham, Nicholas; Griffin, Simon; Jones, Andy P

2017-01-01

A wide range of environmental factors have been related to active ageing, but few studies have explored the impact of weather and day length on physical activity in older adults. We investigate the cross-sectional association between weather conditions, day length and activity in older adults using a population-based cohort in England, the European Prospective Investigation into Cancer and Nutrition (EPIC) Norfolk study. Physical activity was measured objectively over 7 days using an accelerometer and this was used to calculate daily total physical activity (counts per minute), daily minutes of sedentary behaviour and light, moderate and vigorous physical activity (LMVPA). Day length and two types of weather conditions, precipitation and temperature, were obtained from a local weather station. The association between these variables and physical activity was examined by multilevel first-order autoregressive modelling. After adjusting for individual factors, short day length and poor weather conditions, including high precipitation and low temperatures, were associated with up to 10% lower average physical activity (p<0.01) and 8 minutes less time spent in LMVPA but 15 minutes more sedentary time, compared to the best conditions. Day length and weather conditions appear to be an important factor related to active ageing. Future work should focus on developing potential interventions to reduce their impact on physical activity behaviours in older adults.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

VNIR hyperspectral background characterization methods in adverse weather conditions

NASA Astrophysics Data System (ADS)

Romano, João M.; Rosario, Dalton; Roth, Luz

2009-05-01

Hyperspectral technology is currently being used by the military to detect regions of interest where potential targets may be located. Weather variability, however, may affect the ability for an algorithm to discriminate possible targets from background clutter. Nonetheless, different background characterization approaches may facilitate the ability for an algorithm to discriminate potential targets over a variety of weather conditions. In a previous paper, we introduced a new autonomous target size invariant background characterization process, the Autonomous Background Characterization (ABC) or also known as the Parallel Random Sampling (PRS) method, features a random sampling stage, a parallel process to mitigate the inclusion by chance of target samples into clutter background classes during random sampling; and a fusion of results at the end. In this paper, we will demonstrate how different background characterization approaches are able to improve performance of algorithms over a variety of challenging weather conditions. By using the Mahalanobis distance as the standard algorithm for this study, we compare the performance of different characterization methods such as: the global information, 2 stage global information, and our proposed method, ABC, using data that was collected under a variety of adverse weather conditions. For this study, we used ARDEC's Hyperspectral VNIR Adverse Weather data collection comprised of heavy, light, and transitional fog, light and heavy rain, and low light conditions.

Fuzzy Rule Suram for Wood Drying

NASA Astrophysics Data System (ADS)

Situmorang, Zakarias

2017-12-01

Implemented of fuzzy rule must used a look-up table as defuzzification analysis. Look-up table is the actuator plant to doing the value of fuzzification. Rule suram based of fuzzy logic with variables of weather is temperature ambient and humidity ambient, it implemented for wood drying process. The membership function of variable of state represented in error value and change error with typical map of triangle and map of trapezium. Result of analysis to reach 4 fuzzy rule in 81 conditions to control the output system can be constructed in a number of way of weather and conditions of air. It used to minimum of the consumption of electric energy by heater. One cycle of schedule drying is a serial of condition of chamber to process as use as a wood species.

Variable Speed Limit (VSL) - Best Management Practice [Summary

DOT National Transportation Integrated Search

2012-01-01

In variable speed limit (VSL) zones, the speed : limit changes in response to traffic congestion, : adverse weather, or road conditions. VSL zones are : often highly automated and have been employed : successfully in several U.S. and European : locat...

Effects of weather and heliophysical conditions on emergency ambulance calls for elevated arterial blood pressure.

PubMed

Vencloviene, Jone; Babarskiene, Ruta M; Dobozinskas, Paulius; Sakalyte, Gintare; Lopatiene, Kristina; Mikelionis, Nerijus

2015-02-27

We hypothesized that weather and space weather conditions were associated with the exacerbation of essential hypertension. The study was conducted during 2009-2010 in the city of Kaunas, Lithuania. We analyzed 13,475 cards from emergency ambulance calls (EACs), in which the conditions for the emergency calls were made coded I.10-I.15. The Kaunas Weather Station provided daily records of air temperature (T), wind speed (WS), relative humidity, and barometric pressure (BP). We evaluated the associations between daily weather variables and daily number of EACs by applying a multivariate Poisson regression. Unfavorable heliophysical conditions (two days after the active-stormy geomagnetic field or the days with solar WS>600 km/s) increased the daily number of elevated arterial blood pressure (EABP) by 12% (RR=1.12; 95% confidence interval (CI) 1.04-1.21); and WS≥3.5 knots during days of T<1.5 °C and T≥12.5 °C by 8% (RR=1.08; CI 1.04-1.12). An increase of T by 10 °C and an elevation of BP two days after by 10 hPa were associated with a decrease in RR by 3%. An additional effect of T was detected during days of T≥17.5 °C only in females. Women and patients with grade III arterial hypertension at the time of the ambulance call were more sensitive to weather conditions. These results may help in the understanding of the population's sensitivity to different weather conditions.

Future sea ice conditions and weather forecasts in the Arctic: Implications for Arctic shipping.

PubMed

Gascard, Jean-Claude; Riemann-Campe, Kathrin; Gerdes, Rüdiger; Schyberg, Harald; Randriamampianina, Roger; Karcher, Michael; Zhang, Jinlun; Rafizadeh, Mehrad

2017-12-01

The ability to forecast sea ice (both extent and thickness) and weather conditions are the major factors when it comes to safe marine transportation in the Arctic Ocean. This paper presents findings focusing on sea ice and weather prediction in the Arctic Ocean for navigation purposes, in particular along the Northeast Passage. Based on comparison with the observed sea ice concentrations for validation, the best performing Earth system models from the Intergovernmental Panel on Climate Change (IPCC) program (CMIP5-Coupled Model Intercomparison Project phase 5) were selected to provide ranges of potential future sea ice conditions. Our results showed that, despite a general tendency toward less sea ice cover in summer, internal variability will still be large and shipping along the Northeast Passage might still be hampered by sea ice blocking narrow passages. This will make sea ice forecasts on shorter time and space scales and Arctic weather prediction even more important.

Explaining the road accident risk: weather effects.

PubMed

Bergel-Hayat, Ruth; Debbarh, Mohammed; Antoniou, Constantinos; Yannis, George

2013-11-01

This research aims to highlight the link between weather conditions and road accident risk at an aggregate level and on a monthly basis, in order to improve road safety monitoring at a national level. It is based on some case studies carried out in Work Package 7 on "Data analysis and synthesis" of the EU-FP6 project "SafetyNet-Building the European Road Safety Observatory", which illustrate the use of weather variables for analysing changes in the number of road injury accidents. Time series analysis models with explanatory variables that measure the weather quantitatively were used and applied to aggregate datasets of injury accidents for France, the Netherlands and the Athens region, over periods of more than 20 years. The main results reveal significant correlations on a monthly basis between weather variables and the aggregate number of injury accidents, but the magnitude and even the sign of these correlations vary according to the type of road (motorways, rural roads or urban roads). Moreover, in the case of the interurban network in France, it appears that the rainfall effect is mainly direct on motorways--exposure being unchanged, and partly indirect on main roads--as a result of changes in exposure. Additional results obtained on a daily basis for the Athens region indicate that capturing the within-the-month variability of the weather variables and including it in a monthly model highlights the effects of extreme weather. Such findings are consistent with previous results obtained for France using a similar approach, with the exception of the negative correlation between precipitation and the number of injury accidents found for the Athens region, which is further investigated. The outlook for the approach and its added value are discussed in the conclusion. Copyright © 2013. Published by Elsevier Ltd.

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

Treesearch

Jakob Zscheischler; Simone Fatichi; Sebastian Wolf; Peter D. Blanken; Gil Bohrer; Ken Clark; Ankur R. Desai; David Hollinger; Trevor Keenan; Kimberly A. Novick; Sonia I. Seneviratne

2016-01-01

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their...

Weather observations on Whistler Mountain during five storms

NASA Astrophysics Data System (ADS)

Thériault, Julie M.; Rasmussen, Kristen L.; Fisico, Teresa; Stewart, Ronald E.; Joe, Paul; Gultepe, Ismail; Clément, Marilys; Isaac, George A.

2014-01-01

A greater understanding of precipitation formation processes over complex terrain near the west coast of British Colombia will contribute to many relevant applications, such as climate studies, local hydrology, transportation, and winter sport competition. The phase of precipitation is difficult to determine because of the warm and moist weather conditions experienced during the wintertime in coastal mountain ranges. The goal of this study is to investigate the wide range of meteorological conditions that generated precipitation on Whistler Mountain from 4-12 March 2010 during the SNOW-V10 field campaign. During this time period, five different storms were documented in detail and were associated with noticeably different meteorological conditions in the vicinity of Whistler Mountain. New measurement techniques, along with the SNOW-V10 instrumentation, were used to obtain in situ observations during precipitation events along the Whistler mountainside. The results demonstrate a high variability of weather conditions ranging from the synoptic-scale to the macro-scale. These weather events were associated with a variation of precipitation along the mountainside, such as events associated with snow, snow pellets, and rain. Only two events associated with a rain-snow transition along the mountainside were observed, even though above-freezing temperatures along the mountainside were recorded 90 % of the time. On a smaller scale, these events were also associated with a high variability of snowflake types that were observed simultaneously near the top of Whistler Mountain. Overall, these detailed observations demonstrate the importance of understanding small-scale processes to improve observational techniques, short-term weather prediction, and longer-term climate projections over mountainous regions.

Microbial Load of Hard Red Winter Wheat Produced at Three Growing Environments across Nebraska, USA.

PubMed

Sabillón, Luis; Stratton, Jayne; Rose, Devin J; Regassa, Teshome H; Bianchini, Andréia

2016-04-01

Post-flowering weather variables in farm fields may influence the microbial loads of wheat grain. In this study, the effects of weather variables following wheat flowering on the microbiological quality of wheat were evaluated over two consecutive growing seasons (2011 to 2012 and 2012 to 2013) in the state of Nebraska, USA. Three hard red winter wheat lines, including two commercial cultivars (Overland and McGill) and one experimental line (NW07505), were planted in three regions with contrasting key weather variables (Southeast, South Central, and Panhandle district) to ensure that developing seeds were exposed to different weather conditions. The natural microbial flora and deoxynivalenol concentrations of 54 freshly harvested wheat samples (three samples per wheat line, with a total of 9 samples per district) were analyzed to evaluate the impacts of the weather conditions prevailing from flowering to harvesting in each growing location (district) and season on the microbiological quality and safety of wheat grain. In 2012, the values for aerobic plate counts, Enterobacteriaceae, yeasts, molds, and internal mold infection levels were significantly lower in grain samples collected from the Panhandle district than in grain harvested from the South Central and Southeastern districts. No significant differences in the yeast counts were found in grain collected from all districts in 2013, but the levels of internal mold infection and mold counts were significantly higher in grain from the Southeastern district than in grain from the Panhandle district. Deoxynivalenol was detected in all districts; however, the concentrations were below the advisory level of 1 mg/kg for processed wheat. Microbial growth during grain development seems to be dependent on the existence of a threshold level of weather variables during the season. In general, the microbial loads in wheat grain tended to be lower in those areas with lower relative humidity levels (below 55%) and with temperatures lower than 13.7°C and higher than 31.5°C.

Time-lagged effects of weather on plant demography: drought and Astragalus scaphoides.

PubMed

Tenhumberg, Brigitte; Crone, Elizabeth E; Ramula, Satu; Tyre, Andrew J

2018-04-01

Temperature and precipitation determine the conditions where plant species can occur. Despite their significance, to date, surprisingly few demographic field studies have considered the effects of abiotic drivers. This is problematic because anticipating the effect of global climate change on plant population viability requires understanding how weather variables affect population dynamics. One possible reason for omitting the effect of weather variables in demographic studies is the difficulty in detecting tight associations between vital rates and environmental drivers. In this paper, we applied Functional Linear Models (FLMs) to long-term demographic data of the perennial wildflower, Astragalus scaphoides, and explored sensitivity of the results to reduced amounts of data. We compared models of the effect of average temperature, total precipitation, or an integrated measure of drought intensity (standardized precipitation evapotranspiration index, SPEI), on plant vital rates. We found that transitions to flowering and recruitment in year t were highest if winter/spring of year t was wet (positive effect of SPEI). Counterintuitively, if the preceding spring of year t - 1 was wet, flowering probabilities were decreased (negative effect of SPEI). Survival of vegetative plants from t - 1 to t was also negatively affected by wet weather in the spring of year t - 1 and, for large plants, even wet weather in the spring of t - 2 had a negative effect. We assessed the integrated effect of all vital rates on life history performance by fitting FLMs to the asymptotic growth rate, log(λt). Log(λt) was highest if dry conditions in year t - 1 were followed by wet conditions in the year t. Overall, the positive effects of wet years exceeded their negative effects, suggesting that increasing frequency of drought conditions would reduce population viability of A. scaphoides. The drought signal weakened when reducing the number of monitoring years. Substituting space for time did not recover the weather signal, probably because the weather variables varied little between sites. We detected the SPEI signal when the analysis included data from two sites monitored over 20 yr (2 × 20 observations), but not when analyzing data from four sites monitored over 10 yr (4 × 10 observations). © 2018 by the Ecological Society of America.

Understanding the weather signal in national crop-yield variability

NASA Astrophysics Data System (ADS)

Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Pugh, Thomas A. M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, Anders

2017-06-01

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

Evaluating Weather Research and Forecasting Model Sensitivity to Land and Soil Conditions Representative of Karst Landscapes

NASA Astrophysics Data System (ADS)

Johnson, Christopher M.; Fan, Xingang; Mahmood, Rezaul; Groves, Chris; Polk, Jason S.; Yan, Jun

2018-03-01

Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land-atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant sensitivity responses are found over the karst regions, including pronounced warming and cooling effects on the near-surface atmosphere from barren and forested land cover, respectively; (3) the barren ground in the karst regions provides conditions favourable for convective development under certain conditions. Therefore, it is suggested that karst and non-karst landscapes should be distinguished, and their physical processes should be considered for future model development.

Weather, day length and physical activity in older adults: Cross-sectional results from the European Prospective Investigation into Cancer and Nutrition (EPIC) Norfolk Cohort

PubMed Central

Wu, Yu-Tzu; Luben, Robert; Wareham, Nicholas; Griffin, Simon; Jones, Andy P.

2017-01-01

Background A wide range of environmental factors have been related to active ageing, but few studies have explored the impact of weather and day length on physical activity in older adults. We investigate the cross-sectional association between weather conditions, day length and activity in older adults using a population-based cohort in England, the European Prospective Investigation into Cancer and Nutrition (EPIC) Norfolk study. Methods Physical activity was measured objectively over 7 days using an accelerometer and this was used to calculate daily total physical activity (counts per minute), daily minutes of sedentary behaviour and light, moderate and vigorous physical activity (LMVPA). Day length and two types of weather conditions, precipitation and temperature, were obtained from a local weather station. The association between these variables and physical activity was examined by multilevel first-order autoregressive modelling. Results After adjusting for individual factors, short day length and poor weather conditions, including high precipitation and low temperatures, were associated with up to 10% lower average physical activity (p<0.01) and 8 minutes less time spent in LMVPA but 15 minutes more sedentary time, compared to the best conditions. Conclusion Day length and weather conditions appear to be an important factor related to active ageing. Future work should focus on developing potential interventions to reduce their impact on physical activity behaviours in older adults. PMID:28562613

Prediction of County-Level Corn Yields Using an Energy-Crop Growth Index.

NASA Astrophysics Data System (ADS)

Andresen, Jeffrey A.; Dale, Robert F.; Fletcher, Jerald J.; Preckel, Paul V.

1989-01-01

Weather conditions significantly affect corn yields. while weather remains as the major uncontrolled variable in crop production, an understanding of the influence of weather on yields can aid in early and accurate assessment of the impact of weather and climate on crop yields and allow for timely agricultural extension advisories to help reduce farm management costs and improve marketing, decisions. Based on data for four representative countries in Indiana from 1960 to 1984 (excluding 1970 because of the disastrous southern corn leaf blight), a model was developed to estimate corn (Zea mays L.) yields as a function of several composite soil-crop-weather variables and a technology-trend marker, applied nitrogen fertilizer (N). The model was tested by predicting corn yields for 15 other counties. A daily energy-crop growth (ECG) variable in which different weights were used for the three crop-weather variables which make up the daily ECG-solar radiation intercepted by the canopy, a temperature function, and the ratio of actual to potential evapotranspiration-performed better than when the ECG components were weighted equally. The summation of the weighted daily ECG over a relatively short period (36 days spanning silk) was found to provide the best index for predicting county average corn yield. Numerical estimation results indicate that the ratio of actual to potential evapotranspiration (ET/PET) is much more important than the other two ECG factors in estimating county average corn yield in Indiana.

Balancing Europe's wind power output through spatial deployment informed by weather regimes.

PubMed

Grams, Christian M; Beerli, Remo; Pfenninger, Stefan; Staffell, Iain; Wernli, Heini

2017-08-01

As wind and solar power provide a growing share of Europe's electricity1, understanding and accommodating their variability on multiple timescales remains a critical problem. On weekly timescales, variability is related to long-lasting weather conditions, called weather regimes2-5, which can cause lulls with a loss of wind power across neighbouring countries6. Here we show that weather regimes provide a meteorological explanation for multi-day fluctuations in Europe's wind power and can help guide new deployment pathways which minimise this variability. Mean generation during different regimes currently ranges from 22 GW to 44 GW and is expected to triple by 2030 with current planning strategies. However, balancing future wind capacity across regions with contrasting inter-regime behaviour - specifically deploying in the Balkans instead of the North Sea - would almost eliminate these output variations, maintain mean generation, and increase fleet-wide minimum output. Solar photovoltaics could balance low-wind regimes locally, but only by expanding current capacity tenfold. New deployment strategies based on an understanding of continent-scale wind patterns and pan-European collaboration could enable a high share of wind energy whilst minimising the negative impacts of output variability.

Exploring adaptations to climate change with stakeholders: A participatory method to design grassland-based farming systems.

PubMed

Sautier, Marion; Piquet, Mathilde; Duru, Michel; Martin-Clouaire, Roger

2017-05-15

Research is expected to produce knowledge, methods and tools to enhance stakeholders' adaptive capacity by helping them to anticipate and cope with the effects of climate change at their own level. Farmers face substantial challenges from climate change, from changes in the average temperatures and the precipitation regime to an increased variability of weather conditions and the frequency of extreme events. Such changes can have dramatic consequences for many types of agricultural production systems such as grassland-based livestock systems for which climate change influences the seasonality and productivity of fodder production. We present a participatory design method called FARMORE (FARM-Oriented REdesign) that allows farmers to design and evaluate adaptations of livestock systems to future climatic conditions. It explicitly considers three climate features in the design and evaluation processes: climate change, climate variability and the limited predictability of weather. FARMORE consists of a sequence of three workshops for which a pre-existing game-like platform was adapted. Various year-round forage production and animal feeding requirements must be assembled by participants with a computerized support system. In workshop 1, farmers aim to produce a configuration that satisfies an average future weather scenario. They refine or revise the previous configuration by considering a sample of the between-year variability of weather in workshop 2. In workshop 3, they explicitly take the limited predictability of weather into account. We present the practical aspects of the method based on four case studies involving twelve farmers from Aveyron (France), and illustrate it through an in-depth description of one of these case studies with three dairy farmers. The case studies shows and discusses how workshop sequencing (1) supports a design process that progressively accommodates complexity of real management contexts by enlarging considerations of climate change to climate variability and low weather predictability, and (2) increases the credibility and salience of the design method. Further enhancements of the method are outlined, especially the selection of pertinent weather scenarios. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of Weather and Heliophysical Conditions on Emergency Ambulance Calls for Elevated Arterial Blood Pressure

PubMed Central

Vencloviene, Jone; Babarskiene, Ruta M.; Dobozinskas, Paulius; Sakalyte, Gintare; Lopatiene, Kristina; Mikelionis, Nerijus

2015-01-01

We hypothesized that weather and space weather conditions were associated with the exacerbation of essential hypertension. The study was conducted during 2009–2010 in the city of Kaunas, Lithuania. We analyzed 13,475 cards from emergency ambulance calls (EACs), in which the conditions for the emergency calls were made coded I.10–I.15. The Kaunas Weather Station provided daily records of air temperature (T), wind speed (WS), relative humidity, and barometric pressure (BP). We evaluated the associations between daily weather variables and daily number of EACs by applying a multivariate Poisson regression. Unfavorable heliophysical conditions (two days after the active-stormy geomagnetic field or the days with solar WS > 600 km/s) increased the daily number of elevated arterial blood pressure (EABP) by 12% (RR = 1.12; 95% confidence interval (CI) 1.04–1.21); and WS ≥ 3.5 knots during days of T < 1.5 °C and T ≥ 12.5 °C by 8% (RR = 1.08; CI 1.04–1.12). An increase of T by 10 °C and an elevation of BP two days after by 10 hPa were associated with a decrease in RR by 3%. An additional effect of T was detected during days of T ≥ 17.5 °C only in females. Women and patients with grade III arterial hypertension at the time of the ambulance call were more sensitive to weather conditions. These results may help in the understanding of the population’s sensitivity to different weather conditions. PMID:25734792

A hierarchical perspective on the diversity of butterfly species' responses to weather in the Sierra Nevada Mountains.

PubMed

Nice, Chris C; Forister, Matthew L; Gompert, Zachariah; Fordyce, James A; Shapiro, Arthur M

2014-08-01

An important and largely unaddressed issue in studies of biotic-abiotic relationships is the extent to which closely related species, or species living in similar habitats, have similar responses to weather. We addressed this by applying a hierarchical, Bayesian analytical framework to a long-term data set for butterflies which allowed us to simultaneously investigate responses of the entire fauna and individual species. A small number of variables had community-level effects. In particular, higher total annual snow depth had a positive effect on butterfly occurrences, while spring minimum temperature and El Niño-Southern Oscillation (ENSO) sea-surface variables for April-May had negative standardized coefficients. Our most important finding was that variables with large impacts at the community-level did not necessarily have a consistent response across all species. Species-level responses were much more similar to each other for snow depth compared to the other variables with strong community effects. This variation in species-level responses to weather variables raises important complications for the prediction of biotic responses to shifting climatic conditions. In addition, we found that clear associations with weather can be detected when considering ecologically delimited subsets of the community. For example, resident species and non-ruderal species had a much more unified response to weather variables compared to non-resident species and ruderal species, which suggests local adaptation to climate. These results highlight the complexity of biotic-abiotic interactions and confront that complexity with methodological advances that allow ecologists to understand communities and shifting climates while simultaneously revealing species-specific variation in response to climate.

Association of Day Length and Weather Conditions with Physical Activity Levels in Older Community Dwelling People

PubMed Central

Witham, Miles D.; Donnan, Peter T.; Vadiveloo, Thenmalar; Sniehotta, Falko F.; Crombie, Iain K.; Feng, Zhiqiang; McMurdo, Marion E. T.

2014-01-01

Background Weather is a potentially important determinant of physical activity. Little work has been done examining the relationship between weather and physical activity, and potential modifiers of any relationship in older people. We therefore examined the relationship between weather and physical activity in a cohort of older community-dwelling people. Methods We analysed prospectively collected cross-sectional activity data from community-dwelling people aged 65 and over in the Physical Activity Cohort Scotland. We correlated seven day triaxial accelerometry data with daily weather data (temperature, day length, sunshine, snow, rain), and a series of potential effect modifiers were tested in mixed models: environmental variables (urban vs rural dwelling, percentage of green space), psychological variables (anxiety, depression, perceived behavioural control), social variables (number of close contacts) and health status measured using the SF-36 questionnaire. Results 547 participants, mean age 78.5 years, were included in this analysis. Higher minimum daily temperature and longer day length were associated with higher activity levels; these associations remained robust to adjustment for other significant associates of activity: age, perceived behavioural control, number of social contacts and physical function. Of the potential effect modifier variables, only urban vs rural dwelling and the SF-36 measure of social functioning enhanced the association between day length and activity; no variable modified the association between minimum temperature and activity. Conclusions In older community dwelling people, minimum temperature and day length were associated with objectively measured activity. There was little evidence for moderation of these associations through potentially modifiable health, environmental, social or psychological variables. PMID:24497925

Association of day length and weather conditions with physical activity levels in older community dwelling people.

PubMed

Witham, Miles D; Donnan, Peter T; Vadiveloo, Thenmalar; Sniehotta, Falko F; Crombie, Iain K; Feng, Zhiqiang; McMurdo, Marion E T

2014-01-01

Weather is a potentially important determinant of physical activity. Little work has been done examining the relationship between weather and physical activity, and potential modifiers of any relationship in older people. We therefore examined the relationship between weather and physical activity in a cohort of older community-dwelling people. We analysed prospectively collected cross-sectional activity data from community-dwelling people aged 65 and over in the Physical Activity Cohort Scotland. We correlated seven day triaxial accelerometry data with daily weather data (temperature, day length, sunshine, snow, rain), and a series of potential effect modifiers were tested in mixed models: environmental variables (urban vs rural dwelling, percentage of green space), psychological variables (anxiety, depression, perceived behavioural control), social variables (number of close contacts) and health status measured using the SF-36 questionnaire. 547 participants, mean age 78.5 years, were included in this analysis. Higher minimum daily temperature and longer day length were associated with higher activity levels; these associations remained robust to adjustment for other significant associates of activity: age, perceived behavioural control, number of social contacts and physical function. Of the potential effect modifier variables, only urban vs rural dwelling and the SF-36 measure of social functioning enhanced the association between day length and activity; no variable modified the association between minimum temperature and activity. In older community dwelling people, minimum temperature and day length were associated with objectively measured activity. There was little evidence for moderation of these associations through potentially modifiable health, environmental, social or psychological variables.

Work zone variable speed limit systems: Effectiveness and system design issues.

DOT National Transportation Integrated Search

2010-03-01

Variable speed limit (VSL) systems have been used in a number of countries, particularly in Europe, as a method to improve flow and increase safety. VSLs use detectors to collect data on current traffic and/or weather conditions. Posted speed limits ...

Work zone variable speed limit systems : effectiveness and system design issues.

DOT National Transportation Integrated Search

2010-03-01

Variable speed limit (VSL) systems have been used in a number of countries, particularly in Europe, as a method to improve flow and increase safety. VSLs use detectors to collect data on current traffic and/or weather conditions. Posted speed limits ...

A conditional stochastic weather generator for seasonal to multi-decadal simulations

NASA Astrophysics Data System (ADS)

Verdin, Andrew; Rajagopalan, Balaji; Kleiber, William; Podestá, Guillermo; Bert, Federico

2018-01-01

We present the application of a parametric stochastic weather generator within a nonstationary context, enabling simulations of weather sequences conditioned on interannual and multi-decadal trends. The generalized linear model framework of the weather generator allows any number of covariates to be included, such as large-scale climate indices, local climate information, seasonal precipitation and temperature, among others. Here we focus on the Salado A basin of the Argentine Pampas as a case study, but the methodology is portable to any region. We include domain-averaged (e.g., areal) seasonal total precipitation and mean maximum and minimum temperatures as covariates for conditional simulation. Areal covariates are motivated by a principal component analysis that indicates the seasonal spatial average is the dominant mode of variability across the domain. We find this modification to be effective in capturing the nonstationarity prevalent in interseasonal precipitation and temperature data. We further illustrate the ability of this weather generator to act as a spatiotemporal downscaler of seasonal forecasts and multidecadal projections, both of which are generally of coarse resolution.

Seasonality and weather conditions jointly drive flight activity patterns of aquatic and terrestrial chironomids.

PubMed

Vebrová, Lucie; van Nieuwenhuijzen, Andre; Kolář, Vojtěch; Boukal, David S

2018-06-19

Chironomids, a major invertebrate taxon in many standing freshwaters, rely on adult flight to reach new suitable sites, yet the impact of weather conditions on their flight activity is little understood. We investigated diel and seasonal flight activity patterns of aquatic and terrestrial chironomids in a reclaimed sandpit area and analysed how weather conditions and seasonality influenced their total abundance and species composition. Air temperature, relative humidity, wind speed, and air pressure significantly affected total flight activity of both groups, but not in the same way. We identified an intermediate temperature and humidity optimum for the flight activity of terrestrial chironomids, which contrasted with weaker, timescale-dependent relationships in aquatic species. Flight activity of both groups further declined with wind speed and increased with air pressure. Observed flight patterns also varied in time on both daily and seasonal scale. Flight activity of both groups peaked in the evenings after accounting for weather conditions but, surprisingly, aquatic and terrestrial chironomids used partly alternating time windows for dispersal during the season. This may be driven by different seasonal trends of key environmental variables in larval habitats and hence implies that species phenologies and conditions experienced by chironomid larvae (and probably other aquatic insects with short-lived adults) influence adult flight patterns more than weather conditions. Our results provide detailed insights into the drivers of chironomid flight activity and highlight the methodological challenges arising from the inherent collinearity of weather characteristics and their diurnal and seasonal cycles.

Role of Winter Weather Conditions and Slipperiness on Tourists' Accidents in Finland.

PubMed

Lépy, Élise; Rantala, Sinikka; Huusko, Antti; Nieminen, Pentti; Hippi, Marjo; Rautio, Arja

2016-08-15

(1) BACKGROUND: In Finland, slippery snowy or icy ground surface conditions can be quite hazardous to human health during wintertime. We focused on the impacts of the variability in weather conditions on tourists' health via documented accidents during the winter season in the Sotkamo area. We attempted to estimate the slipping hazard in a specific context of space and time focusing on the weather and other possible parameters, responsible for fluctuations in the numbers of injuries/accidents; (2) METHODS: We used statistical distributions with graphical illustrations to examine the distribution of visits to Kainuu Hospital by non-local patients and their characteristics/causes; graphs to illustrate the distribution of the different characteristics of weather conditions; questionnaires and interviews conducted among health care and safety personnel in Sotkamo and Kuusamo; (3) RESULTS: There was a clear seasonal distribution in the numbers and types of extremity injuries of non-local patients. While the risk of slipping is emphasized, other factors leading to injuries are evaluated; and (4) CONCLUSIONS: The study highlighted the clear role of wintery weather conditions as a cause of extremity injuries even though other aspects must also be considered. Future scenarios, challenges and adaptive strategies are also discussed from the viewpoint of climate change.

Role of Winter Weather Conditions and Slipperiness on Tourists’ Accidents in Finland

PubMed Central

Lépy, Élise; Rantala, Sinikka; Huusko, Antti; Nieminen, Pentti; Hippi, Marjo; Rautio, Arja

2016-01-01

(1) Background: In Finland, slippery snowy or icy ground surface conditions can be quite hazardous to human health during wintertime. We focused on the impacts of the variability in weather conditions on tourists’ health via documented accidents during the winter season in the Sotkamo area. We attempted to estimate the slipping hazard in a specific context of space and time focusing on the weather and other possible parameters, responsible for fluctuations in the numbers of injuries/accidents; (2) Methods: We used statistical distributions with graphical illustrations to examine the distribution of visits to Kainuu Hospital by non-local patients and their characteristics/causes; graphs to illustrate the distribution of the different characteristics of weather conditions; questionnaires and interviews conducted among health care and safety personnel in Sotkamo and Kuusamo; (3) Results: There was a clear seasonal distribution in the numbers and types of extremity injuries of non-local patients. While the risk of slipping is emphasized, other factors leading to injuries are evaluated; and (4) Conclusions: The study highlighted the clear role of wintery weather conditions as a cause of extremity injuries even though other aspects must also be considered. Future scenarios, challenges and adaptive strategies are also discussed from the viewpoint of climate change. PMID:27537899

Bayesian hierarchical modelling of North Atlantic windiness

NASA Astrophysics Data System (ADS)

Vanem, E.; Breivik, O. N.

2013-03-01

Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operations to less extreme conditions. Nevertheless, possible changes in the statistics of extreme weather conditions, possibly due to anthropogenic climate change, represent an additional hazard to ship operations that is less straightforward to account for in a consistent way. Obviously, there are large uncertainties as to how future climate change will affect the extreme weather conditions at sea and there is a need for stochastic models that can describe the variability in both space and time at various scales of the environmental conditions. Previously, Bayesian hierarchical space-time models have been developed to describe the variability and complex dependence structures of significant wave height in space and time. These models were found to perform reasonably well and provided some interesting results, in particular, pertaining to long-term trends in the wave climate. In this paper, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over an area in the North Atlantic ocean is investigated. When the results from the model for North Atlantic windiness is compared to the results for significant wave height over the same area, it is interesting to observe that whereas an increasing trend in significant wave height was identified, no statistically significant long-term trend was estimated in windiness. This may indicate that the increase in significant wave height is not due to an increase in locally generated wind waves, but rather to increased swell. This observation is also consistent with studies that have suggested a poleward shift of the main storm tracks.

43 CFR 418.27 - Distribution system operation.

Code of Federal Regulations, 2010 CFR

2010-10-01

... authorized employees or agents to open and close individual turnouts and operate the distribution system... variable field conditions, weather, etc., they must immediately notify the District so proper adjustments...

A second generation climate index for tourism (CIT): specification and verification.

PubMed

de Freitas, C R; Scott, Daniel; McBoyle, Geoff

2008-05-01

Climate is a key resource for many types of tourism and as such can be measured and evaluated. An index approach is required for this task because of the multifaceted nature of weather and the complex ways that weather variables come together to give meaning to climate for tourism. Here we address the deficiencies of past indices by devising a theoretically sound and empirically tested method that integrates the various facets of climate and weather into a single index called the Climate Index for Tourism (CIT). CIT rates the climate resource for activities that are highly climate/weather sensitive, specifically, beach "sun, sea and sand" (3S) holidays. CIT integrates thermal (T), aesthetic (A) and physical (P) facets of weather, which are combined in a weather typology matrix to determine a climate satisfaction rating that ranges from very poor (1=unacceptable) to very good (7=optimal). Parameter A refers to sky condition and P to rain or high wind. T is the body-atmosphere energy balance that integrates the environmental and physiological thermal variables, such as solar heat load, heat loss by convection (wind) and by evaporation (sweating), longwave radiation exchange and metabolic heat (activity level). Rather than use T as a net energy (calorific) value, CIT requires that it be expressed as thermal sensation using the standard nine-point ASHRAE scale ("very hot" to "very cold"). In this way, any of the several body-atmosphere energy balance schemes available may be used, maximizing the flexibility of the index. A survey (N=331) was used to validate the initial CIT. Respondents were asked to rate nine thermal states (T) with different sky conditions (A). They were also asked to assess the impact of high winds or prolonged rain on the perceived quality of the overall weather condition. The data was analysed statistically to complete the weather typology matrix, which covered every possible combination of T, A and P. Conditions considered to be optimal (CIT class 6-7) for 3S tourism were those that were "slightly warm" with clear skies or scattered cloud (

A second generation climate index for tourism (CIT): specification and verification

NASA Astrophysics Data System (ADS)

de Freitas, C. R.; Scott, Daniel; McBoyle, Geoff

2008-05-01

Climate is a key resource for many types of tourism and as such can be measured and evaluated. An index approach is required for this task because of the multifaceted nature of weather and the complex ways that weather variables come together to give meaning to climate for tourism. Here we address the deficiencies of past indices by devising a theoretically sound and empirically tested method that integrates the various facets of climate and weather into a single index called the Climate Index for Tourism (CIT). CIT rates the climate resource for activities that are highly climate/weather sensitive, specifically, beach “sun, sea and sand” (3S) holidays. CIT integrates thermal (T), aesthetic (A) and physical (P) facets of weather, which are combined in a weather typology matrix to determine a climate satisfaction rating that ranges from very poor (1 = unacceptable) to very good (7 = optimal). Parameter A refers to sky condition and P to rain or high wind. T is the body-atmosphere energy balance that integrates the environmental and physiological thermal variables, such as solar heat load, heat loss by convection (wind) and by evaporation (sweating), longwave radiation exchange and metabolic heat (activity level). Rather than use T as a net energy (calorific) value, CIT requires that it be expressed as thermal sensation using the standard nine-point ASHRAE scale (“very hot” to “very cold”). In this way, any of the several body-atmosphere energy balance schemes available may be used, maximizing the flexibility of the index. A survey ( N = 331) was used to validate the initial CIT. Respondents were asked to rate nine thermal states (T) with different sky conditions (A). They were also asked to assess the impact of high winds or prolonged rain on the perceived quality of the overall weather condition. The data was analysed statistically to complete the weather typology matrix, which covered every possible combination of T, A and P. Conditions considered to be optimal (CIT class 6-7) for 3S tourism were those that were “slightly warm” with clear skies or scattered cloud (≤25% cloud). Acceptable conditions (CIT = 4-5) fell within the thermal range “indifferent” to “hot” even when the sky was overcast. Wind equal to or in excess of 6 m/s (22 km/h) or rain resulted in the CIT rating dropping to 1 or 2 (unacceptable) and was thus an override of pleasant thermal conditions. Further cross-cultural research is underway to examine whether climate preferences vary with different social and cultural tourist segments internationally.

Ensemble hydrological forecast efficiency evolution over various issue dates and lead-time: case study for the Cheboksary reservoir (Volga River)

NASA Astrophysics Data System (ADS)

Gelfan, Alexander; Moreido, Vsevolod

2017-04-01

Ensemble hydrological forecasting allows for describing uncertainty caused by variability of meteorological conditions in the river basin for the forecast lead-time. At the same time, in snowmelt-dependent river basins another significant source of uncertainty relates to variability of initial conditions of the basin (snow water equivalent, soil moisture content, etc.) prior to forecast issue. Accurate long-term hydrological forecast is most crucial for large water management systems, such as the Cheboksary reservoir (the catchment area is 374 000 sq.km) located in the Middle Volga river in Russia. Accurate forecasts of water inflow volume, maximum discharge and other flow characteristics are of great value for this basin, especially before the beginning of the spring freshet season that lasts here from April to June. The semi-distributed hydrological model ECOMAG was used to develop long-term ensemble forecast of daily water inflow into the Cheboksary reservoir. To describe variability of the meteorological conditions and construct ensemble of possible weather scenarios for the lead-time of the forecast, two approaches were applied. The first one utilizes 50 weather scenarios observed in the previous years (similar to the ensemble streamflow prediction (ESP) procedure), the second one uses 1000 synthetic scenarios simulated by a stochastic weather generator. We investigated the evolution of forecast uncertainty reduction, expressed as forecast efficiency, over various consequent forecast issue dates and lead time. We analyzed the Nash-Sutcliffe efficiency of inflow hindcasts for the period 1982 to 2016 starting from 1st of March with 15 days frequency for lead-time of 1 to 6 months. This resulted in the forecast efficiency matrix with issue dates versus lead-time that allows for predictability identification of the basin. The matrix was constructed separately for observed and synthetic weather ensembles.

A climate-based multivariate extreme emulator of met-ocean-hydrological events for coastal flooding

NASA Astrophysics Data System (ADS)

Camus, Paula; Rueda, Ana; Mendez, Fernando J.; Tomas, Antonio; Del Jesus, Manuel; Losada, Iñigo J.

2015-04-01

Atmosphere-ocean general circulation models (AOGCMs) are useful to analyze large-scale climate variability (long-term historical periods, future climate projections). However, applications such as coastal flood modeling require climate information at finer scale. Besides, flooding events depend on multiple climate conditions: waves, surge levels from the open-ocean and river discharge caused by precipitation. Therefore, a multivariate statistical downscaling approach is adopted to reproduce relationships between variables and due to its low computational cost. The proposed method can be considered as a hybrid approach which combines a probabilistic weather type downscaling model with a stochastic weather generator component. Predictand distributions are reproduced modeling the relationship with AOGCM predictors based on a physical division in weather types (Camus et al., 2012). The multivariate dependence structure of the predictand (extreme events) is introduced linking the independent marginal distributions of the variables by a probabilistic copula regression (Ben Ayala et al., 2014). This hybrid approach is applied for the downscaling of AOGCM data to daily precipitation and maximum significant wave height and storm-surge in different locations along the Spanish coast. Reanalysis data is used to assess the proposed method. A commonly predictor for the three variables involved is classified using a regression-guided clustering algorithm. The most appropriate statistical model (general extreme value distribution, pareto distribution) for daily conditions is fitted. Stochastic simulation of the present climate is performed obtaining the set of hydraulic boundary conditions needed for high resolution coastal flood modeling. References: Camus, P., Menéndez, M., Méndez, F.J., Izaguirre, C., Espejo, A., Cánovas, V., Pérez, J., Rueda, A., Losada, I.J., Medina, R. (2014b). A weather-type statistical downscaling framework for ocean wave climate. Journal of Geophysical Research, doi: 10.1002/2014JC010141. Ben Ayala, M.A., Chebana, F., Ouarda, T.B.M.J. (2014). Probabilistic Gaussian Copula Regression Model for Multisite and Multivariable Downscaling, Journal of Climate, 27, 3331-3347.

Online identification of wind model for improving quadcopter trajectory monitoring

NASA Astrophysics Data System (ADS)

Beniak, Ryszard; Gudzenko, Oleksandr

2017-10-01

In this paper, we consider a problem of quadcopter control in severe weather conditions. One type of such weather conditions is a strong variable wind. In this paper, we ponder deterministic and stochastic models of winds at low altitudes with the quadcopter performing aggressive maneuvers. We choose an adaptive algorithm as our control algorithm. This algorithm might seem suitable one to solve the given problem, as it is able to adjust quickly to changing conditions. However, as shown in the paper, this algorithm is not applicable to rapidly changing winds and requires additional filters to smooth the impulse streams, so as not to lose the stability of the object.

Weather conditions promote route flexibility during open ocean crossing in a long-distance migratory raptor

NASA Astrophysics Data System (ADS)

Mellone, Ugo; López-López, Pascual; Limiñana, Rubén; Urios, Vicente

2011-07-01

Weather conditions are paramount in shaping birds' migratory routes, promoting the evolution of behavioural plasticity and allowing for adaptive decisions on when to depart or stop during migration. Here, we describe and analyze the influence of weather conditions in shaping the sea-crossing stage of the pre-breeding journey made by a long-distance migratory bird, the Eleonora's falcon ( Falco eleonorae), tracked by satellite telemetry from the wintering grounds in the Southern Hemisphere to the breeding sites in the Northern Hemisphere. As far as we know, the data presented here are the first report of repeated oceanic journeys of the same individuals in consecutive years. Our results show inter-annual variability in the routes followed by Eleonora's falcons when crossing the Strait of Mozambique, between Madagascar and eastern continental Africa. Interestingly, our observations illustrate that individuals show high behavioural plasticity and are able to change their migration route from one year to another in response to weather conditions, thus minimising the risk of long ocean crossing by selecting winds blowing towards Africa for departure and changing the routes to avoid low pressure areas en route. Our results suggest that weather conditions can really act as obstacles during migration, and thus, besides ecological barriers, the migratory behaviour of birds could also be shaped by "meteorological barriers". We briefly discuss orientation mechanisms used for navigation. Since environmental conditions during migration could cause carry-over effects, we consider that forecasting how global changes of weather patterns will shape the behaviour of migratory birds is of the utmost importance.

ITS traffic data consolidation system

DOT National Transportation Integrated Search

2005-03-01

The Arizona Department of Transportation (ADOT) maintains a variety of independent applications to monitor roadway : conditions and activities across the state including traffic counts, weather data, signal timing, Variable Message Sign (VMS) : advis...

Weather and eared grebe winter migration near the Great Salt Lake, Utah.

PubMed

Williams, Augusta A; Laird, Neil F

2018-03-01

This study provides insight from the use of weather radar observations to understand the characteristics of the eared grebe migration near the Great Salt Lake (GSL) and provides unique information on weather conditions connected to these migration events. Doppler weather radar measurements from the Salt Lake City, Utah WSR-88D radar site (KMTX), along with meteorological surface and rawinsonde data, were used to identify and examine 281 eared grebe migration events across 15 winters from 1997/1998 through 2011/2012. An average of about 19 migration events occurred each winter with considerable interannual variability, as well as large variance in the spatial area and number of birds departing the GSL during each event. The migration events typically occurred during clear sky conditions in the presence of surface high pressure and colder than average surface temperatures. Migration events began 55 min after sunset, on average across the winter seasons, and in one case we demonstrate that an extended, nonstop flight was initiated of the departing eared grebes to northern Mexico. Eared grebes leaving the GSL largely flew above the freezing level with a mean northerly tailwind at flight altitude of 3.1 m s -1 and a westerly, cross-flight wind of 5.0 m s -1 while having an average flight speed at cruising altitude of 16.9 m s -1 , or 61 km h -1 . In addition to determining the variability of meteorological conditions during migration events across the 15 winters, atmospheric conditions during the largest migration event observed are presented and discussed.

Weather and eared grebe winter migration near the Great Salt Lake, Utah

NASA Astrophysics Data System (ADS)

Williams, Augusta A.; Laird, Neil F.

2018-03-01

This study provides insight from the use of weather radar observations to understand the characteristics of the eared grebe migration near the Great Salt Lake (GSL) and provides unique information on weather conditions connected to these migration events. Doppler weather radar measurements from the Salt Lake City, Utah WSR-88D radar site (KMTX), along with meteorological surface and rawinsonde data, were used to identify and examine 281 eared grebe migration events across 15 winters from 1997/1998 through 2011/2012. An average of about 19 migration events occurred each winter with considerable interannual variability, as well as large variance in the spatial area and number of birds departing the GSL during each event. The migration events typically occurred during clear sky conditions in the presence of surface high pressure and colder than average surface temperatures. Migration events began 55 min after sunset, on average across the winter seasons, and in one case we demonstrate that an extended, nonstop flight was initiated of the departing eared grebes to northern Mexico. Eared grebes leaving the GSL largely flew above the freezing level with a mean northerly tailwind at flight altitude of 3.1 m s-1 and a westerly, cross-flight wind of 5.0 m s-1 while having an average flight speed at cruising altitude of 16.9 m s-1, or 61 km h-1. In addition to determining the variability of meteorological conditions during migration events across the 15 winters, atmospheric conditions during the largest migration event observed are presented and discussed.

A preliminary look at AVE-SESAME 4 conducted on 9-10 May 1979

NASA Technical Reports Server (NTRS)

July, M.; Turner, R. E.

1980-01-01

This report contains information on data collected, symptotic conditions, and severe and unusual weather reported during the Atmospheric Variability Experiment Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME) 4 period. The information provides researchers a look at conditions during the period.

Extreme weather conditions reduce the CO2 fertilization effect in temperate C3 grasslands

NASA Astrophysics Data System (ADS)

Obermeier, Wolfgang; Lehnert, Lukas; Kammann, Claudia; Müller, Christoph; Grünhage, Ludger; Luterbacher, Jürg; Erbs, Martin; Yuan, Naiming; Bendix, Jörg

2016-04-01

The increase in atmospheric greenhouse gas concentrations from anthropogenic activities is the major driver of global climate change. The rising atmospheric carbon dioxide (CO2) concentrations may stimulate plant photosynthesis and, thus, cause a net sink effect in the global carbon cycle. As a consequence of an enhanced photosynthesis, an increase in the net primary productivity (NPP) of C3 plants (termed CO2 fertilization) is widely assumed. This process is associated with a reduced stomatal conductance of leaves as the carbon demand of photosynthesis is met earlier. This causes a higher water-use efficiency and, hence, may reduce water stress in plants exposed to elevated CO2 concentrations ([eCO2]). However, the magnitude and persistence of the CO2 fertilization effect under a future climate including more frequent weather extremes are controversial. To test the CO2 fertilization effect for Central European grasslands, a data set comprising 16 years of biomass samples and environmental variables such as local weather and soil conditions was analysed by means of a novel approach. The data set was recorded on a "Free Air Carbon dioxide Enrichment" (FACE) experimental site which allows to quantify the CO2 fertilization effect under naturally occurring climate variations. The results indicate that the CO2 fertilization effect on the aboveground biomass is strongest under local average environmental conditions. Such intermediate regimes were defined by the mean +/- 1 standard deviation of the long-term average in the respective variable three months before harvest. The observed CO2 fertilization effect was reduced or vanished under drier, wetter and hotter conditions when the respective variable exceeded the bounds of the intermediate regimes. Comparable conditions, characterized by a higher frequency of more extreme weather conditions, are predicted for the future by climate projections. Consequently, biogeochemical models may overestimate the future NPP sink capacity of temperate C3 grasslands. Because temperate grasslands represent an important part of the Earth's terrestrial surface and therefore the global carbon cycle, atmospheric CO2 concentrations [CO2] might increase faster than currently expected.

Differences in the importance of weather and weather-based decisions among campers in Ontario parks (Canada)

NASA Astrophysics Data System (ADS)

Hewer, Micah J.; Scott, Daniel J.; Gough, William A.

2017-10-01

Parks and protected areas represent an important resource for tourism in Canada, in which camping is a common recreational activity. The important relationship between weather and climate with recreation and tourism has been widely acknowledged within the academic literature. Howbeit, the need for activity-specific assessments has been identified as an on-going need for future research in the field of tourism climatology. Furthermore, very little is known about the interrelationships between personal characteristics and socio-demographics with weather preferences and behavioural thresholds. This study uses a stated climate preferences approach (survey responses) to explore differences in the importance of weather and related weather-based decisions among summer campers in Ontario parks. Statistically significant differences were found among campers for each of the four dependent variables tested in this study. Physically active campers placed greater importance on weather but were still more tolerant of adverse weather conditions. Older campers placed greater importance on weather. Campers travelling shorter distances placed greater importance on weather and were more likely to leave the park early due to adverse weather. Campers staying for longer periods of time were less likely to leave early due to weather and were willing to endure longer durations of adverse weather conditions. Beginner campers placed greater importance on weather, were more likely to leave early due to weather and recorded lower temporal weather thresholds. The results of this study contribute to the study of tourism climatology by furthering understanding of how personal characteristics such as gender, age, activity selection, trip duration, distance travelled, travel experience and life cycles affect weather preferences and decisions, focusing this time on recreational camping in a park tourism context.

Differences in the importance of weather and weather-based decisions among campers in Ontario parks (Canada).

PubMed

Hewer, Micah J; Scott, Daniel J; Gough, William A

2017-10-01

Parks and protected areas represent an important resource for tourism in Canada, in which camping is a common recreational activity. The important relationship between weather and climate with recreation and tourism has been widely acknowledged within the academic literature. Howbeit, the need for activity-specific assessments has been identified as an on-going need for future research in the field of tourism climatology. Furthermore, very little is known about the interrelationships between personal characteristics and socio-demographics with weather preferences and behavioural thresholds. This study uses a stated climate preferences approach (survey responses) to explore differences in the importance of weather and related weather-based decisions among summer campers in Ontario parks. Statistically significant differences were found among campers for each of the four dependent variables tested in this study. Physically active campers placed greater importance on weather but were still more tolerant of adverse weather conditions. Older campers placed greater importance on weather. Campers travelling shorter distances placed greater importance on weather and were more likely to leave the park early due to adverse weather. Campers staying for longer periods of time were less likely to leave early due to weather and were willing to endure longer durations of adverse weather conditions. Beginner campers placed greater importance on weather, were more likely to leave early due to weather and recorded lower temporal weather thresholds. The results of this study contribute to the study of tourism climatology by furthering understanding of how personal characteristics such as gender, age, activity selection, trip duration, distance travelled, travel experience and life cycles affect weather preferences and decisions, focusing this time on recreational camping in a park tourism context.

Asynchronous vegetation phenology enhances winter body condition of a large mobile herbivore.

PubMed

Searle, Kate R; Rice, Mindy B; Anderson, Charles R; Bishop, Chad; Hobbs, N T

2015-10-01

Understanding how spatial and temporal heterogeneity influence ecological processes forms a central challenge in ecology. Individual responses to heterogeneity shape population dynamics, therefore understanding these responses is central to sustainable population management. Emerging evidence has shown that herbivores track heterogeneity in nutritional quality of vegetation by responding to phenological differences in plants. We quantified the benefits mule deer (Odocoileus hemionus) accrue from accessing habitats with asynchronous plant phenology in northwest Colorado over 3 years. Our analysis examined both the direct physiological and indirect environmental effects of weather and vegetation phenology on mule deer winter body condition. We identified several important effects of annual weather patterns and topographical variables on vegetation phenology in the home ranges of mule deer. Crucially, temporal patterns of vegetation phenology were linked with differences in body condition, with deer tending to show poorer body condition in areas with less asynchronous vegetation green-up and later vegetation onset. The direct physiological effect of previous winter precipitation on mule deer body condition was much less important than the indirect effect mediated by vegetation phenology. Additionally, the influence of vegetation phenology on body fat was much stronger than that of overall vegetation productivity. In summary, changing annual weather patterns, particularly in relation to seasonal precipitation, have the potential to alter body condition of this important ungulate species during the critical winter period. This finding highlights the importance of maintaining large contiguous areas of spatially and temporally variable resources to allow animals to compensate behaviourally for changing climate-driven resource patterns.

Impacts from urban water systems on receiving waters - How to account for severe wet-weather events in LCA?

PubMed

Risch, Eva; Gasperi, Johnny; Gromaire, Marie-Christine; Chebbo, Ghassan; Azimi, Sam; Rocher, Vincent; Roux, Philippe; Rosenbaum, Ralph K; Sinfort, Carole

2018-01-01

Sewage systems are a vital part of the urban infrastructure in most cities. They provide drainage, which protects public health, prevents the flooding of property and protects the water environment around urban areas. On some occasions sewers will overflow into the water environment during heavy rain potentially causing unacceptable impacts from releases of untreated sewage into the environment. In typical Life Cycle Assessment (LCA) studies of urban wastewater systems (UWS), average dry-weather conditions are modelled while wet-weather flows from UWS, presenting a high temporal variability, are not currently accounted for. In this context, the loads from several storm events could be important contributors to the impact categories freshwater eutrophication and ecotoxicity. In this study we investigated the contributions of these wet-weather-induced discharges relative to average dry-weather conditions in the life cycle inventory for UWS. In collaboration with the Paris public sanitation service (SIAAP) and Observatory of Urban Pollutants (OPUR) program researchers, this work aimed at identifying and comparing contributing flows from the UWS in the Paris area by a selection of routine wastewater parameters and priority pollutants. This collected data is organized according to archetypal weather days during a reference year. Then, for each archetypal weather day and its associated flows to the receiving river waters (Seine), the parameters of pollutant loads (statistical distribution of concentrations and volumes) were determined. The resulting inventory flows (i.e. the potential loads from the UWS) were used as LCA input data to assess the associated impacts. This allowed investigating the relative importance of episodic wet-weather versus "continuous" dry-weather loads with a probabilistic approach to account for pollutant variability within the urban flows. The analysis at the scale of one year showed that storm events are significant contributors to the impacts of freshwater eutrophication and ecotoxicity compared to those arising from treated effluents. At the rain event scale the wet-weather contributions to these impacts are even more significant, accounting for example for up to 62% of the total impact on freshwater ecotoxicity. This also allowed investigating and discussing the ecotoxicity contribution of each class of pollutants among the broad range of inventoried substances. Finally, with such significant contributions of pollutant loads and associated impacts from wet-weather events, further research is required to better include temporally-differentiated emissions when evaluating eutrophication and ecotoxicity. This will provide a better understanding of how the performance of an UWS system affects the receiving environment for given local weather conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

Carisse, Odile; McNealis, Vanessa

2018-01-01

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

AgroClimate: Simulating and Monitoring the Risk of Extreme Weather Events from a Crop Phenology Perspective

NASA Astrophysics Data System (ADS)

Fraisse, C.; Pequeno, D.; Staub, C. G.; Perry, C.

2016-12-01

Climate variability, particularly the occurrence of extreme weather conditions such as dry spells and heat stress during sensitive crop developmental phases can substantially increase the prospect of reduced crop yields. Yield losses or crop failure risk due to stressful weather conditions vary mainly due to stress severity and exposure time and duration. The magnitude of stress effects is also crop specific, differing in terms of thresholds and adaptation to environmental conditions. To help producers in the Southeast USA mitigate and monitor the risk of crop losses due to extreme weather events we developed a web-based tool that evaluates the risk of extreme weather events during the season taking into account the crop development stages. Producers can enter their plans for the upcoming season in a given field (e.g. crop, variety, planting date, acreage etc.), select or not a specific El Nino Southern Oscillation (ENSO) phase, and will be presented with the probabilities (ranging from 0 -100%) of extreme weather events occurring during sensitive phases of the growing season for the selected conditions. The DSSAT models CERES-Maize, CROPGRO-Soybean, CROPGRO-Cotton, and N-Wheat phenology models have been translated from FORTRAN to a standalone versions in R language. These models have been tested in collaboration with Extension faculty and producers during the 2016 season and their usefulness for risk mitigation and monitoring evaluated. A companion AgroClimate app was also developed to help producers track and monitor phenology development during the cropping season.

SPAGETTA: a Multi-Purpose Gridded Stochastic Weather Generator

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Propagation of hydroclimatic variability through the critical zone

NASA Astrophysics Data System (ADS)

Porporato, A. M.; Calabrese, S.; Parolari, A.

2016-12-01

The interaction between soil moisture dynamics and mineral-weathering reactions (e.g., ion exchange, precipitation-dissolution) affects the availability of nutrients to plants, composition of soils, soil acidification, as well as CO2 sequestration. Across the critical zone (CZ), this interaction is responsible for propagating hydroclimatic fluctuations to deeper soil layers, controlling weathering rates via leaching events which intermittently alter the alkalinity levels. In this contribution, we analyze these dynamics using a stochastic modeling approach based on spatially lumped description of soil hydrology and chemical weathering reactions forced by multi-scale temporal hydrologic variability. We quantify the role of soil moisture dynamics in filtering the rainfall fluctuations through its impacts on soil water chemistry, described by a system of ordinary differential equations (and algebraic equations, for the equilibrium reactions), driving the evolution of alkalinity, pH, the chemical species of the soil solution, and the mineral-weathering rate. A probabilistic description of the evolution of the critical zone is thus obtained, allowing us to describe the CZ response to long-term climate fluctuations, ecosystem and land-use conditions, in terms of key variables groups. The model is applied to the weathering rate of albite in the Calhoun CZ observatory and then extended to explore similarities and differences across other CZs. Typical time scales of response and degrees of sensitivities of CZ to hydroclimatic fluctuations and human forcing are also explored.

Hydrological Responses of Weather Conditions and Crop Change of Agricultural Area in the Rincon Valley, New Mexico

NASA Astrophysics Data System (ADS)

Ahn, S.; Sheng, Z.; Abudu, S.

2017-12-01

Hydrologic cycle of agricultural area has been changing due to the impacts of climate and land use changes (crop coverage changes) in an arid region of Rincon Valley, New Mexico. This study is to evaluate the impacts of weather condition and crop coverage change on hydrologic behavior of agricultural area in Rincon Valley (2,466km2) for agricultural watershed management using a watershed-scale hydrologic model, SWAT (Soil and Water Assessment Tool). The SWAT model was developed to incorporate irrigation of different crops using auto irrigation function. For the weather condition and crop coverage change evaluation, three spatial crop coverages including a normal (2008), wet (2009), and dry (2011) years were prepared using USDA crop data layer (CDL) for fourteen different crops. The SWAT model was calibrated for the period of 2001-2003 and validated for the period of 2004-2006 using daily-observed streamflow data. Scenario analysis was performed for wet and dry years based on the unique combinations of crop coverages and releases from Caballo Reservoir. The SWAT model simulated the present vertical water budget and horizontal water transfer considering irrigation practices in the Rincon Valley. Simulation results indicated the temporal and spatial variability for irrigation and non-irrigation seasons of hydrologic cycle in agricultural area in terms of surface runoff, evapotranspiration, infiltration, percolation, baseflow, soil moisture, and groundwater recharge. The water supply of the dry year could not fully cover whole irrigation period due to dry weather conditions, resulting in reduction of crop acreage. For extreme weather conditions, the temporal variation of water budget became robust, which requires careful irrigation management of the agricultural area. The results could provide guidelines for farmers to decide crop patterns in response to different weather conditions and water availability.

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

NASA Astrophysics Data System (ADS)

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

1995-12-01

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

Comparison of pore space textural characteristics of natural stone exposed to real weathering environment and/or subjected to accelerated weathering tests: implications for durability assessment

NASA Astrophysics Data System (ADS)

Prikryl, Richard; Weishauptová, Zuzana

2017-04-01

One of the key questions in the debate on durability of natural stone is related to the relevance of accelerated weathering tests for durability assessments, specifically whether similar material responses can be achieved? In the recent study, specimens of opuka stone (extremely fine-grained clayey-calcareous silicite) was subjected to accelerated weathering tests in a climatic chamber (sulphur dioxide atmosphere, freezing/thawing). After completion of certain number of cycles, pore space textural characteristics by means of mercury porosimetry were studied. These data were compared with porosimetric data obtained from a piece of stone, sampled from a carved stone altar located in the interior of the St. Vitus Cathedral (Prague, Czech Republic) which was affected by 150-years lasting indoor decay processes (cyclic themohygric stresses due to variable indoor atmospheric conditions). Interestingly, the pore space textural characteristics of these two sets of specimens are closely related and show some distinct features different from fresh, non-weathered material. Our observation therefore supports relevance of some accelerated weathering simulations; however, conditions of these simulations must be based on parameters of real environment.

Mitigating Aviation Communication and Satellite Orbit Operations Surprises from Adverse Space Weather

NASA Technical Reports Server (NTRS)

Tobiska, W. Kent

2008-01-01

Adverse space weather affects operational activities in aviation and satellite systems. For example, large solar flares create highly variable enhanced neutral atmosphere and ionosphere electron density regions. These regions impact aviation communication frequencies as well as precision orbit determination. The natural space environment, with its dynamic space weather variability, is additionally changed by human activity. The increase in orbital debris in low Earth orbit (LEO), combined with lower atmosphere CO2 that rises into the lower thermosphere and causes increased cooling that results in increased debris lifetime, adds to the environmental hazards of navigating in near-Earth space. This is at a time when commercial space endeavors are posed to begin more missions to LEO during the rise of the solar activity cycle toward the next maximum (2012). For satellite and aviation operators, adverse space weather results in greater expenses for orbit management, more communication outages or aviation and ground-based high frequency radio used, and an inability to effectively plan missions or service customers with space-based communication, imagery, and data transferal during time-critical activities. Examples of some revenue-impacting conditions and solutions for mitigating adverse space weather are offered.

Four top tier challenges for Space Weather Research for the next decade

NASA Astrophysics Data System (ADS)

Spann, James

2017-04-01

The science of space weather is that which (1) develops the knowledge and understanding to predict conditions in space that impact life and society, and (2) leads to operational solutions that protect assets and systems to the benefit of society. Advances over the past decades in this area of research have yielded amazing discoveries and significant strides toward fulfilling the promise of an operational solution to space weather, and have facilitated the enterprise to make its way into the realm of national and international policy. Even if the resources, technologies, and political will were available to take advantage of this progress, our current lack of understanding of space weather would prevent the implementation of a fully operational system. This talk will highlight four distinct areas of research that, if fully understood, could enable operational solutions to space weather impacts, given sufficient resources and political will. These areas are (a) trigger of solar variability, (b) acceleration of mass and energy in interplanetary space, (c) geoeffectiveness of solar wind, and (d) ionospheric variability. A brief description, technical challenges, and possible pathways to resolution will be offered for each of these areas.

Solar Disinfection of Pseudomonas aeruginosa in Harvested Rainwater: A Step towards Potability of Rainwater

PubMed Central

Amin, Muhammad T.; Nawaz, Mohsin; Amin, Muhammad N.; Han, Mooyoung

2014-01-01

Efficiency of solar based disinfection of Pseudomonas aeruginosa (P. aeruginosa) in rooftop harvested rainwater was evaluated aiming the potability of rainwater. The rainwater samples were exposed to direct sunlight for about 8–9 hours and the effects of water temperature (°C), sunlight irradiance (W/m2), different rear surfaces of polyethylene terephthalate bottles, variable microbial concentrations, pH and turbidity were observed on P. aeruginosa inactivation at different weathers. In simple solar disinfection (SODIS), the complete inactivation of P. aeruginosa was obtained only under sunny weather conditions (>50°C and >700 W/m2) with absorptive rear surface. Solar collector disinfection (SOCODIS) system, used to improve the efficiency of simple SODIS under mild and weak weather, completely inactivated the P. aeruginosa by enhancing the disinfection efficiency of about 20% only at mild weather. Both SODIS and SOCODIS systems, however, were found inefficient at weak weather. Different initial concentrations of P. aeruginosa and/or Escherichia coli had little effects on the disinfection efficiency except for the SODIS with highest initial concentrations. The inactivation of P. aeruginosa increased by about 10–15% by lowering the initial pH values from 10 to 3. A high initial turbidity, adjusted by adding kaolin, adversely affected the efficiency of both systems and a decrease, about 15–25%; in inactivation of P. aeruginosa was observed. The kinetics of this study was investigated by Geeraerd Model for highlighting the best disinfection system based on reaction rate constant. The unique detailed investigation of P. aeruginosa disinfection with sunlight based disinfection systems under different weather conditions and variable parameters will help researchers to understand and further improve the newly invented SOCODIS system. PMID:24595188

Predicting Material Performance in the Space Environment from Laboratory Test Data, Static Design Environments, and Space Weather Models

NASA Technical Reports Server (NTRS)

Minow, Josep I.; Edwards, David L.

2008-01-01

Qualifying materials for use in the space environment is typically accomplished with laboratory exposures to simulated UV/EUV, atomic oxygen, and charged particle radiation environments with in-situ or subsequent measurements of material properties of interest to the particular application. Choice of environment exposure levels are derived from static design environments intended to represent either mean or extreme conditions that are anticipated to be encountered during a mission. The real space environment however is quite variable. Predictions of the on orbit performance of a material qualified to laboratory environments can be done using information on 'space weather' variations in the real environment. This presentation will first review the variability of space environments of concern for material degradation and then demonstrate techniques for using test data to predict material performance in a variety of space environments from low Earth orbit to interplanetary space using historical measurements and space weather models.

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

NASA Astrophysics Data System (ADS)

Ruffault, Julien; Mouillot, Florent; Moebius, Flavia

2013-04-01

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

Reduced Urban Heat Island intensity under warmer conditions

NASA Astrophysics Data System (ADS)

Scott, Anna A.; Waugh, Darryn W.; Zaitchik, Ben F.

2018-06-01

The Urban Heat Island (UHI), the tendency for urban areas to be hotter than rural regions, represents a significant health concern in summer as urban populations are exposed to elevated temperatures. A number of studies suggest that the UHI increases during warmer conditions, however there has been no investigation of this for a large ensemble of cities. Here we compare urban and rural temperatures in 54 US cities for 2000–2015 and show that the intensity of the Urban Heat Island, measured here as the differences in daily-minimum or daily-maximum temperatures between urban and rural stations or ΔT, in fact tends to decrease with increasing temperature in most cities (38/54). This holds when investigating daily variability, heat extremes, and variability across climate zones and is primarily driven by changes in rural areas. We relate this change to large-scale or synoptic weather conditions, and find that the lowest ΔT nights occur during moist weather conditions. We also find that warming cities have not experienced an increasing Urban Heat Island effect.

Bird migration flight altitudes studied by a network of operational weather radars.

PubMed

Dokter, Adriaan M; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan

2011-01-06

A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which--when extended to multiple radars--enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe.

Bird migration flight altitudes studied by a network of operational weather radars

PubMed Central

Dokter, Adriaan M.; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan

2011-01-01

A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which—when extended to multiple radars—enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe. PMID:20519212

Temporal variability of the quality of Taraxacum officinale seed progeny from the East-Ural radioactive trace: is there an interaction between low level radiation and weather conditions?

PubMed

Pozolotina, Vera N; Antonova, Elena V

2017-03-01

The multiple stressors, in different combinations, may impact differently upon seed quality, and low-level doses of radiation may enhance synergistic or antagonistic effects. During 1991-2014 we investigated the quality of the dandelion (Taraxacum officinale s.l.) seed progeny growing under low-level radiation exposure at the East-Ural Radioactive Trace (EURT) area (result of the Kyshtym accident, Russia), and in plants from areas exposed to background radiation. The viability of the dandelion seed progeny was assessed according to chronic radiation exposure, accounting for the variability of weather conditions among years. Environmental factors (temperature, precipitation, and their ratio in different months) can modify the radiobiological effects. We found a wide range of possible responses to multiple stressors: inhibition, stimulation, and indifferent effects in different seasons. The intraspecific variability of the quality of dandelion seed progeny was greatly increased under conditions of low doses of chronic irradiation. Temperature was the most significant factor for seed progeny formation in the EURT zone, whereas the sums of precipitation and ratios of precipitation to temperature dominantly affected organisms from the background population.

Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series

NASA Astrophysics Data System (ADS)

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

2013-04-01

This study extends a stochastic downscaling methodology to generation of an ensemble of hourly time series of meteorological variables that express possible future climate conditions at a point-scale. The stochastic downscaling uses general circulation model (GCM) realizations and an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed for several climate statistics using a Bayesian methodology that can weight GCM realizations based on the model relative performance with respect to a historical climate and a degree of disagreement in projecting future conditions. A Monte Carlo technique is used to sample the factors of change from their respective marginal distributions. As a comparison with traditional approaches, factors of change are also estimated by averaging GCM realizations. With either approach, the derived factors of change are applied to the climate statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series of meteorological variables that can be considered to be representative of future climate conditions. In this study, the time series are generated in an ensemble mode to fully reflect the uncertainty of GCM projections, climate stochasticity, as well as uncertainties of the downscaling procedure. Applications of the methodology in reproducing future climate conditions for the periods of 2000-2009, 2046-2065 and 2081-2100, using the period of 1962-1992 as the historical baseline are discussed for the location of Firenze (Italy). The inferences of the methodology for the period of 2000-2009 are tested against observations to assess reliability of the stochastic downscaling procedure in reproducing statistics of meteorological variables at different time scales.

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

PubMed

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

2008-10-01

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

Climatic conditions preceding historically great fires in the North Central Region.

Treesearch

Donald A. Haines; Rodney W. Sando

1969-01-01

This paper examines the importance of various climatic variables before seven well-known fires of the past. Also, the 1871 synoptic weather pattern preceding the Chicago-Peshtigo-Michigan fire disaster is examined in detail.

WEATHERABILITY OF ENHANCED DEGRADABLE PLASTICS

EPA Science Inventory

The main objective of this study was to assess the performance and the asociated variability of several selected enhanced degradable plastic materials under a variety of different exposure conditions. Other objectives were to identify the major products formed during degradation ...

Examples of variable speed limit applications : speed management workshop

DOT National Transportation Integrated Search

2000-01-09

VSL systems are a type of Intelligent Transportation System (ITS) that utilizes traffic : speed and volume detection, weather information, and road surface condition technology to determine appropriate speeds at which drivers should be traveling, giv...

The El Nino/Southern Oscillation and Future Soybean Prices

NASA Technical Reports Server (NTRS)

Keppenne, C.

1993-01-01

Recently, it was shown that the application of a method combining singular spectrum analysis (SSA) and the maximum entropy method to univariate indicators of the coupled ocean-atmosphere El Nino/Southern Oscillation (ENSO) phenomenon can be helpful in determining whether an El Nino (EN) or La Nina (LN) event will occur. SSA - a variant of principal component analysis applied in the time domain - filters out variability unrelated to ENSO and separates the quasi-biennial (QB), two-to-three year variability, from a lower-frequency (LF) four-to-six year EN-LN cycle; the total variance associated with ENSO combines the QB and LF modes. ENSO has been known to affect weather conditions over much of the globe. For example, EN events have been connected with unusually rainy weather over the Central and Western US, while the opposite phases of the oscillation (LN) have been plausibly associated with extreme dry conditions over much of the same geographical area...

Differences in Meteorological Conditions between Days with Persistent and Non-Persistent Pollution in Beijing, China

NASA Astrophysics Data System (ADS)

You, Ting; Wu, Renguang; Huang, Gang

2018-02-01

We compared the regional synoptic patterns and local meteorological conditions during persistent and non-persistent pollution events in Beijing using US NCEP-Department of Energy reanalysis outputs and observations from meteorological stations. The analysis focused on the impacts of high-frequency (period < 90 days) variations in meteorological conditions on persistent pollution events (those lasting for at least 3 days). Persistent pollution events tended to occur in association with slow-moving weather systems producing stagnant weather conditions, whereas rapidly moving weather systems caused a dramatic change in the local weather conditions so that the pollution event was short-lived. Although Beijing was under the influence of anomalous southerly winds in all four seasons during pollution events, notable differences were identified in the regional patterns of sea-level pressure and local anomalies in relative humidity among persistent pollution events in different seasons. A region of lower pressure was present to the north of Beijing in spring, fall, and winter, whereas regions of lower and higher pressures were observed northwest and southeast of Beijing, respectively, in summer. The relative humidity near Beijing was higher in fall and winter, but lower in spring and summer. These differences may explain the seasonal dependence of the relationship between air pollution and the local meteorological variables. Our analysis showed that the temperature inversion in the lower troposphere played an important part in the occurrence of air pollution under stagnant weather conditions. Some results from this study are based on a limited number of events and thus require validation using more data.

Optimizing Placement of Weather Stations: Exploring Objective Functions of Meaningful Combinations of Multiple Weather Variables

NASA Astrophysics Data System (ADS)

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

2017-12-01

Many regions of the world lack ground-based weather data due to inadequate or unreliable weather station networks. For example, most countries in Sub-Saharan Africa have unreliable, sparse networks of weather stations. The absence of these data can have consequences on weather forecasting, prediction of severe weather events, agricultural planning, and climate change monitoring. The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to place weather stations within each country. We should consider how we can create accurate spatio-temporal maps of weather data and how to balance the desired accuracy of each weather variable of interest (precipitation, temperature, relative humidity, etc.). We can express this problem as a joint optimization of multiple weather variables, given a fixed number of weather stations. We use reanalysis data as the best representation of the "true" weather patterns that occur in the region of interest. For each possible combination of sites, we interpolate the reanalysis data between selected locations and calculate the mean average error between the reanalysis ("true") data and the interpolated data. In order to formulate our multi-variate optimization problem, we explore different methods of weighting each weather variable in our objective function. These methods include systematic variation of weights to determine which weather variables have the strongest influence on the network design, as well as combinations targeted for specific purposes. For example, we can use computed evapotranspiration as a metric that combines many weather variables in a way that is meaningful for agricultural and hydrological applications. We compare the errors of the weather station networks produced by each optimization problem formulation. We also compare these errors to those of manually designed weather station networks in West Africa, planned by the respective host-country's meteorological agency.

National climate assessment technical report on the impacts of climate and land use and land cover change

USGS Publications Warehouse

Loveland, Thomas; Mahmood, Rezaul; Patel-Weynand, Toral; Karstensen, Krista; Beckendorf, Kari; Bliss, Norman; Carleton, Andrew

2012-01-01

This technical report responds to the recognition by the U.S. Global Change Research Program (USGCRP) and the National Climate Assessment (NCA) of the importance of understanding how land use and land cover (LULC) affects weather and climate variability and change and how that variability and change affects LULC. Current published, peer-reviewed, scientific literature and supporting data from both existing and original sources forms the basis for this report's assessment of the current state of knowledge regarding land change and climate interactions. The synthesis presented herein documents how current and future land change may alter environment processes and in turn, how those conditions may affect both land cover and land use by specifically investigating, * The primary contemporary trends in land use and land cover, * The land-use and land-cover sectors and regions which are most affected by weather and climate variability,* How land-use practices are adapting to climate change, * How land-use and land-cover patterns and conditions are affecting weather and climate, and * The key elements of an ongoing Land Resources assessment. These findings present information that can be used to better assess land change and climate interactions in order to better assess land management and adaptation strategies for future environmental change and to assist in the development of a framework for an ongoing national assessment.

Linking crop yield anomalies to large-scale atmospheric circulation in Europe.

PubMed

Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J

2017-06-15

Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.

What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods

PubMed Central

Zhang, Kai; Li, Yun; Schwartz, Joel D.; O'Neill, Marie S.

2014-01-01

Hot weather increases risk of mortality. Previous studies used different sets of weather variables to characterize heat stress, resulting in variation in heat-mortality- associations depending on the metric used. We employed a statistical learning method – random forests – to examine which of various weather variables had the greatest impact on heat-related mortality. We compiled a summertime daily weather and mortality counts dataset from four U.S. cities (Chicago, IL; Detroit, MI; Philadelphia, PA; and Phoenix, AZ) from 1998 to 2006. A variety of weather variables were ranked in predicting deviation from typical daily all-cause and cause-specific death counts. Ranks of weather variables varied with city and health outcome. Apparent temperature appeared to be the most important predictor of heat-related mortality for all-cause mortality. Absolute humidity was, on average, most frequently selected one of the top variables for all-cause mortality and seven cause-specific mortality categories. Our analysis affirms that apparent temperature is a reasonable variable for activating heat alerts and warnings, which are commonly based on predictions of total mortality in next few days. Additionally, absolute humidity should be included in future heat-health studies. Finally, random forests can be used to guide choice of weather variables in heat epidemiology studies. PMID:24834832

Description of atmospheric conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS)

NASA Astrophysics Data System (ADS)

Pierre Auger Collaboration; Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allard, D.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antiči'C, T.; Aramo, C.; Arganda, E.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Bäcker, T.; Badescu, A. M.; Balzer, M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Barroso, S. L. C.; Baughman, B.; Bäuml, J.; Beatty, J. J.; Becker, B. R.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; Benzvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Bruijn, R.; Buchholz, P.; Bueno, A.; Burton, R. E.; Caballero-Mora, K. S.; Caccianiga, B.; Caramete, L.; Caruso, R.; Castellina, A.; Catalano, O.; Cataldi, G.; Cazon, L.; Cester, R.; Chauvin, J.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos Diaz, J.; Chudoba, J.; Clay, R. W.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coppens, J.; Cordier, A.; Coutu, S.; Covault, C. E.; Creusot, A.; Criss, A.; Cronin, J.; Curutiu, A.; Dagoret-Campagne, S.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; de Domenico, M.; de Donato, C.; de Jong, S. J.; de La Vega, G.; de Mello Junior, W. J. M.; de Mello Neto, J. R. T.; de Mitri, I.; de Souza, V.; de Vries, K. D.; Del Peral, L.; Del Río, M.; Deligny, O.; Dembinski, H.; Dhital, N.; di Giulio, C.; Díaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; Dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Dutan, I.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Fajardo Tapia, I.; Falcke, H.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Gascon, A.; Gemmeke, H.; Ghia, P. L.; Giaccari, U.; Giller, M.; Glass, H.; Gold, M. S.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gómez Vitale, P. F.; Gonçalves, P.; Gonzalez, D.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gouffon, P.; Grashorn, E.; Grebe, S.; Griffith, N.; Grigat, M.; Grillo, A. F.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Guzman, A.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horneffer, A.; Horvath, P.; Hrabovský, M.; Huber, D.; Huege, T.; Insolia, A.; Ionita, F.; Italiano, A.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Koang, D.-H.; Kotera, K.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuehn, F.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; Lachaud, C.; Lahurd, D.; Latronico, L.; Lauer, R.; Lautridou, P.; Le Coz, S.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Maldera, S.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Maris, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Mertsch, P.; Meurer, C.; Mi'Canovi'C, S.; Micheletti, M. I.; Minaya, I. A.; Miramonti, L.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, E.; Moreno, J. C.; Mostafá, M.; Moura, C. A.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Nitz, D.; Nosek, D.; Nožka, L.; Oehlschläger, J.; Olinto, A.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parizot, E.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Pȩkala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrinca, P.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodriguez-Cabo, I.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-D'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Saftoiu, A.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sarkar, S.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F.; Schulte, S.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Silva Lopez, H. H.; Sima, O.; 'Smiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanic, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Taşcău, O.; Tavera Ruiz, C. G.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Travnicek, P.; Tridapalli, D. B.; Tristram, G.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van den Berg, A. M.; Varela, E.; Vargascárdenas, B.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Wommer, M.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.

2012-04-01

Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargüe and averaged monthly models, the utility of the GDAS data is shown.

Description of Atmospheric Conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS)

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

Abreu, P.; /Lisbon, IST; Aglietta, M.

2012-01-01

Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargue and averaged monthly models, the utility of the GDAS data is shown.

Multiscale climate emulator of multimodal wave spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, Ana; Hegermiller, Christie A.; Antolinez, Jose A. A.; Camus, Paula; Vitousek, Sean; Ruggiero, Peter; Barnard, Patrick L.; Erikson, Li H.; Tomás, Antonio; Mendez, Fernando J.

2017-02-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this complex problem tractable using computationally expensive numerical models. So far, the skill of statistical-downscaling model-based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Multiscale Climate Emulator of Multimodal Wave Spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, A.; Hegermiller, C.; Alvarez Antolinez, J. A.; Camus, P.; Vitousek, S.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Tomas, A.; Mendez, F. J.

2016-12-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this problem complex yet tractable using computationally-expensive numerical models. So far, the skill of statistical-downscaling models based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical-downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the Southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

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

PubMed

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.

Current denudation rates in dolostone karst from central Spain: Implications for the formation of unroofed caves

NASA Astrophysics Data System (ADS)

Krklec, Kristina; Domínguez-Villar, David; Carrasco, Rosa M.; Pedraza, Javier

2016-07-01

Rock tablets of known weight were buried in the soil of a karst region in Central Spain to evaluate the carbonate weathering during a period of a year. The experiment was conducted at two different soil depths: 5-10 and 50-55 cm from the surface. The parental rock used in the experiment is composed of dolomite and magnesite with variable proportion of accessory minerals and minor elements. Soil mineral and chemical composition as well as its texture was also characterized. Meteorological conditions at the site together with temperature and CO2 in both soil levels were monitored. Sets of tablets were retrieved after 6 and 12 months of the start of the experiment to account for seasonal weathering. Different lithologies do not exhibit significant differences in weathering, although a large inter-sample variability is attributed to variable size and distribution of the porosity. Results show an enhanced weathering during the wet and cold season that accounts for 78 ± 1% of the total annual weathering. Rock tablets examined under scanning electron microscopy prior and after exposure to natural environment show that most of the material lost occurred along cracks, edges or large pores. Although dissolution is a common process, most of the weathering is due to crystal detachment. Rock tablets at the depth of 5-10 cm were weathered 68 ± 1% more than those set at 50-55 cm from the surface. Higher soil moisture and concentration of CO2 were found deeper in the soil, which likely enhanced the dissolution of carbonate. However, physical weathering dominated weight loss of rock tablets at both soil depths; especially at the 5-10 cm level where soil thermal and moisture cycles were more frequent and greater. Denudation rate calculated from the 12 months set provides values of 2.48 ± 1.07 μm/yr and 1.75 ± 0.66 μm/yr at the depths of 5-10 and 50-55 cm, respectively. Since the conditions at the average contact between soil and bedrock are similar to those at the 50-55 cm depth, we consider that this is a more reliable denudation rate for the studied location during the studied period. The calculated weathering rate suggests that denudation has a limited contribution to the thinning of bedrock over caves at this site. Therefore, we consider that the formation of unroofed caves in this region most likely results from the thinning of bedrock cover over caves due to collapse of blocks from their ceilings.

A probabilistic approach to modeling erosion for spatially-varied conditions

Treesearch

William J. Elliot; Peter R. Robichaud; C. D. Pannkuk

2001-01-01

In the years following a major forest disturbance, such as fire, the erosion rate is greatly influenced by variability in weather, in soil properties, and in spatial distribution. This paper presents a method to incorporate these variabilities into the erosion rate predicted by the Water Erosion Prediction Project model. It appears that it is not necessary to describe...

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

NASA Astrophysics Data System (ADS)

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

2013-01-01

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

Sensitivity of barley varieties to weather in Finland.

PubMed

Hakala, K; Jauhiainen, L; Himanen, S J; Rötter, R; Salo, T; Kahiluoto, H

2012-04-01

Global climate change is predicted to shift seasonal temperature and precipitation patterns. An increasing frequency of extreme weather events such as heat waves and prolonged droughts is predicted, but there are high levels of uncertainty about the nature of local changes. Crop adaptation will be important in reducing potential damage to agriculture. Crop diversity may enhance resilience to climate variability and changes that are difficult to predict. Therefore, there has to be sufficient diversity within the set of available cultivars in response to weather parameters critical for yield formation. To determine the scale of such 'weather response diversity' within barley (Hordeum vulgare L.), an important crop in northern conditions, the yield responses of a wide range of modern and historical varieties were analysed according to a well-defined set of critical agro-meteorological variables. The Finnish long-term dataset of MTT Official Variety Trials was used together with historical weather records of the Finnish Meteorological Institute. The foci of the analysis were firstly to describe the general response of barley to different weather conditions and secondly to reveal the diversity among varieties in the sensitivity to each weather variable. It was established that barley yields were frequently reduced by drought or excessive rain early in the season, by high temperatures at around heading, and by accelerated temperature sum accumulation rates during periods 2 weeks before heading and between heading and yellow ripeness. Low temperatures early in the season increased yields, but frost during the first 4 weeks after sowing had no effect. After canopy establishment, higher precipitation on average resulted in higher yields. In a cultivar-specific analysis, it was found that there were differences in responses to all but three of the studied climatic variables: waterlogging and drought early in the season and temperature sum accumulation rate before heading. The results suggest that low temperatures early in the season, delayed sowing, rain 3-7 weeks after sowing, a temperature change 3-4 weeks after sowing, a high temperature sum accumulation rate from heading to yellow ripeness and high temperatures (⩾25°C) at around heading could mostly be addressed by exploiting the traits found in the range of varieties included in the present study. However, new technology and novel genetic material are needed to enable crops to withstand periods of excessive rain or drought early in the season and to enhance performance under increased temperature sum accumulation rates prior to heading.

Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe

NASA Astrophysics Data System (ADS)

Vautard, Robert; Christidis, Nikolaos; Ciavarella, Andrew; Alvarez-Castro, Carmen; Bellprat, Omar; Christiansen, Bo; Colfescu, Ioana; Cowan, Tim; Doblas-Reyes, Francisco; Eden, Jonathan; Hauser, Mathias; Hegerl, Gabriele; Hempelmann, Nils; Klehmet, Katharina; Lott, Fraser; Nangini, Cathy; Orth, René; Radanovics, Sabine; Seneviratne, Sonia I.; van Oldenborgh, Geert Jan; Stott, Peter; Tett, Simon; Wilcox, Laura; Yiou, Pascal

2018-04-01

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed sea surface temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North-Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution.

Reduced CO2 fertilization effect in temperate C3 grasslands under more extreme weather conditions

NASA Astrophysics Data System (ADS)

Obermeier, W. A.; Lehnert, L. W.; Kammann, C. I.; Müller, C.; Grünhage, L.; Luterbacher, J.; Erbs, M.; Moser, G.; Seibert, R.; Yuan, N.; Bendix, J.

2017-02-01

The increase in atmospheric greenhouse gas concentrations from anthropogenic activities is the major driver of recent global climate change. The stimulation of plant photosynthesis due to rising atmospheric carbon dioxide concentrations ([CO2]) is widely assumed to increase the net primary productivity (NPP) of C3 plants--the CO2 fertilization effect (CFE). However, the magnitude and persistence of the CFE under future climates, including more frequent weather extremes, are controversial. Here we use data from 16 years of temperate grassland grown under `free-air carbon dioxide enrichment’ conditions to show that the CFE on above-ground biomass is strongest under local average environmental conditions. The observed CFE was reduced or disappeared under wetter, drier and/or hotter conditions when the forcing variable exceeded its intermediate regime. This is in contrast to predictions of an increased CO2 fertilization effect under drier and warmer conditions. Such extreme weather conditions are projected to occur more intensely and frequently under future climate scenarios. Consequently, current biogeochemical models might overestimate the future NPP sink capacity of temperate C3 grasslands and hence underestimate future atmospheric [CO2] increase.

Plausible Effect of Weather on Atlantic Meridional Overturning Circulation with a Coupled General Circulation Model

NASA Astrophysics Data System (ADS)

Liu, Zedong; Wan, Xiuquan

2018-04-01

The Atlantic meridional overturning circulation (AMOC) is a vital component of the global ocean circulation and the heat engine of the climate system. Through the use of a coupled general circulation model, this study examines the role of synoptic systems on the AMOC and presents evidence that internally generated high-frequency, synoptic-scale weather variability in the atmosphere could play a significant role in maintaining the overall strength and variability of the AMOC, thereby affecting climate variability and change. Results of a novel coupling technique show that the strength and variability of the AMOC are greatly reduced once the synoptic weather variability is suppressed in the coupled model. The strength and variability of the AMOC are closely linked to deep convection events at high latitudes, which could be strongly affected by the weather variability. Our results imply that synoptic weather systems are important in driving the AMOC and its variability. Thus, interactions between atmospheric weather variability and AMOC may be an important feedback mechanism of the global climate system and need to be taken into consideration in future climate change studies.

Local weather is associated with rates of online searches for musculoskeletal pain symptoms.

PubMed

Telfer, Scott; Obradovich, Nick

2017-01-01

Weather conditions are commonly believed to influence musculoskeletal pain, however the evidence for this is mixed. This study aimed to examine the relationship between local meteorological conditions and online search trends for terms related to knee pain, hip pain, and arthritis. Five years of relative online search volumes for these terms were obtained for the 50 most populous cities in the contiguous United States, along with corresponding local weather data for temperature, relative humidity, barometric pressure, and precipitation. Methods from the climate econometrics literature were used to assess the casual impact of these meteorological variables on the relative volumes of searches for pain. For temperatures between -5°C and 30°C, search volumes for hip pain increased by 12 index points, and knee pain increased by 18 index points. Precipitation had a negative effect on search volumes for these terms. At temperatures >30°C, search volumes for arthritis related pain decreased by 7 index points. These patterns were not seen for pain searches unrelated to the musculoskeletal system. In summary, selected local weather conditions are significantly associated with online search volumes for specific musculoskeletal pain symptoms. We believe the predominate driver for this to be the relative changes in physical activity levels associated with meteorological conditions.

The Mauna Kea Weather Center: Custom Atmospheric Forecasting Support for Mauna Kea

NASA Astrophysics Data System (ADS)

Businger, Steven

2011-03-01

The success of operations at Mauna Kea Observatories is strongly influenced by weather conditions. The Mauna Kea Weather Center, an interdisciplinary research program, was established in 1999 to develop and provide custom weather support for Mauna Kea Observatories. The operational forecasting goals of the program are to facilitate the best possible use of favorable atmospheric conditions for scientific benefit and to ensure operational safety. During persistent clear periods, astronomical observing quality varies substantially due to changes in the vertical profiles of temperature, wind, moisture, and turbulence. Cloud and storm systems occasionally cause adverse or even hazardous conditions. A dedicated, daily, real-time mesoscale numerical modeling effort provides crucial forecast guidance in both cases. Several key atmospheric variables are forecast with sufficient skill to be of operational and scientific benefit to the telescopes on Mauna Kea. Summit temperature forecasts allow mirrors to be set to the ambient temperature to reduce image distortion. Precipitable water forecasts allow infrared observations to be prioritized according to atmospheric opacity. Forecasts of adverse and hazardous conditions protect the safety of personnel and allow for scheduling of maintenance when observing is impaired by cloud. The research component of the project continues to improve the accuracy and content of the forecasts. In particular, case studies have resulted in operational forecasts of astronomical observing quality, or seeing.

Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models

PubMed Central

Chen, Feng; Chen, Suren; Ma, Xiaoxiang

2016-01-01

Traffic and environmental conditions (e.g., weather conditions), which frequently change with time, have a significant impact on crash occurrence. Traditional crash frequency models with large temporal scales and aggregated variables are not sufficient to capture the time-varying nature of driving environmental factors, causing significant loss of critical information on crash frequency modeling. This paper aims at developing crash frequency models with refined temporal scales for complex driving environments, with such an effort providing more detailed and accurate crash risk information which can allow for more effective and proactive traffic management and law enforcement intervention. Zero-inflated, negative binomial (ZINB) models with site-specific random effects are developed with unbalanced panel data to analyze hourly crash frequency on highway segments. The real-time driving environment information, including traffic, weather and road surface condition data, sourced primarily from the Road Weather Information System, is incorporated into the models along with site-specific road characteristics. The estimation results of unbalanced panel data ZINB models suggest there are a number of factors influencing crash frequency, including time-varying factors (e.g., visibility and hourly traffic volume) and site-varying factors (e.g., speed limit). The study confirms the unique significance of the real-time weather, road surface condition and traffic data to crash frequency modeling. PMID:27322306

Weather impacts on single-vehicle truck crash injury severity.

PubMed

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

2016-09-01

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

Uncertainty analysis of accident notification time and emergency medical service response time in work zone traffic accidents.

PubMed

Meng, Qiang; Weng, Jinxian

2013-01-01

Taking into account the uncertainty caused by exogenous factors, the accident notification time (ANT) and emergency medical service (EMS) response time were modeled as 2 random variables following the lognormal distribution. Their mean values and standard deviations were respectively formulated as the functions of environmental variables including crash time, road type, weekend, holiday, light condition, weather, and work zone type. Work zone traffic accident data from the Fatality Analysis Report System between 2002 and 2009 were utilized to determine the distributions of the ANT and the EMS arrival time in the United States. A mixed logistic regression model, taking into account the uncertainty associated with the ANT and the EMS response time, was developed to estimate the risk of death. The results showed that the uncertainty of the ANT was primarily influenced by crash time and road type, whereas the uncertainty of EMS response time is greatly affected by road type, weather, and light conditions. In addition, work zone accidents occurring during a holiday and in poor light conditions were found to be statistically associated with a longer mean ANT and longer EMS response time. The results also show that shortening the ANT was a more effective approach in reducing the risk of death than the EMS response time in work zones. To shorten the ANT and the EMS response time, work zone activities are suggested to be undertaken during non-holidays, during the daytime, and in good weather and light conditions.

From AWE-GEN to AWE-GEN-2d: a high spatial and temporal resolution weather generator

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2016-04-01

A new weather generator, AWE-GEN-2d (Advanced WEather GENerator for 2-Dimension grid) is developed following the philosophy of combining physical and stochastic approaches to simulate meteorological variables at high spatial and temporal resolution (e.g. 2 km x 2 km and 5 min for precipitation and cloud cover and 100 m x 100 m and 1 h for other variables variable (temperature, solar radiation, vapor pressure, atmospheric pressure and near-surface wind). The model is suitable to investigate the impacts of climate variability, temporal and spatial resolutions of forcing on hydrological, ecological, agricultural and geomorphological impacts studies. Using appropriate parameterization the model can be used in the context of climate change. Here we present the model technical structure of AWE-GEN-2d, which is a substantial evolution of four preceding models (i) the hourly-point scale Advanced WEather GENerator (AWE-GEN) presented by Fatichi et al. (2011, Adv. Water Resour.) (ii) the Space-Time Realizations of Areal Precipitation (STREAP) model introduced by Paschalis et al. (2013, Water Resour. Res.), (iii) the High-Resolution Synoptically conditioned Weather Generator developed by Peleg and Morin (2014, Water Resour. Res.), and (iv) the Wind-field Interpolation by Non Divergent Schemes presented by Burlando et al. (2007, Boundary-Layer Meteorol.). The AWE-GEN-2d is relatively parsimonious in terms of computational demand and allows generating many stochastic realizations of current and projected climates in an efficient way. An example of model application and testing is presented with reference to a case study in the Wallis region, a complex orography terrain in the Swiss Alps.

An AEM-TEM study of weathering and diagenesis, Abert Lake, Oregon. (1) Weathering reactions in the volcanics

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

Banfield, J.F.; Veblen, D.R.; Jones, B.F.

1991-10-01

Abert Lake in south-central Oregon provides a site suitable for the study of sequential weathering and diagenetic events. In this first of two papers, transmission electron microscopy was used to characterize the igneous mineralogy, subsolidus alteration assemblage, and the structural and chemical aspects of silicate weathering reactions that occur in the volcanic rocks that outcrop around the lake. Olivine and pyroxene replacement occurred topotactically, whereas feldspar and glass alteration produced randomly oriented smectite in channels and cavities. The tetrahedral, octahedral, and interlayer compositions of the weathering products, largely dioctahedral smectites, varied with primary mineral composition, rock type, and as themore » result of addition of elements released from adjacent reaction sites. The variability within and between the smectite assemblages highlights the microenvironmental diversity, fluctuating redox conditions, and variable solution chemistry associated with mineral weathering reactions in the surficial environment. Late-stage exhalative and aqueous alteration of the volcanics redistributed many components and formed a variety of alkali and alkali-earth carbonate, chloride, sulfate, and fluoride minerals in vugs and cracks. Overall, substantial Mg, Si, Na, Ca, and K are released by weathering reactions that include the almost complete destruction of the Mg-smectite that initially replaced olivine. The leaching of these elements from the volcanics provides an important source of these constituents in the lake water. The nature of subsequent diagenetic reactions resulting from the interaction between the materials transported to the lake and the solution will be described in part.« less

A geochemical record of the link between chemical weathering and the East Asian summer monsoon during the late Holocene preserved in lacustrine sediments from Poyang Lake, central China

NASA Astrophysics Data System (ADS)

Huang, Chao; Wei, Gangjian; Li, Wuxian; Liu, Ying

2018-04-01

This paper presents relatively high-resolution geochemical records spanning the past 4000 cal yr BP obtained from the lacustrine sediments of Poyang Lake in central China. The variations in the intensity of the East Asian summer monsoon (EASM) are traced using the K/Na, Ti/Na, Al/K, kaolinite/illite and clay/feldspar ratios, together with the chemical index of alteration (CIA), as indicators of chemical weathering. During the last 4000 years, the proxy records of chemical weathering from Poyang Lake exhibit an overall enhanced trend, consistent with regional hydrological changes in previous independent records. Further comparisons and analyses demonstrate that regional moisture variations in central China is inversely correlated with the EASM intensity, with weak EASM generating high precipitation in central China. Our data reveal three intervals of dramatically dry climatic conditions (i.e., ca. 4000-3200 cal yr BP, ca. 2800-2400 cal yr BP, and ca. 500-200 cal yr BP). A period of weak chemical weathering, related to cold and dry climatic conditions, occurred during the Little Ice Age (LIA), whereas more intense chemical weathering, reflecting warm and humid climatic conditions, was recorded during the Medieval Warm Period (MWP). Besides, an intensification of chemical weathering in Poyang Lake during the late Holocene agrees well with strong ENSO activity, suggesting that moisture variations in central China may be predominantly driven by ENSO variability.

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

Lopez, Anthony

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

Impact of transient climate change upon Grouse population dynamics in the Italian Alps

NASA Astrophysics Data System (ADS)

Pirovano, Andrea; Bocchiola, Daniele

2010-05-01

Understanding the effect of short to medium term weather condition, and of transient global warming upon wildlife species life history is essential to predict the demographic consequences therein, and possibly develop adaptation strategies, especially in game species, where hunting mortality may play an important role in population dynamics. We carried out a preliminary investigation of observed impact of weather variables upon population dynamics indexes of three alpine Grouse species (i.e. Rock Ptarmigan, Lagopus Mutus, Black Grouse, Tetrao Tetrix, Rock Partridge, Alectoris Graeca), nested within central Italian Alps, based upon 15 years (1995-2009) of available censuses data, provided by the Sondrio Province authority. We used a set of climate variables already highlighted within recent literature for carrying considerable bearing on Grouse population dynamics, including e.g. temperature at hatching time and during winter, snow cover at nesting, and precipitation during nursing period. We then developed models of Grouses' population dynamics by explicitly driving population change according to their dependence upon the significant weather variables and population density and we evaluated objective indexes to assess the so obtained predictive power. Eventually, we develop projection of future local climate, based upon locally derived trends, and upon projections from GCMs (A2 IPCC storyline) already validated for the area, to project forward in time (until 2100 or so) the significant climatic variables, which we then use to force population dynamics models of the target species. The projected patterns obtained through this exercise are discussed and compared against those expected under stationary climate conditions at present, and preliminary conclusions are drawn.

Weather-centric rangeland revegetation planning

USGS Publications Warehouse

Hardegree, Stuart P.; Abatzoglou, John T.; Brunson, Mark W.; Germino, Matthew; Hegewisch, Katherine C.; Moffet, Corey A.; Pilliod, David S.; Roundy, Bruce A.; Boehm, Alex R.; Meredith, Gwendwr R.

2018-01-01

Invasive annual weeds negatively impact ecosystem services and pose a major conservation threat on semiarid rangelands throughout the western United States. Rehabilitation of these rangelands is challenging due to interannual climate and subseasonal weather variability that impacts seed germination, seedling survival and establishment, annual weed dynamics, wildfire frequency, and soil stability. Rehabilitation and restoration outcomes could be improved by adopting a weather-centric approach that uses the full spectrum of available site-specific weather information from historical observations, seasonal climate forecasts, and climate-change projections. Climate data can be used retrospectively to interpret success or failure of past seedings by describing seasonal and longer-term patterns of environmental variability subsequent to planting. A more detailed evaluation of weather impacts on site conditions may yield more flexible adaptive-management strategies for rangeland restoration and rehabilitation, as well as provide estimates of transition probabilities between desirable and undesirable vegetation states. Skillful seasonal climate forecasts could greatly improve the cost efficiency of management treatments by limiting revegetation activities to time periods where forecasts suggest higher probabilities of successful seedling establishment. Climate-change projections are key to the application of current environmental models for development of mitigation and adaptation strategies and for management practices that require a multidecadal planning horizon. Adoption of new weather technology will require collaboration between land managers and revegetation specialists and modifications to the way we currently plan and conduct rangeland rehabilitation and restoration in the Intermountain West.

A Physically Based Coupled Chemical and Physical Weathering Model for Simulating Soilscape Evolution

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Welivitiya, D.; Hancock, G. R.

2015-12-01

A critical missing link in existing landscape evolution models is a dynamic soil evolution models where soils co-evolve with the landform. Work by the authors over the last decade has demonstrated a computationally manageable model for soil profile evolution (soilscape evolution) based on physical weathering. For chemical weathering it is clear that full geochemistry models such as CrunchFlow and PHREEQC are too computationally intensive to be couplable to existing soilscape and landscape evolution models. This paper presents a simplification of CrunchFlow chemistry and physics that makes the task feasible, and generalises it for hillslope geomorphology applications. Results from this simplified model will be compared with field data for soil pedogenesis. Other researchers have previously proposed a number of very simple weathering functions (e.g. exponential, humped, reverse exponential) as conceptual models of the in-profile weathering process. The paper will show that all of these functions are possible for specific combinations of in-soil environmental, geochemical and geologic conditions, and the presentation will outline the key variables controlling which of these conceptual models can be realistic models of in-profile processes and under what conditions. The presentation will finish by discussing the coupling of this model with a physical weathering model, and will show sample results from our SSSPAM soilscape evolution model to illustrate the implications of including chemical weathering in the soilscape evolution model.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Collaborative adaptive landscape management (CALM) in rangelands: Discussion of general principles

USDA-ARS?s Scientific Manuscript database

The management of rangeland landscapes involves broad spatial extents, mixed land ownership, and multiple resource objectives. Management outcomes depend on biophysical heterogeneity, highly variable weather conditions, land use legacies, and spatial processes such as wildlife movement, hydrological...

Chapter 5: Quality assurance/quality control in stormwater sampling

USDA-ARS?s Scientific Manuscript database

Sampling the quality of stormwater presents unique challenges because stormwater flow is relatively short-lived with drastic variability. Furthermore, storm events often occur with little advance warning, outside conventional work hours, and under adverse weather conditions. Therefore, most stormwat...

Fire activity as a function of fire–weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA

USGS Publications Warehouse

Urbieta, Itziar R.; Zavala, Gonzalo; Bedia, Joaquin; Gutierrez, Jose M.; San Miguel-Ayanz, Jesus; Camia, Andrea; Keeley, Jon E.; Moreno, Jose M.

2015-01-01

Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire–weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.

Fire activity as a function of fire-weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA

NASA Astrophysics Data System (ADS)

Urbieta, Itziar R.; Zavala, Gonzalo; Bedia, Joaquín; Gutiérrez, José M.; San Miguel-Ayanz, Jesús; Camia, Andrea; Keeley, Jon E.; Moreno, José M.

2015-11-01

Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire-weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.

Influence of long-term chronic exposure and weather conditions on Scots pine populations.

PubMed

Geras'kin, Stanislav; Vasiliyev, Denis; Makarenko, Ekaterina; Volkova, Polina; Kuzmenkov, Alexey

2017-04-01

Over a period of 8 years (2007-2014), we were evaluating seed quality and morphological abnormalities in Scots pine trees affected as a result of the Chernobyl accident. The calculated dose rates for the trees at the study sites varied from background values at the reference sites to 40 mGy/year at the most contaminated site. We investigated whether radioactive contamination and/or weather factors could decrease the reproductive capacity or increase the frequency of morphological abnormalities of needles in pine trees. Scots pine seeds are characterized by high interannual variability of viability, which is largely determined by weather conditions. No consistent differences in reproductive capacity were detected between the impacted and reference populations. Brachyblasts with three needles were found only in the affected populations; however, their frequency was very low and only at the very border of significance at the p < 0.10 level.

Variations in thematic mapper spectra of soil related to tillage and crop residue management - Initial evaluation

NASA Technical Reports Server (NTRS)

Seeley, M. W.; Ruschy, D. L.; Linden, D. R.

1983-01-01

A cooperative research project was initiated in 1982 to study differences in thematic mapper spectral characteristics caused by variable tillage and crop residue practices. Initial evaluations of radiometric data suggest that spectral separability of variably tilled soils can be confounded by moisture and weathering effects. Separability of bare tilled soils from those with significant amounts of corn residue is enhanced by wet conditions, but still possible under dry conditions when recent tillage operations have occurred. In addition, thematic mapper data may provide an alternative method to study the radiant energy balance at the soil surface in conjunction with variable tillage systems.

MATISSE: a meteorological aviation supporting system developed in a GIS environment

NASA Astrophysics Data System (ADS)

Rillo, Valeria; Mercogliano, Paola

2014-05-01

Awareness of weather conditions plays an increasing role in different societal and economic sectors, in particular the aviation one which is very sensitive to the meteorological conditions. In fact, adverse meteorological conditions are among the most important causes of accidents causing human and economic losses. For these reasons it is crucial to monitor and nowcast such events and avoid risks during all the flight phases. In this framework CIRA (Italian Aerospace Research Center) has implemented MATISSE (Meteorological AviaTIon Supporting SystEm), an ArcGIS Desktop Plug in, in order to detect and forecast meteorological aviation hazards over the main European airports, by using different sources of meteorological data (synoptic information, satellite data, numerical weather prediction models outputs). Such functionalities are realized after a preprocessing of raw data achieving more complex information, useful for the detection and the forecast of aviation hazards. After that, the data are stored in a database used by ArcGIS and further processed in order to provide maps, graphs and statistics. MATISSE presents a dockable toolbar in a GIS environment, allowing the user to easily select and visualize the desired information. In particular, the user can access to real time functionalities and visualize, on a map, the chosen meteorological hazard or variable (such as visibility conditions, cumulonimbi, wind speeds and directions, present weather, pressure, relative humidity, past weather, cloud cover, height of base of clouds, cloud type, geopotential, altimeter settings, three hour pressure change) over an airport or an area of interest (Europe, Italy). Such variables are represented in a user friendly way, by using simple icons easy to understand and reporting the risk level for aviation in order to provide pilots information about the meteorological conditions during the flight and the following hours. MATISSE, in fact, is able to handle the output of COSMO LM model (NetCDF files) and visualize such information. Moreover it is interfaced to an innovative tool based on MSG-2 satellite data, able to forecast the evolution of cumulonimbi, clouds responsible of thunderstorms, wind shear, icing and turbulence phenomena. MATISSE includes also tool for the statistical characterization of the typical weather bad conditions on the airport of interest, for example percentage of fog events on particular time windows.

Flight responses by a migratory soaring raptor to changing meteorological conditions.

PubMed

Lanzone, Michael J; Miller, Tricia A; Turk, Philip; Brandes, David; Halverson, Casey; Maisonneuve, Charles; Tremblay, Junior; Cooper, Jeff; O'Malley, Kieran; Brooks, Robert P; Katzner, Todd

2012-10-23

Soaring birds that undertake long-distance migration should develop strategies to minimize the energetic costs of endurance flight. This is relevant because condition upon completion of migration has direct consequences for fecundity, fitness and thus, demography. Therefore, strong evolutionary pressures are expected for energy minimization tactics linked to weather and topography. Importantly, the minute-by-minute mechanisms birds use to subsidize migration in variable weather are largely unknown, in large part because of the technological limitations in studying detailed long-distance bird flight. Here, we show golden eagle (Aquila chrysaetos) migratory response to changing meteorological conditions as monitored by high-resolution telemetry. In contrast to expectations, responses to meteorological variability were stereotyped across the 10 individuals studied. Eagles reacted to increased wind speed by using more orographic lift and less thermal lift. Concomitantly, as use of thermals decreased, variation in flight speed and altitude also decreased. These results demonstrate how soaring migrant birds can minimize energetic expenditures, they show the context for avian decisions and choices of specific instantaneous flight mechanisms and they have important implications for design of bird-friendly wind energy.

Influence of olfactory and visual cover on nest site selection and nest success for grassland-nesting birds.

PubMed

Fogarty, Dillon T; Elmore, R Dwayne; Fuhlendorf, Samuel D; Loss, Scott R

2017-08-01

Habitat selection by animals is influenced by and mitigates the effects of predation and environmental extremes. For birds, nest site selection is crucial to offspring production because nests are exposed to extreme weather and predation pressure. Predators that forage using olfaction often dominate nest predator communities; therefore, factors that influence olfactory detection (e.g., airflow and weather variables, including turbulence and moisture) should influence nest site selection and survival. However, few studies have assessed the importance of olfactory cover for habitat selection and survival. We assessed whether ground-nesting birds select nest sites based on visual and/or olfactory cover. Additionally, we assessed the importance of visual cover and airflow and weather variables associated with olfactory cover in influencing nest survival. In managed grasslands in Oklahoma, USA, we monitored nests of Northern Bobwhite ( Colinus virginianus ), Eastern Meadowlark ( Sturnella magna ), and Grasshopper Sparrow ( Ammodramus savannarum ) during 2015 and 2016. To assess nest site selection, we compared cover variables between nests and random points. To assess factors influencing nest survival, we used visual cover and olfactory-related measurements (i.e., airflow and weather variables) to model daily nest survival. For nest site selection, nest sites had greater overhead visual cover than random points, but no other significant differences were found. Weather variables hypothesized to influence olfactory detection, specifically precipitation and relative humidity, were the best predictors of and were positively related to daily nest survival. Selection for overhead cover likely contributed to mitigation of thermal extremes and possibly reduced detectability of nests. For daily nest survival, we hypothesize that major nest predators focused on prey other than the monitored species' nests during high moisture conditions, thus increasing nest survival on these days. Our study highlights how mechanistic approaches to studying cover informs which dimensions are perceived and selected by animals and which dimensions confer fitness-related benefits.

Improving the freight transportation roadway system during snow events : a performance evaluation of deicing chemicals.

DOT National Transportation Integrated Search

2012-05-01

The ability of state DOTs to adequately clear roadways during winter weather conditions is critical for a safe and effective : freight transportation system. Variables affecting winter maintenance operations include the type of precipitation, air and...

Simulation of crop yield variability by improved root-soil-interaction modelling

NASA Astrophysics Data System (ADS)

Duan, X.; Gayler, S.; Priesack, E.

2009-04-01

Understanding the processes and factors that govern the within-field variability in crop yield has attached great importance due to applications in precision agriculture. Crop response to environment at field scale is a complex dynamic process involving the interactions of soil characteristics, weather conditions and crop management. The numerous static factors combined with temporal variations make it very difficult to identify and manage the variability pattern. Therefore, crop simulation models are considered to be useful tools in analyzing separately the effects of change in soil or weather conditions on the spatial variability, in order to identify the cause of yield variability and to quantify the spatial and temporal variation. However, tests showed that usual crop models such as CERES-Wheat and CERES-Maize were not able to quantify the observed within-field yield variability, while their performance on crop growth simulation under more homogeneous and mainly non-limiting conditions was sufficent to simulate average yields at the field-scale. On a study site in South Germany, within-field variability in crop growth has been documented since years. After detailed analysis and classification of the soil patterns, two site specific factors, the plant-available-water and the O2 deficiency, were considered as the main causes of the crop growth variability in this field. Based on our measurement of root distribution in the soil profile, we hypothesize that in our case the insufficiency of the applied crop models to simulate the yield variability can be due to the oversimplification of the involved root models which fail to be sensitive to different soil conditions. In this study, the root growth model described by Jones et al. (1991) was adapted by using data of root distributions in the field and linking the adapted root model to the CERES crop model. The ability of the new root model to increase the sensitivity of the CERES crop models to different enviromental conditions was then evaluated by means of comparison of the simualtion results with measured data and by scenario calculations.

Assessing Lebanon's wildfire potential in association with current and future climatic conditions

Treesearch

George H. Mitri; Mireille G. Jazi; David McWethy

2015-01-01

The increasing occurrence and extent of large-scale wildfires in the Mediterranean have been linked to extended periods of warm and dry weather. We set out to assess Lebanon's wildfire potential in association with current and future climatic conditions. The Keetch-Byram Drought Index (KBDI) was the primary climate variable used in our evaluation of climate/fire...

Factors influencing fire severity under moderate burning conditions in the Klamath Mountains, northern California, USA

Treesearch

Becky L. Estes; Eric E. Knapp; Carl N. Skinner; Jay D. Miller; Haiganoush K. Preisler

2017-01-01

Topography, weather, and fuels are known factors driving fire behavior, but the degree to which each contributes to the spatial pattern of fire severity under different conditions remains poorly understood. The variability in severity within the boundaries of the 2006 wildfires that burned in the Klamath Mountains, northern California, along with data on burn...

Time-Hierarchical Clustering and Visualization of Weather Forecast Ensembles.

PubMed

Ferstl, Florian; Kanzler, Mathias; Rautenhaus, Marc; Westermann, Rudiger

2017-01-01

We propose a new approach for analyzing the temporal growth of the uncertainty in ensembles of weather forecasts which are started from perturbed but similar initial conditions. As an alternative to traditional approaches in meteorology, which use juxtaposition and animation of spaghetti plots of iso-contours, we make use of contour clustering and provide means to encode forecast dynamics and spread in one single visualization. Based on a given ensemble clustering in a specified time window, we merge clusters in time-reversed order to indicate when and where forecast trajectories start to diverge. We present and compare different visualizations of the resulting time-hierarchical grouping, including space-time surfaces built by connecting cluster representatives over time, and stacked contour variability plots. We demonstrate the effectiveness of our visual encodings with forecast examples of the European Centre for Medium-Range Weather Forecasts, which convey the evolution of specific features in the data as well as the temporally increasing spatial variability.

Effects of Weather Conditions on Oxidative Stress, Oxidative Damage, and Antioxidant Capacity in a Wild-Living Mammal, the European Badger (Meles meles).

PubMed

Bilham, Kirstin; Newman, Chris; Buesching, Christina D; Noonan, Michael J; Boyd, Amy; Smith, Adrian L; Macdonald, David W

Wild-living animals are subject to weather variability that may cause the generation of reactive oxygen species, resulting in oxidative stress and tissue damage, potentially driving demographic responses. Our 3-yr field study investigated the effects of seasonal weather conditions on biomarkers for oxidative stress, oxidative damage, and antioxidant defense in the European badger (Meles meles). We found age class effects: cubs were more susceptible to oxidative stress and oxidative damage than adults, especially very young cubs in the spring, when they also exhibited lower antioxidant biomarkers than adults. Although previous studies have found that intermediate spring and summer rainfall and warmer temperatures favor cub survival, counterintuitively these conditions were associated with more severe oxidative damage. Oxidative damage was high in cubs even when antioxidant biomarkers were high. In contrast, adult responses accorded with previous survival analyses. Wetter spring and summer conditions were associated with higher oxidative damage, but they were also associated with higher antioxidant biomarkers. Autumnal weather did not vary substantially from normative values, and thus effects were muted. Winter carryover effects were partially evident, with drier and milder conditions associated with greater oxidative damage in the following spring but also with higher antioxidant capacity. Plausibly, warmer conditions promoted more badger activity, with associated metabolic costs at a time of year when food supply is limited. Modeling biomarkers against projected climate change scenarios predicted greater future risks of oxidative damage, although not necessarily exceeding antioxidant capacity. This interdisciplinary approach demonstrates that individual adaptive physiological responses are associated with variation in natural environmental conditions.

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

NASA Technical Reports Server (NTRS)

Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

1997-01-01

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

Influence of weather and climate on subjective symptom intensity in atopic eczema

NASA Astrophysics Data System (ADS)

Vocks, E.; Busch, R.; Fröhlich, C.; Borelli, S.; Mayer, H.; Ring, J.

The frequent clinical observation that the course of atopic eczema, a skin disease involving a disturbed cutaneous barrier function, is influenced by climate and weather motivated us to analyse these relationships biometrically. In the Swiss high-mountain area of Davos the intensity of itching experienced by patients with atopic eczema was evaluated and compared to 15 single meteorological variables recorded daily during an entire 7-year observation period. By means of univariate analyses and multiple regressions, itch intensity was found to be correlated with some meteorological variables. A clear-cut inverse correlation exists with air temperature (coefficient of correlation: -0.235, P<0.001), but the effects of water vapour pressure, air pressure and hours of sunshine are less pronounced. The results show that itching in atopic eczema is significantly dependent on meteorological conditions. The data suggest that, in patients with atopic eczema, a certain range of thermo-hygric atmospheric conditions with a balance of heat and water loss on the skin surface is essential for the skin to feel comfortable.

A transient stochastic weather generator incorporating climate model uncertainty

NASA Astrophysics Data System (ADS)

Glenis, Vassilis; Pinamonti, Valentina; Hall, Jim W.; Kilsby, Chris G.

2015-11-01

Stochastic weather generators (WGs), which provide long synthetic time series of weather variables such as rainfall and potential evapotranspiration (PET), have found widespread use in water resources modelling. When conditioned upon the changes in climatic statistics (change factors, CFs) predicted by climate models, WGs provide a useful tool for climate impacts assessment and adaption planning. The latest climate modelling exercises have involved large numbers of global and regional climate models integrations, designed to explore the implications of uncertainties in the climate model formulation and parameter settings: so called 'perturbed physics ensembles' (PPEs). In this paper we show how these climate model uncertainties can be propagated through to impact studies by testing multiple vectors of CFs, each vector derived from a different sample from a PPE. We combine this with a new methodology to parameterise the projected time-evolution of CFs. We demonstrate how, when conditioned upon these time-dependent CFs, an existing, well validated and widely used WG can be used to generate non-stationary simulations of future climate that are consistent with probabilistic outputs from the Met Office Hadley Centre's Perturbed Physics Ensemble. The WG enables extensive sampling of natural variability and climate model uncertainty, providing the basis for development of robust water resources management strategies in the context of a non-stationary climate.

Remote sensing of atmospheric particulates: Technological innovation and physical limitations in applications to short-range weather prediction

NASA Technical Reports Server (NTRS)

Curran, R. J.; Kropfil, R.; Hallett, J.

1984-01-01

Techniques for remote sensing of particles, from cloud droplet to hailstone size, using optical and microwave frequencies are reviewed. The inherent variability of atmospheric particulates is examined to delineate conditions when the signal can give information to be effectively utilized in a forecasting context. The physical limitations resulting from the phase, size, orientation and concentration variability of the particulates are assessed.

Hourly predictive Levenberg-Marquardt ANN and multi linear regression models for predicting of dew point temperature

NASA Astrophysics Data System (ADS)

Zounemat-Kermani, Mohammad

2012-08-01

In this study, the ability of two models of multi linear regression (MLR) and Levenberg-Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash-Sutcliffe efficiency coefficient ( {| {{{Log}}({{NS}})} |} ) were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.

Late Mio-Pliocene chemical weathering of the Yulong porphyry Cu deposit in the eastern Tibetan Plateau constrained by goethite (U-Th)/He dating: Implication for Asian summer monsoon

NASA Astrophysics Data System (ADS)

Deng, Xiao-Dong; Li, Jian-Wei; Shuster, David L.

2017-08-01

Chemical weathering has provided a potentially important feedback between tectonic forcing and climate evolution of the Asian continent, although precise constraints on the timing and history of weathering are only variably documented. Here, we use goethite (U-Th)/He and 4He/3He geochronology to constrain the timing and rates of chemical weathering at the Yulong porphyry Cu deposit on the eastern Tibetan Plateau. Goethite grains have (U-Th)/He ages ranging from 6.73 ± 0.51 to 0.53 ± 0.04 Ma that correlate with independent paleoclimatic proxies inferred from supergene Mn-oxides and loess deposits under variable tectonic regimes and vegetation zones over the southeastern Asia. This correlation indicates that regional climatic conditions, especially monsoonal precipitation, controlled chemical weathering and goethite precipitation in a vast area of southeastern Asia. The goethite ages suggest that the Asian summer monsoon was relatively strong from 7 to 4.6 Ma, but weakened between 4.6 and 4 Ma, and then significantly intensified from 4 to 2 Ma. The precipitation ages of goethites collected along a 100-m-thick weathering profile decrease with depth, and indicate a downward propagation of the weathering front at rates of <6.7, 53.5 ± 10.8, and 4.8 ± 0.6 m/Ma during the intervals of 7-4, 4-2, and 2-0.7 Ma, respectively. The rapid propagation of weathering front during 4-2 Ma was caused by abrupt lowering of the water table, which was possibly related to local surface uplift or reorganization of the river systems in southeastern Tibet during this period.

A granulometry and secondary mineral fingerprint of chemical weathering in periglacial landscapes and its application to blockfield origins

NASA Astrophysics Data System (ADS)

Goodfellow, Bradley W.

2012-12-01

A review of published literature was undertaken to determine if there was a fingerprint of chemical weathering in regoliths subjected to periglacial conditions during their formation. If present, this fingerprint would be applied to the question of when blockfields in periglacial landscapes were initiated. These blocky diamicts are usually considered to represent remnants of regoliths that were chemically weathered under a warm, Neogene climate and therefore indicate surfaces that have undergone only a few metres to a few 10s of metres of erosion during the Quaternary. Based on a comparison of clay and silt abundances and secondary mineral assemblages from blockfields, other regoliths in periglacial settings, and regoliths from non-periglacial settings, a fingerprint of chemical weathering in periglacial landscapes was identified. A mobile regolith origin under, at least seasonal, periglacial conditions is indicated where clay(%) ≤ 0.5*silt(%) + 8 across a sample batch. This contrasts with a mobile regolith origin under non-periglacial conditions, which is indicated where clay(%) ≥ 0.5*silt(%) - 6 across a sample batch with clay(%) ≥ 0.5*silt(%) + 8 in at least one sample. A range of secondary minerals, which frequently includes interstratified minerals and indicates high local variability in leaching conditions, is also commonly present in regoliths exposed to periglacial conditions during their formation. Clay/silt ratios display a threshold response to temperature, related to the freezing point of water, but there is little response to precipitation or regolith residence time. Lithology controls clay and silt abundances, which increase from felsic, through intermediate, to mafic compositions, but does not control clay/silt ratios. Use of a sedigraph or Coulter Counter to determine regolith granulometry systematically indicates lower clay abundances and intra-site variability than use of a pipette or hydrometer. In contrast to clay/silt ratios, secondary mineral assemblages vary according to regolith residence time, temperature, and/or precipitation. A microsystems model is invoked as a conceptual framework in which to interpret the concurrent formation of the observed secondary mineral ranges. According to the fingerprint of chemical weathering in periglacial landscapes, there is generally no evidence of blockfield origins under warm Neogene climates. Nearly all blockfields appear to be a product of Quaternary physical and chemical weathering. A more dominant role for periglacial processes in further bevelling elevated, low relief, non-glacial surface remnants in otherwise glacially eroded landscapes is therefore indicated.

The association between temperature and mortality in tropical middle income Thailand from 1999 to 2008

NASA Astrophysics Data System (ADS)

Tawatsupa, Benjawan; Dear, Keith; Kjellstrom, Tord; Sleigh, Adrian

2014-03-01

We have investigated the association between tropical weather condition and age-sex adjusted death rates (ADR) in Thailand over a 10-year period from 1999 to 2008. Population, mortality, weather and air pollution data were obtained from four national databases. Alternating multivariable fractional polynomial (MFP) regression and stepwise multivariable linear regression analysis were used to sequentially build models of the associations between temperature variable and deaths, adjusted for the effects and interactions of age, sex, weather (6 variables), and air pollution (10 variables). The associations are explored and compared among three seasons (cold, hot and wet months) and four weather zones of Thailand (the North, Northeast, Central, and South regions). We found statistically significant associations between temperature and mortality in Thailand. The maximum temperature is the most important variable in predicting mortality. Overall, the association is nonlinear U-shape and 31 °C is the minimum-mortality temperature in Thailand. The death rates increase when maximum temperature increase with the highest rates in the North and Central during hot months. The final equation used in this study allowed estimation of the impact of a 4 °C increase in temperature as projected for Thailand by 2100; this analysis revealed that the heat-related deaths will increase more than the cold-related deaths avoided in the hot and wet months, and overall the net increase in expected mortality by region ranges from 5 to 13 % unless preventive measures were adopted. Overall, these results are useful for health impact assessment for the present situation and future public health implication of global climate change for tropical Thailand.

Ionospheric Response to Extremes in the Space Environment: Establishing Benchmarks for the Space Weather Action Plan.

NASA Astrophysics Data System (ADS)

Viereck, R. A.; Azeem, S. I.

2017-12-01

One of the goals of the National Space Weather Action Plan is to establish extreme event benchmarks. These benchmarks are estimates of environmental parameters that impact technologies and systems during extreme space weather events. Quantitative assessment of anticipated conditions during these extreme space weather event will enable operators and users of affected technologies to develop plans for mitigating space weather risks and improve preparedness. The ionosphere is one of the most important regions of space because so many applications either depend on ionospheric space weather for their operation (HF communication, over-the-horizon radars), or can be deleteriously affected by ionospheric conditions (e.g. GNSS navigation and timing, UHF satellite communications, synthetic aperture radar, HF communications). Since the processes that influence the ionosphere vary over time scales from seconds to years, it continues to be a challenge to adequately predict its behavior in many circumstances. Estimates with large uncertainties, in excess of 100%, may result in operators of impacted technologies over or under preparing for such events. The goal of the next phase of the benchmarking activity is to reduce these uncertainties. In this presentation, we will focus on the sources of uncertainty in the ionospheric response to extreme geomagnetic storms. We will then discuss various research efforts required to better understand the underlying processes of ionospheric variability and how the uncertainties in ionospheric response to extreme space weather could be reduced and the estimates improved.

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

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

USGS Publications Warehouse

Bradford, J.B.

2011-01-01

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

Compositional differences of phenolic compounds between black currant (Ribes nigrum L.) cultivars and their response to latitude and weather conditions.

PubMed

Zheng, Jie; Yang, Baoru; Ruusunen, Ville; Laaksonen, Oskar; Tahvonen, Risto; Hellsten, Jorma; Kallio, Heikki

2012-07-04

Phenolic compounds in black currants of three Finnish cultivars and their response to growth latitude and weather conditions were analyzed over a six-year period. 'Melalahti' had lower contents of total phenolic compounds (31.4% and 29.2% lower than 'Mortti' and 'Ola', respectively), total anthocyanins (32.6% and 30.5%), and total hydroxycinnamic acid derivatives (23.1% and 23.8%) (p < 0.05) and was less affected by growth latitude and weather conditions than 'Mortti' and 'Ola'. However, all the cultivars grown at higher latitude (66°34' N) had lower contents of total flavonols, total anthocyanins, and total phenolic compounds than those grown at lower latitude (60°23' N) (p < 0.05). The content of total hydroxycinnamic acid conjugates did not vary in 'Melalahti' (p > 0.05) but increased as the latitude increased in 'Mortti' and 'Ola' (p < 0.05). Temperature and radiation were the major weather variables influencing the composition of phenolic compounds. Delphinidin-3-O-glucoside, delphinidin-3-O-rutinoside, and myricetin-3-O-glucoside content showed positive correlations with temperature and radiation in all three cultivars. The study gives important guidelines for the selection of raw materials and growth sites as well as for the berry cultivation for commercial exploitation of black currant berries.

Angular Distributions of Discrete Mesoscale Mapping Functions

NASA Astrophysics Data System (ADS)

Kroszczyński, Krzysztof

2015-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

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

USGS Publications Warehouse

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

2002-01-01

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

Investigating Subjective Experience and the Influence of Weather Among Individuals With Fibromyalgia: A Content Analysis of Twitter.

PubMed

Delir Haghighi, Pari; Kang, Yong-Bin; Buchbinder, Rachelle; Burstein, Frada; Whittle, Samuel

2017-01-19

Little is understood about the determinants of symptom expression in individuals with fibromyalgia syndrome (FMS). While individuals with FMS often report environmental influences, including weather events, on their symptom severity, a consistent effect of specific weather conditions on FMS symptoms has yet to be demonstrated. Content analysis of a large number of messages by individuals with FMS on Twitter can provide valuable insights into variation in the fibromyalgia experience from a first-person perspective. The objective of our study was to use content analysis of tweets to investigate the association between weather conditions and fibromyalgia symptoms among individuals who tweet about fibromyalgia. Our second objective was to gain insight into how Twitter is used as a form of communication and expression by individuals with fibromyalgia and to explore and uncover thematic clusters and communities related to weather. Computerized sentiment analysis was performed to measure the association between negative sentiment scores (indicative of severe symptoms such as pain) and coincident environmental variables. Date, time, and location data for each individual tweet were used to identify corresponding climate data (such as temperature). We used graph analysis to investigate the frequency and distribution of domain-related terms exchanged in Twitter and their association strengths. A community detection algorithm was applied to partition the graph and detect different communities. We analyzed 140,432 tweets related to fibromyalgia from 2008 to 2014. There was a very weak positive correlation between humidity and negative sentiment scores (r=.009, P=.001). There was no significant correlation between other environmental variables and negative sentiment scores. The graph analysis showed that "pain" and "chronicpain" were the most frequently used terms. The Louvain method identified 6 communities. Community 1 was related to feelings and symptoms at the time (subjective experience). It also included a list of weather-related terms such as "weather," "cold," and "rain." According to our results, a uniform causal effect of weather variation on fibromyalgia symptoms at the group level remains unlikely. Any impact of weather on fibromyalgia symptoms may vary geographically or at an individual level. Future work will further explore geographic variation and interactions focusing on individual pain trajectories over time. ©Pari Delir Haghighi, Yong-Bin Kang, Rachelle Buchbinder, Frada Burstein, Samuel Whittle. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 19.01.2017.

Plants remember past weather: a study for atmospheric pollen concentrations of Ambrosia, Poaceae and Populus

NASA Astrophysics Data System (ADS)

Matyasovszky, István; Makra, László; Csépe, Zoltán; Sümeghy, Zoltán; Deák, Áron József; Pál-Molnár, Elemér; Tusnády, Gábor

2015-10-01

After extreme dry (wet) summers or years, pollen production of different taxa may decrease (increase) substantially. Accordingly, studying effects of current and past meteorological conditions on current pollen concentrations for different taxa have of major importance. The purpose of this study is separating the weight of current and past weather conditions influencing current pollen productions of three taxa. Two procedures, namely multiple correlations and factor analysis with special transformation are used. The 11-year (1997-2007) data sets include daily pollen counts of Ambrosia (ragweed), Poaceae (grasses) and Populus (poplar), as well as daily values of four climate variables (temperature, relative humidity, global solar flux and precipitation). Multiple correlations of daily pollen counts with simultaneous values of daily meteorological variables do not show annual course for Ambrosia, but do show definite trends for Populus and Poaceae. Results received using the two methods revealed characteristic similarities. For all the three taxa, the continental rainfall peak and additional local showers in the growing season can strengthen the weight of the current meteorological elements. However, due to the precipitation, big amount of water can be stored in the soil contributing to the effect of the past climate elements during dry periods. Higher climate sensitivity (especially water sensitivity) of the herbaceous taxa ( Ambrosia and Poaceae) can be definitely established compared to the arboreal Populus. Separation of the weight of the current and past weather conditions for different taxa involves practical importance both for health care and agricultural production.

Meteorological Variables and Behavior of Learners with Autism: An Examination of Possible Relationships

ERIC Educational Resources Information Center

VanBuskirk, Sabrina E.; Simpson, Richard L.

2013-01-01

For this study, we collected classroom behavioral data for three children with autism relative to daily meteorological conditions. Meteorological data, including barometric pressure, humidity, outdoor temperature, and moon illumination, were obtained from the National Weather Service. Relationships between children's individual target behaviors…

Considerations in the weathering of wood-plastic composites

Treesearch

Nicole M. Stark

2007-01-01

During weathering, wood-plastic composites (WPCs) can fade and lose stiffness and strength. Weathering variables that induce these changes include exposure to UV light and water. Each variable degrades WPCs independently, but can also act synergistically. Recent efforts have highlighted the need to understand how WPCs weather, and to develop schemes for protection. The...

Tying Variability in Summertime North American Extreme Weather Regimes to the Boreal Summer Intraseasonal Oscillation

NASA Astrophysics Data System (ADS)

Jenney, A. M.; Randall, D. A.

2017-12-01

Tropical intraseasonal oscillations are known to be a source of extratropical variability. We show that subseasonal variability in observed North American epidemiologically significant regional extreme weather regimes is teleconnected to the boreal summer intraseasonal oscillation (BSISO)—a complex tropical weather system that is active during the northern summer and has a 30-50 day timescale. The dynamics of the teleconnection are examined. We also find that interannual variability of the tropical mean-state can modulate the teleconnection. Our results suggest that the BSISO may enable subseasonal to seasonal predictions of North American summertime weather extremes.

Environmental links to interannual variability in shellfish toxicity in Cobscook Bay and eastern Maine, a strongly tidally mixed coastal region

NASA Astrophysics Data System (ADS)

Horecka, Hannah M.; Thomas, Andrew C.; Weatherbee, Ryan A.

2014-05-01

The Gulf of Maine experiences annual closures of shellfish harvesting due to the accumulation of toxins produced by dinoflagellates of the genus Alexandrium. Factors controlling the timing, location, and magnitude of these events in eastern Maine remain poorly understood. Previous work identified possible linkages between interannual variability of oceanographic variables and shellfish toxicity along the western Maine coastline but no such linkages were evident along the eastern Maine coast in the vicinity of Cobscook Bay, where strong tidal mixing tends to reduce seasonal variability in oceanographic properties. Using 21 years (1985-2005) of shellfish toxicity data, interannual variability in two metrics of annual toxicity, maximum magnitude and total annual toxicity, from stations in the Cobscook Bay region are examined for relationships to a suite of available environmental variables. Consistent with earlier work, no (or only weak) correlations were found between toxicity and oceanographic variables, even those very proximate to the stations such as local sea surface temperature. Similarly no correlations were evident between toxicity and air temperature, precipitation or relative humidity. The data suggest possible connections to local river discharge, but plausible mechanisms are not obvious. Correlations between toxicity and two variables indicative of local meteorological conditions, dew point and atmospheric pressure, both suggest a link between increased toxicity in these eastern Maine stations and weather conditions characterized by clearer skies/drier air (or less stormy/humid conditions). As no correlation of opposite sign was evident between toxicity and local precipitation, one plausible link is through light availability and its positive impact on phytoplankton production in this persistently foggy section of coast. These preliminary findings point to both the value of maintaining long-term shellfish toxicity sampling and a need for inclusion of weather variability in future modeling studies aimed at development of a more mechanistic understanding of factors controlling interannual differences in eastern Gulf of Maine shellfish toxicity.

There's no such thing as bad weather, just the wrong clothing: climate, weather and active school transportation in Toronto, Canada.

PubMed

Mitra, Raktim; Faulkner, Guy

2012-07-10

Climatic conditions may enable or deter active school transportation in many North American cities, but the topic remains largely overlooked in the existing literature. This study explores the effect of seasonal climate (i.e., fall versus winter) and weekly weather conditions (i.e., temperature, precipitation) on active travelling to school across different built and policy environments. Home-to-school trips by 11-12-year-old children in the City of Toronto were examined using data from the 2006 Transportation Tomorrow Survey. Binomial logistic regressions were estimated to explore the correlates of the choice of active (i.e., walking) versus non-active (i.e., private automobile, transit and school bus) mode for school trips. Climate and weather-related variables were not associated with choice of school travel mode. Children living within the sidewalk snow-plough zone (i.e., in the inner-suburban neighbourhoods) were less likely to walk to school than children living outside of the zone (i.e., in the inner-city neighbourhoods). Given that seasonality and short-term weather conditions appear not to limit active school transportation in general, built environment interventions designed to facilitate active travel could have benefits that spill over across the entire year rather than being limited to a particular season. Educational campaigns with strategies for making the trip fun and ensuring that the appropriate clothing choices are made are also warranted in complementing built environment modifications.

Atmospheric and oceanographic research review, 1978. [global weather, ocean/air interactions, and climate

NASA Technical Reports Server (NTRS)

1978-01-01

Research activities related to global weather, ocean/air interactions, and climate are reported. The global weather research is aimed at improving the assimilation of satellite-derived data in weather forecast models, developing analysis/forecast models that can more fully utilize satellite data, and developing new measures of forecast skill to properly assess the impact of satellite data on weather forecasting. The oceanographic research goal is to understand and model the processes that determine the general circulation of the oceans, focusing on those processes that affect sea surface temperature and oceanic heat storage, which are the oceanographic variables with the greatest influence on climate. The climate research objective is to support the development and effective utilization of space-acquired data systems in climate forecast models and to conduct sensitivity studies to determine the affect of lower boundary conditions on climate and predictability studies to determine which global climate features can be modeled either deterministically or statistically.

Spatially explicit modeling of blackbird abundance in the Prairie Pothole Region

USGS Publications Warehouse

Forcey, Greg M.; Thogmartin, Wayne E.; Linz, George M.; McKann, Patrick C.; Crimmins, Shawn M.

2015-01-01

Knowledge of factors influencing animal abundance is important to wildlife biologists developing management plans. This is especially true for economically important species such as blackbirds (Icteridae), which cause more than $100 million in crop damages annually in the United States. Using data from the North American Breeding Bird Survey, the National Land Cover Dataset, and the National Climatic Data Center, we modeled effects of regional environmental variables on relative abundance of 3 blackbird species (red-winged blackbird,Agelaius phoeniceus; yellow-headed blackbird, Xanthocephalus xanthocephalus; common grackle, Quiscalus quiscula) in the Prairie Pothole Region of the central United States. We evaluated landscape covariates at 3 logarithmically related spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and modeled weather variables at the 100,000-ha scale. We constructed models a priori using information from published habitat associations. We fit models with WinBUGS using Markov chain Monte Carlo techniques. Both landscape and weather variables contributed strongly to predicting blackbird relative abundance (95% credibility interval did not overlap 0). Variables with the strongest associations with blackbird relative abundance were the percentage of wetland area and precipitation amount from the year before bird surveys were conducted. The influence of spatial scale appeared small—models with the same variables expressed at different scales were often in the best model subset. This large-scale study elucidated regional effects of weather and landscape variables, suggesting that management strategies aimed at reducing damages caused by these species should consider the broader landscape, including weather effects, because such factors may outweigh the influence of localized conditions or site-specific management actions. The regional species distributional models we developed for blackbirds provide a tool for understanding these broader landscape effects and guiding wildlife management practices to areas that are optimally beneficial. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Water vapour fluxes trends on different time scales and their relationship with weather and soil drivers: a case study from a dehesa site in South Spain

NASA Astrophysics Data System (ADS)

Polo, María José; Egüen, Marta; Andreu, Ana; Carpintero, Elisabet; Gómez-Giráldez, Pedro; Patrocinio González-Dugo, María

2017-04-01

Water vapour fluxes between the soil surface and the atmosphere constitute one of the most important components of the water cycle in the continental areas. Their regime directly affect the availability of water to plants, water storage in surface bodies, air humidity in the boundary layer, snow persistence… among others, and the list of indirectly affected processes comprises a large number of components. Water potential or wetness gradients are some of the main drivers of water vapour fluxes to the atmosphere; soil humidity is usually monitored as key variable in many hydrological and environmental studies, and its estimated series are used to calibrate and validate the modelling of certain hydrological processes. However, such results may differ when water fluxes are used instead of water state variables, such as humidity. This work shows the analysis of high resolution water vapour fluxes series from a dehesa area in South Spain where a complete energy and water fluxes/variables monitoring site has been operating for the last four years. The results include pasture and tree vegetated control points. The daily water budget calculation on both types of sites has been performed from weather and energy fluxes measurements, and soil moisture measurements, and the results have been aggregated on a weekly, monthly and seasonal basis. Comparison between observed trends of soil moisture and calculated trends of water vapour fluxes is included to show the differences arising in terms of the regime of the dominant weather variables in this type of ecosystems. The results identify significant thresholds for each weather variable driver and highlight the importance of the wind regime, which is the somehow forgotten variable in future climate impacts on hydrology. Further work is being carried out to assess water cycle potential trends under future climate conditions and their impacts on the vegetation in dehesa ecosystems.

Influence of Anthropogenic Climate Change on Planetary Wave Resonance and Extreme Weather Events.

PubMed

Mann, Michael E; Rahmstorf, Stefan; Kornhuber, Kai; Steinman, Byron A; Miller, Sonya K; Coumou, Dim

2017-03-27

Persistent episodes of extreme weather in the Northern Hemisphere summer have been shown to be associated with the presence of high-amplitude quasi-stationary atmospheric Rossby waves within a particular wavelength range (zonal wavenumber 6-8). The underlying mechanistic relationship involves the phenomenon of quasi-resonant amplification (QRA) of synoptic-scale waves with that wavenumber range becoming trapped within an effective mid-latitude atmospheric waveguide. Recent work suggests an increase in recent decades in the occurrence of QRA-favorable conditions and associated extreme weather, possibly linked to amplified Arctic warming and thus a climate change influence. Here, we isolate a specific fingerprint in the zonal mean surface temperature profile that is associated with QRA-favorable conditions. State-of-the-art ("CMIP5") historical climate model simulations subject to anthropogenic forcing display an increase in the projection of this fingerprint that is mirrored in multiple observational surface temperature datasets. Both the models and observations suggest this signal has only recently emerged from the background noise of natural variability.

Utilization of Live Localized Weather Information for Sustainable Agriculture

NASA Astrophysics Data System (ADS)

Anderson, J.; Usher, J.

2010-09-01

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

Ecology of West Nile virus across four European countries: empirical modelling of the Culex pipiens abundance dynamics as a function of weather.

PubMed

Groen, Thomas A; L'Ambert, Gregory; Bellini, Romeo; Chaskopoulou, Alexandra; Petric, Dusan; Zgomba, Marija; Marrama, Laurence; Bicout, Dominique J

2017-10-26

Culex pipiens is the major vector of West Nile virus in Europe, and is causing frequent outbreaks throughout the southern part of the continent. Proper empirical modelling of the population dynamics of this species can help in understanding West Nile virus epidemiology, optimizing vector surveillance and mosquito control efforts. But modelling results may differ from place to place. In this study we look at which type of models and weather variables can be consistently used across different locations. Weekly mosquito trap collections from eight functional units located in France, Greece, Italy and Serbia for several years were combined. Additionally, rainfall, relative humidity and temperature were recorded. Correlations between lagged weather conditions and Cx. pipiens dynamics were analysed. Also seasonal autoregressive integrated moving-average (SARIMA) models were fitted to describe the temporal dynamics of Cx. pipiens and to check whether the weather variables could improve these models. Correlations were strongest between mean temperatures at short time lags, followed by relative humidity, most likely due to collinearity. Precipitation alone had weak correlations and inconsistent patterns across sites. SARIMA models could also make reasonable predictions, especially when longer time series of Cx. pipiens observations are available. Average temperature was a consistently good predictor across sites. When only short time series (~ < 4 years) of observations are available, average temperature can therefore be used to model Cx. pipiens dynamics. When longer time series (~ > 4 years) are available, SARIMAs can provide better statistical descriptions of Cx. pipiens dynamics, without the need for further weather variables. This suggests that density dependence is also an important determinant of Cx. pipiens dynamics.

Weather chains during the 2013/2014 winter and their significance for seasonal prediction

NASA Astrophysics Data System (ADS)

Davies, Huw C.

2015-11-01

Day-to-day weather forecasting has improved substantially over the past few decades. In contrast, progress in seasonal prediction outside the tropics has been meagre and mixed. On seasonal timescales, the constraining influence of the initial atmospheric state is weak, and the internal variability associated with transient weather systems tends to be large compared with the nuanced influence of anomalies in external forcing. Current research and operational activities focus on exploring and exploiting potential links between external anomalies and seasonal-mean climate patterns. Here I examine reanalysed meteorological data sets for the unusual winter 2013/2014, with drought and freezing conditions juxtaposed over North America and severe wet and stormy weather over parts of Europe, to study the role of weather systems and their transient upper-tropospheric flow patterns. I find that the amplitude, recurrence and location of these transient patterns account directly for the corresponding anomalous seasonal-mean patterns. They occurred episodically and sequentially, were linked dynamically, and exhibited some circumpolar connectivity. I conclude that the upper-tropospheric components of transient weather systems are significant for understanding and predicting seasonal weather patterns, whereas the role of external factors is more subtle.

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

PubMed

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.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters

USGS Publications Warehouse

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

Geochemical evolution of the Critical Zone across variable time scales informs concentration-discharge relationships: Jemez River Basin Critical Zone Observatory

NASA Astrophysics Data System (ADS)

McIntosh, Jennifer C.; Schaumberg, Courtney; Perdrial, Julia; Harpold, Adrian; Vázquez-Ortega, Angélica; Rasmussen, Craig; Vinson, David; Zapata-Rios, Xavier; Brooks, Paul D.; Meixner, Thomas; Pelletier, Jon; Derry, Louis; Chorover, Jon

2017-05-01

This study investigates the influence of water, carbon, and energy fluxes on solute production and transport through the Jemez Critical Zone (CZ) and impacts on C-Q relationships over variable spatial and temporal scales. Chemical depletion-enrichment profiles of soils, combined with regolith thickness and groundwater data indicate the importance to stream hydrochemistry of incongruent dissolution of silicate minerals during deep bedrock weathering, which is primarily limited by water fluxes, in this highly fractured, young volcanic terrain. Under high flow conditions (e.g., spring snowmelt), wetting of soil and regolith surfaces and presence of organic acids promote mineral dissolution and provide a constant supply of base cations, Si, and DIC to soil water and groundwater. Mixing of waters from different hydrochemical reservoirs in the near stream environment during "wet" periods leads to the chemostatic behavior of DIC, base cations, and Si in stream flow. Metals transported by organic matter complexation (i.e., Ge, Al) and/or colloids (i.e., Al) during periods of soil saturation and lateral connectivity to the stream display a positive relationship with Q. Variable Si-Q relationships, under all but the highest flow conditions, can be explained by nonconservative transport and precipitation of clay minerals, which influences long versus short-term Si weathering fluxes. By combining measurements of the CZ obtained across different spatial and temporal scales, we were able to constrain weathering processes in different hydrological reservoirs that may be flushed to the stream during hydrologic events, thereby informing C-Q relationships.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters.

PubMed

Grisham, Blake A; Boal, Clint W; Haukos, David A; Davis, Dawn M; Boydston, Kathy K; Dixon, Charles; Heck, Willard R

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

Wave Coupling between the Lower and Middle Thermosphere as Viewed from Quasi-Sun-Synchronous Satellites

NASA Astrophysics Data System (ADS)

Gasperini, Federico

In a society increasingly dependent on space technology, space weather has become a prominent scientific paradigm. In the last decade evidence has shown that terrestrial weather significantly influences space weather. Periodic absorption of solar radiation in local time and longitude by tropospheric water vapor and stratospheric ozone as well as latent heat release in clouds generate a spatially- and temporally-evolving spectrum of global-scale atmospheric waves (i.e., tides, planetary waves and Kelvin waves). A subset of these waves propagates vertically, evolving with height due to wave-mean flow, wave-wave, and wave-plasma interactions, and driving electric fields of tidal origin in the dynamo region. While considerable improvements have been made on the understanding of MLT dynamics, driven in part by the development and deployment of new instruments and techniques, relatively little is known about the coupling of waves in the 120-300 km `thermospheric gap' between satellite remote-sensing and in-situ wave diagnostics. The dissertation herein reveals vertical wave coupling in this height region and quantifies its role in determining thermospheric variability. This objective is accomplished employing quasi-Sun-synchronous satellite measurements (i.e., TIMED, CHAMP, and GOCE) and state-of-the-art numerical modeling simulations (i.e., TIME-GCM/MERRA). Evidence is found for the vertical propagation from the lower to the middle thermosphere of the eastward propagating diurnal tide with zonal wave number 3 (DE3) and the 3-day ultra-fast Kelvin wave (UFKW), two major global-scale atmospheric oscillations of tropospheric origin. These waves are shown to nonlinearly interact and produce secondary waves responsible for significant longitudinal and day-to-day variability. For solar and geomagnetic quiet conditions, atmospheric waves are found to be responsible for up to 60% of the total variability, demonstrating lower atmosphere coupling as a key contributor to thermosphere weather, at least in the absence of major solar-driven variability. Additionally, background atmospheric conditions (i.e., dissipation and zonal mean winds) and found to significantly impact the latitudinal-temporal evolution of upward propagating waves.

Blood pressure response to patterns of weather fluctuations and effect on mortality.

PubMed

Aubinière-Robb, Louise; Jeemon, Panniyammakal; Hastie, Claire E; Patel, Rajan K; McCallum, Linsay; Morrison, David; Walters, Matthew; Dawson, Jesse; Sloan, William; Muir, Scott; Dominiczak, Anna F; McInnes, Gordon T; Padmanabhan, Sandosh

2013-07-01

Very few studies have looked at longitudinal intraindividual blood pressure responses to weather conditions. There are no data to suggest that specific response to changes in weather will have an impact on survival. We analyzed >169 000 clinic visits of 16 010 Glasgow Blood Pressure Clinic patients with hypertension. Each clinic visit was mapped to the mean West of Scotland monthly weather (temperature, sunshine, rainfall) data. Percentage change in blood pressure was calculated between pairs of consecutive clinic visits, where the weather alternated between 2 extreme quartiles (Q(1)-Q(4) or Q(4)-Q(1)) or remained in the same quartile (Q(n)-Q(n)) of each weather parameter. Subjects were also categorized into 2 groups depending on whether their blood pressure response in Q(1)-Q(4) or Q(4)-Q(1) were concordant or discordant to Q(n)-Q(n). Generalized estimating equations and Cox proportional hazards model were used to model the effect on longitudinal blood pressure and mortality, respectively. Q(n)-Q(n) showed a mean 2% drop in blood pressure consistently, whereas Q(4)-Q(1) showed a mean 2.1% and 1.6% rise in systolic and diastolic blood pressure, respectively. However, Q(1)-Q(4) did not show significant changes in blood pressure. Temperature-sensitive subjects had significantly higher mortality (1.35 [95% confidence interval, 1.06-1.71]; P=0.01) and higher follow-up systolic blood pressure (1.85 [95% confidence interval, 0.24-3.46]; P=0.02) compared with temperature-nonsensitive subjects. Blood pressure response to temperature may be one of the underlying mechanisms that determine long-term blood pressure variability. Knowing a patient's blood pressure response to weather can help reduce unnecessary antihypertensive treatment modification, which may in turn increase blood pressure variability and, thus, risk.

Permafrost as an additional driving factor for the extreme fire event in the boreal Baikal region in 2003

NASA Astrophysics Data System (ADS)

Forkel, M.; Thonicke, K.; Beer, C.; Cramer, W.; Bartalev, S.; Schmullius, C.

2012-04-01

Wildfires are a natural and important element in the functioning of boreal forests. However, in some years, fires with extreme spread and severity occur. Such severe fires degrade the forest, affect human values, emit huge amount of carbon and aerosols and alter the land surface albedo. Usually, wind, slope, and dry conditions have been recognized as factors determining fire spread. In the Baikal region, 127,000 km2 burned in 2003, while the annual average burned area is approx. 8100 km2. In average years, 16% of the burned area occurred in the continuous permafrost zone but in 2003, 33% of these burned areas coincide with the existence of permanently frozen grounds. Permafrost and the associated upper active layer, which thaws during summer and refreezes during winter, is an important supply for soil moisture in boreal ecosystems. This leads to the question if permafrost hydrology is a potential additional driving factor for extreme fire events in boreal forests. Using temperature and precipitation data, we calculated the Nesterov index as indicator for fire weather conditions. Further, we used satellite observations of burned area and surface moisture, a digital elevation model, a land cover and a permafrost map to evaluate drivers for the temporal dynamic and spatial variability of surface moisture conditions and burned area in spring 2003. On the basis of time series decomposition, we separated the effect of drivers for fire activity on different time scales. We next computed cross-correlations to identify potential time lags between weather conditions, surface moisture and fire activity. Finally, we assessed the predictive capability of different combinations of driving variables for surface moisture conditions and burned area using multivariate spatial-temporal regression models. The results from this study demonstrate that permafrost in larch-dominated ecosystems regulates the inter-annual variability of surface moisture and thus increases the inter-annual variability of burned area. The drought conditions in spring 2003 were accelerated by the presence of permafrost because less water was stored in the upper active layer from the dry previous summer 2002 and the permafrost table prevents vegetative water uptake from deeper layers. In contrast, weather conditions (precipitation anomaly, Nesterov index) are weaker predictors for the 2003 fire event. Our analysis advances the understanding of complex interactions between the atmosphere, vegetation and soil on how feedback mechanisms can lead to extreme fire events. These findings emphasize the importance of a mechanistic coupling of soil thermodynamics, hydrology, and fire activity in earth system models for projecting climate change impacts over the next century.

What is the benefit of driving a hydrological model with data from a multi-site weather generator compared to data from a simple delta change approach?"

NASA Astrophysics Data System (ADS)

Rössler, Ole; Keller, Denise; Fischer, Andreas

2016-04-01

In 2011 the Swiss national consortium C2SM providednew climate change scenarios were released in Switzerland that came with a comprehensive data set of temperature and precipitation changes under climate change conditions for every a large network of meteorological stations, and for aggregated as well as regions in across Switzerland. These climate change signals were generated for three emission scenarios and three different future time-periods and designed to be used asbased on a delta change factors approach. This data set proved to be very successful in Switzerland as many different users, researchers, private companies, and societal users were able to use and interpret the climate data set. Thus, a range of applications that are all based on the same climate data set enabled a comparable view on climate change impact in several disciplines. The main limitation and criticism to this data set was the usage of the delta change approach for downscaling as it comes with severe limitations such as underestimatinges changes in extreme values and neglecting changes in variability and changes in temporal sequencesneglecting changes in variability, be it year-to-year or day-to-day, and changes in temporal sequences . lacks a change in the day-to-day-variability. One way to overcome this the latter limitation is the usage of stochastic weather generators in a downscaling context. Weather generators are known to be one suitable downscaling technique, but A common limitation of most weather generators is the absence of spatial consistency rrelation in the generated daily time-series, resulting in an underestimation of areal means over several stations that are often low-biased. refer to one point scale (single-site) and lacks the spatial representation of weather. The latter A realistic representation of the inter-station correlation in the downscaled time-series This is of high particular importance in some impact studies, especially infor any hydrological impact studiesy. Recently, a multi-site weather generator was developed and tested for downscaling purposes over Switzerland. The weather generator is of type Richardson, that is run with spatially correlated random number streams to ensure spatial consistency. As a downside, multi-site weather generators are much more complex to develop, but they are a very promising alternative downscaling technique. A new multi-site-weather generator was developed for Switzerland in a previous study (Keller et al. 2014). In this study, we tested this new multi-site-weather generator against the "standard" delta change derived data in a hydrological impact assessment study that focused on runoff in the meso-scale catchment of the river Thur catchment. Two hydrological models of different complexity were run with the data sets under present (1980-2009) and under future conditions (2070-2099), assuming the SRES A1B emission2070-2100 scenario conditions. Eight meteorological stations were used to interpolate a meteorological field that served as input to calibrate and validate the two hydrological models against runoff. The downscaling intercomparison was done for We applied 10 GCM-RCM combinations simulations of the ENSEMBLES. In case of the weather generator, that allows for multiple synthetic realizations, we generated for which change factors for each station (delta change approach) were available and generated 25 realizations of multi-site weather. with each climate model projection. Results show that the delta change driven data constitutes only one appropriate representation compared to theof a bandwidth of runoff projections yielded by the multi-site weather generator data. Especially oOn average, differences between both the two approaches are small. Low and high runoff Runoff values to both extremes are however better reproduced with the weather generator driven data set. The stochastic representation of multiday rainfall events are considered as the main reason. Hence, tThere is a clear yet small added value to the delta change approach that in turn performs rather well. Although these small but considerable differences might questioning the need to construct a multi-site-weather generator with a huge effort, the potential and possibilities to further develop the multi-site weather generator is undoubted.

Gauging climate change effects at local scales: weather-based indices to monitor insect harassment in caribou.

PubMed

Witter, Leslie A; Johnson, Chris J; Croft, Bruno; Gunn, Anne; Poirier, Lisa M

2012-09-01

Climate change is occurring at an accelerated rate in the Arctic. Insect harassment may be an important link between increased summer temperature and reduced body condition in caribou and reindeer (both Rangifer tarandus). To examine the effects of climate change at a scale relevant to Rangifer herds, we developed monitoring indices using weather to predict activity of parasitic insects across the central Arctic. During 2007-2009, we recorded weather conditions and used carbon dioxide baited traps to monitor activity of mosquitoes (Culicidae), black flies (Simuliidae), and oestrid flies (Oestridae) on the post-calving and summer range of the Bathurst barren-ground caribou (Rangifer tarandus groenlandicus) herd in Northwest Territories and Nunavut, Canada. We developed statistical models representing hypotheses about effects of weather, habitat, location, and temporal variables on insect activity. We used multinomial logistic regression to model mosquito and black fly activity, and logistic regression to model oestrid fly presence. We used information theory to select models to predict activity levels of insects. Using historical weather data, we used hindcasting to develop a chronology of insect activity on the Bathurst range from 1957 to 2008. Oestrid presence and mosquito and black fly activity levels were explained by temperature. Wind speed, light intensity, barometric pressure, relative humidity, vegetation, topography, location, time of day, and growing degree-days also affected mosquito and black fly levels. High predictive ability of all models justified the use of weather to index insect activity. Retrospective analyses indicated conditions favoring mosquito activity declined since the late 1950s, while predicted black fly and oestrid activity increased. Our indices can be used as monitoring tools to gauge potential changes in insect harassment due to climate change at scales relevant to caribou herds.

Use of a Principal Components Analysis for the Generation of Daily Time Series.

NASA Astrophysics Data System (ADS)

Dreveton, Christine; Guillou, Yann

2004-07-01

A new approach for generating daily time series is considered in response to the weather-derivatives market. This approach consists of performing a principal components analysis to create independent variables, the values of which are then generated separately with a random process. Weather derivatives are financial or insurance products that give companies the opportunity to cover themselves against adverse climate conditions. The aim of a generator is to provide a wider range of feasible situations to be used in an assessment of risk. Generation of a temperature time series is required by insurers or bankers for pricing weather options. The provision of conditional probabilities and a good representation of the interannual variance are the main challenges of a generator when used for weather derivatives. The generator was developed according to this new approach using a principal components analysis and was applied to the daily average temperature time series of the Paris-Montsouris station in France. The observed dataset was homogenized and the trend was removed to represent correctly the present climate. The results obtained with the generator show that it represents correctly the interannual variance of the observed climate; this is the main result of the work, because one of the main discrepancies of other generators is their inability to represent accurately the observed interannual climate variance—this discrepancy is not acceptable for an application to weather derivatives. The generator was also tested to calculate conditional probabilities: for example, the knowledge of the aggregated value of heating degree-days in the middle of the heating season allows one to estimate the probability if reaching a threshold at the end of the heating season. This represents the main application of a climate generator for use with weather derivatives.

Severe haze in Hangzhou in winter 2013/14 and associated meteorological anomalies

NASA Astrophysics Data System (ADS)

Chen, Yini; Zhu, Zhiwei; Luo, Ling; Zhang, Jiwei

2018-03-01

Aerosol pollution over eastern China has worsened considerably in recent years, resulting in heavy haze weather with low visibility and poor air quality. The present study investigates the characteristics of haze weather in Hangzhou city, and aims to unravel the meteorological anomalies associated with the heavy haze that occurred over Hangzhou in winter 2013/14. On the interannual timescale, because of the neutral condition of tropical sea surface temperature anomalies during winter 2013/14, no significant circulation and convection anomalies were induced over East Asia, leading to a stable atmospheric condition favorable for haze weather in Hangzhou. Besides, the shift of the polar vortex, caused by changes in surface temperature and ice cover at high latitudes, induced a barotropic anomalous circulation dipole pattern. The southerly anomaly associated with this anomalous dipole pattern hindered the transportation of cold/clear air mass from Siberia to central-eastern China, leading to abnormal haze during winter 2013/14 in Hangzhou. On the intraseasonal timescale, an eastward-propagating mid-latitude Rossby wave train altered the meridional wind anomaly over East Asia, causing the intraseasonal variability of haze weather during 2013/14 in Hangzhou.

The potential health impacts of climate variability and change for the United States: executive summary of the report of the health sector of the U.S. National Assessment.

PubMed Central

Patz, J A; McGeehin, M A; Bernard, S M; Ebi, K L; Epstein, P R; Grambsch, A; Gubler, D J; Reither, P; Romieu, I; Rose, J B; Samet, J M; Trtanj, J

2000-01-01

We examined the potential impacts of climate variability and change on human health as part of a congressionally mandated study of climate change in the United States. Our author team, comprising experts from academia, government, and the private sector, was selected by the federal interagency U.S. Global Change Research Program, and this report stems from our first 18 months of work. For this assessment we used a set of assumptions and/or projections of future climates developed for all participants in the National Assessment of the Potential Consequences of Climate Variability and Change. We identified five categories of health outcomes that are most likely to be affected by climate change because they are associated with weather and/or climate variables: temperature-related morbidity and mortality; health effects of extreme weather events (storms, tornadoes, hurricanes, and precipitation extremes); air-pollution-related health effects; water- and foodborne diseases; and vector- and rodent-borne diseases. We concluded that the levels of uncertainty preclude any definitive statement on the direction of potential future change for each of these health outcomes, although we developed some hypotheses. Although we mainly addressed adverse health outcomes, we identified some positive health outcomes, notably reduced cold-weather mortality, which has not been extensively examined. We found that at present most of the U.S. population is protected against adverse health outcomes associated with weather and/or climate, although certain demographic and geographic populations are at increased risk. We concluded that vigilance in the maintenance and improvement of public health systems and their responsiveness to changing climate conditions and to identified vulnerable subpopulations should help to protect the U.S. population from any adverse health outcomes of projected climate change. PMID:10753097

The potential health impacts of climate variability and change for the United States: executive summary of the report of the health sector of the U.S. National Assessment.

PubMed

Patz, J A; McGeehin, M A; Bernard, S M; Ebi, K L; Epstein, P R; Grambsch, A; Gubler, D J; Reither, P; Romieu, I; Rose, J B; Samet, J M; Trtanj, J

2000-04-01

We examined the potential impacts of climate variability and change on human health as part of a congressionally mandated study of climate change in the United States. Our author team, comprising experts from academia, government, and the private sector, was selected by the federal interagency U.S. Global Change Research Program, and this report stems from our first 18 months of work. For this assessment we used a set of assumptions and/or projections of future climates developed for all participants in the National Assessment of the Potential Consequences of Climate Variability and Change. We identified five categories of health outcomes that are most likely to be affected by climate change because they are associated with weather and/or climate variables: temperature-related morbidity and mortality; health effects of extreme weather events (storms, tornadoes, hurricanes, and precipitation extremes); air-pollution-related health effects; water- and foodborne diseases; and vector- and rodent-borne diseases. We concluded that the levels of uncertainty preclude any definitive statement on the direction of potential future change for each of these health outcomes, although we developed some hypotheses. Although we mainly addressed adverse health outcomes, we identified some positive health outcomes, notably reduced cold-weather mortality, which has not been extensively examined. We found that at present most of the U.S. population is protected against adverse health outcomes associated with weather and/or climate, although certain demographic and geographic populations are at increased risk. We concluded that vigilance in the maintenance and improvement of public health systems and their responsiveness to changing climate conditions and to identified vulnerable subpopulations should help to protect the U.S. population from any adverse health outcomes of projected climate change.

The association between temperature and mortality in tropical middle income Thailand from 1999 to 2008.

PubMed

Tawatsupa, Benjawan; Dear, Keith; Kjellstrom, Tord; Sleigh, Adrian

2014-03-01

We have investigated the association between tropical weather condition and age-sex adjusted death rates (ADR) in Thailand over a 10-year period from 1999 to 2008. Population, mortality, weather and air pollution data were obtained from four national databases. Alternating multivariable fractional polynomial (MFP) regression and stepwise multivariable linear regression analysis were used to sequentially build models of the associations between temperature variable and deaths, adjusted for the effects and interactions of age, sex, weather (6 variables), and air pollution (10 variables). The associations are explored and compared among three seasons (cold, hot and wet months) and four weather zones of Thailand (the North, Northeast, Central, and South regions). We found statistically significant associations between temperature and mortality in Thailand. The maximum temperature is the most important variable in predicting mortality. Overall, the association is nonlinear U-shape and 31 °C is the minimum-mortality temperature in Thailand. The death rates increase when maximum temperature increase with the highest rates in the North and Central during hot months. The final equation used in this study allowed estimation of the impact of a 4 °C increase in temperature as projected for Thailand by 2100; this analysis revealed that the heat-related deaths will increase more than the cold-related deaths avoided in the hot and wet months, and overall the net increase in expected mortality by region ranges from 5 to 13 % unless preventive measures were adopted. Overall, these results are useful for health impact assessment for the present situation and future public health implication of global climate change for tropical Thailand.

Effect of Weather Variability on Seasonal Influenza Among Different Age Groups in Queensland, Australia: A Bayesian Spatiotemporal Analysis.

PubMed

Huang, Xiaodong; Mengersen, Kerrie; Milinovich, Gabriel; Hu, Wenbiao

2017-06-01

The effects of weather variability on seasonal influenza among different age groups remain unclear. The comparative study aims to explore the differences in the associations between weather variability and seasonal influenza, and growth rates of seasonal influenza epidemics among different age groups in Queensland, Australia. Three Bayesian spatiotemporal conditional autoregressive models were fitted at the postal area level to quantify the relationships between seasonal influenza and monthly minimum temperature (MIT), monthly vapor pressure, school calendar pattern, and Index of Relative Socio-Economic Advantage and Disadvantage for 3 age groups (<15, 15-64, and ≥65 years). The results showed that the expected decrease in monthly influenza cases was 19.3% (95% credible interval [CI], 14.7%-23.4%), 16.3% (95% CI, 13.6%-19.0%), and 8.5% (95% CI, 1.5%-15.0%) for a 1°C increase in monthly MIT at <15, 15-64, and ≥65 years of age, respectively, while the average increase in the monthly influenza cases was 14.6% (95% CI, 9.0%-21.0%), 12.1% (95% CI, 8.8%-16.1%), and 9.2% (95% CI, 1.4%-16.9%) for a 1-hPa increase in vapor pressure. Weather variability appears to be more influential on seasonal influenza transmission in younger (0-14) age groups. The growth rates of influenza at postal area level were relatively small for older (≥65) age groups in Queensland, Australia. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

A climatology of weather-driven mixing events in a dimictic Arctic lake

NASA Astrophysics Data System (ADS)

Cooke, Melanie; MacIntyre, Sally; Kushner, Paul

2014-05-01

For dimictic and polymictic Arctic lakes, mixing during the ice-free season is primarily controlled by the passage of cold fronts and their associated strong winds. At Toolik Lake, a Long Term Ecological Research site in Alaska, year-to-year variability in lake stability and mixing frequency has been considerable over the past 14 summers. Mixing is important for lake productivity, distributing dissolved gases and nutrients through the water column. Summertime Arctic warming might be expected to stabilize Arctic lakes such as Toolik, but the control of individual weather events on a season's mixing characteristics complicates the ability to predict trends in stability and mixing. With this motivation, this work aims to characterize weather systems that are conducive to mixing at Toolik. High resolution lake and meteorological data from the site were used to characterize mixing while atmospheric reanalysis data were used to describe the weather systems. Mixing events were first identified using an automated algorithm based on Lake Number and lake thermal structure. The algorithm identified mixing events that are separated by at least the timescale of weather systems, so that any given weather event should cause at most one mixing event. Because low Lake Number conditions typically highlight strong wind events, temperature profile data over time were used to identify thermocline deepening as a complementary indicator for mixing. Mixing events were found to be most often characterized by simultaneous occurrence of a low Lake Number condition and thermocline deepening. Once mixing events were identified, they were classified according to their corresponding atmospheric structures. Two primary weather system types with distinct characteristics were determined to be associated with mixing. The analysis suggests that changing the occurrence of these weather system types might change the summertime thermal structure of Toolik Lake, and by extension other lakes in the region.

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

PubMed

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

2015-12-01

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

Rainfall and temperature distinguish between Karnal bunt positive and negative years in wheat fields in Texas.

PubMed

Workneh, F; Allen, T W; Nash, G H; Narasimhan, B; Srinivasan, R; Rush, C M

2008-01-01

Karnal bunt of wheat, caused by the fungus Tilletia indica, is an internationally regulated disease. Since its first detection in central Texas in 1997, regions in which the disease was detected have been under strict federal quarantine regulations resulting in significant economic losses. A study was conducted to determine the effect of weather factors on incidence of the disease since its first detection in Texas. Weather variables (temperature and rainfall amount and frequency) were collected and used as predictors in discriminant analysis for classifying bunt-positive and -negative fields using incidence data for 1997 and 2000 to 2003 in San Saba County. Rainfall amount and frequency were obtained from radar (Doppler radar) measurements. The three weather variables correctly classified 100% of the cases into bunt-positive or -negative fields during the specific period overlapping the stage of wheat susceptibility (boot to soft dough) in the region. A linear discriminant-function model then was developed for use in classification of new weather variables into the bunt occurrence groups (+ or -). The model was evaluated using weather data for 2004 to 2006 for San Saba area (central Texas), and data for 2001 and 2002 for Olney area (north-central Texas). The model correctly predicted bunt occurrence in all cases except for the year 2004. The model was also evaluated for site-specific prediction of the disease using radar rainfall data and in most cases provided similar results as the regional level evaluation. The humid thermal index (HTI) model (widely used for assessing risk of Karnal bunt) agreed with our model in all cases in the regional level evaluation, including the year 2004 for the San Saba area, except for the Olney area where it incorrectly predicted weather conditions in 2001 as unfavorable. The current model has a potential to be used in a spray advisory program in regulated wheat fields.

A Modeling Study of the Causes and Predictability of the Spring 2011 Extreme U.S. Weather Activity

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Chang, Yehui; Wang, Hailan; Koster, Randal; Suarez, Max

2016-01-01

This study examines the causes and predictability of the spring 2011 U.S. extreme weather using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Goddard Earth Observing System Model, version 5, (GEOS-5) atmospheric general circulation model simulations. The focus is on assessing the impact on precipitation of sea surface temperature (SST) anomalies, land conditions, and large-scale atmospheric modes of variability. A key result is that the April record-breaking precipitation in the Ohio River valley was primarily the result of the unforced development of a positive North Atlantic Oscillation (NAO)-like mode of variability with unusually large amplitude, limiting the predictability of the precipitation in that region at 1-month leads. SST forcing (La Nia conditions) contributed to the broader continental-scale pattern of precipitation anomalies, producing drying in the southern plains and weak wet anomalies in the northeast, while the impact of realistic initial North American land conditions was to enhance precipitation in the upper Midwest and produce deficits in the Southeast. It was further found that 1) the 1 March atmospheric initial condition was the primary source of the ensemble mean precipitation response over the eastern United States in April (well beyond the limit of weather predictability), suggesting an influence on the initial state of the previous SST forcing and/or tropospheric/stratospheric coupling linked to an unusually persistent and cold polar vortex; and 2) stationary wave model experiments suggest that the SST-forced base state for April enhanced the amplitude of the NAO response compared to that of the climatological state, though the impact is modest and can be of either sign.

Statistical modeling of interannual shoreline change driven by North Atlantic climate variability spanning 2000-2014 in the Bay of Biscay

NASA Astrophysics Data System (ADS)

Robinet, A.; Castelle, B.; Idier, D.; Le Cozannet, G.; Déqué, M.; Charles, E.

2016-12-01

Modeling studies addressing daily to interannual coastal evolution typically relate shoreline change with waves, currents and sediment transport through complex processes and feedbacks. For wave-dominated environments, the main driver (waves) is controlled by the regional atmospheric circulation. Here a simple weather regime-driven shoreline model is developed for a 15-year shoreline dataset (2000-2014) collected at Truc Vert beach, Bay of Biscay, SW France. In all, 16 weather regimes (four per season) are considered. The centroids and occurrences are computed using the ERA-40 and ERA-Interim reanalyses, applying k-means and EOF methods to the anomalies of the 500-hPa geopotential height over the North Atlantic Basin. The weather regime-driven shoreline model explains 70% of the observed interannual shoreline variability. The application of a proven wave-driven equilibrium shoreline model to the same period shows that both models have similar skills at the interannual scale. Relation between the weather regimes and the wave climate in the Bay of Biscay is investigated and the primary weather regimes impacting shoreline change are identified. For instance, the winter zonal regime characterized by a strengthening of the pressure gradient between the Iceland low and the Azores high is associated with high-energy wave conditions and is found to drive an increase in the shoreline erosion rate. The study demonstrates the predictability of interannual shoreline change from a limited number of weather regimes, which opens new perspectives for shoreline change modeling and encourages long-term shoreline monitoring programs.

[Influence of weather in the incidence of acute myocardial infarction in Galicia (Spain)].

PubMed

Fernández-García, José Manuel; Dosil Díaz, Olga; Taboada Hidalgo, Juan José; Fernández, José Ramón; Sánchez-Santos, Luis

2015-08-07

To assess the interactions between weather and the impact of each individual meteorological parameters in the incidence of acute myocardial infarctions (AMI) in Galicia. Retrospective study analyzing the number of AMI diagnosed and transferred to the hospital by the Emergencies Sanitary System of Galicia between 2002 and 2009. We included patients with clinical and ECG findings of AMI. The correlation between 10-minute meteorological variables (temperature, humidity, pressure, accumulated rainfall and wind speed) recorded by MeteoGalicia and the incidence of AMI was assessed. A total of 4,717 AMI were registered (72.8% men, 27.2% women). No seasonal variations were found. No significant correlations were detected with regard to average daily temperature (P=.683) or wind speed (P=.895). Correlation between atmospheric pressure and incidence of AMI was significant (P<.005), as well as with the daily relative humidity average (P=.005). Our study showed a statistical significant association with atmospheric pressure and with the daily relative humidity average. Since the local conditions of weather are widely variable, future studies should establish the relationship between weather patterns (including combinations of meteorological parameters), rather than seasonal variations, and the incidence of AMI. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

Observational study of atmospheric surface layer and coastal weather in northern Qatar

NASA Astrophysics Data System (ADS)

Samanta, Dhrubajyoti; Sadr, Reza

2016-04-01

Atmospheric surface layer is the interaction medium between atmosphere and Earth's surface. Better understanding of its turbulence nature is essential in characterizing the local weather, climate variability and modeling of turbulent exchange processes. The importance of Middle East region, with its unique geographical, economical and weather condition is well recognized. However, high quality micrometeorological observational studies are rare in this region. Here we show experimental results from micrometeorological observations from an experimental site in the coastal region of Qatar during August-December 2015. Measurements of winds are obtained from three sonic anemometers installed on a 9 m tower placed at Al Ghariyah beach in northern Qatar (26.08 °N, 51.36 °E). Different surface layer characteristics is analyzed and compared with earlier studies in equivalent weather conditions. Monthly statistics of wind speed, wind direction, temperature, humidity and heat index are made from concurrent observations from sonic anemometer and weather station to explore variations with surface layer characteristics. The results also highlights potential impact of sea breeze circulation on local weather and atmospheric turbulence. The observed daily maximum temperature and heat index during morning period may be related to sea breeze circulations. Along with the operational micrometeorological observation system, a camera system and ultrasonic wave measurement system are installed recently in the site to study coastline development and nearshore wave dynamics. Overall, the complete observational set up is going to provide new insights about nearshore wind dynamics and wind-wave interaction in Qatar.

Ubiquitous Geo-Sensing for Context-Aware Analysis: Exploring Relationships between Environmental and Human Dynamics

PubMed Central

Sagl, Günther; Blaschke, Thomas; Beinat, Euro; Resch, Bernd

2012-01-01

Ubiquitous geo-sensing enables context-aware analyses of physical and social phenomena, i.e., analyzing one phenomenon in the context of another. Although such context-aware analysis can potentially enable a more holistic understanding of spatio-temporal processes, it is rarely documented in the scientific literature yet. In this paper we analyzed the collective human behavior in the context of the weather. We therefore explored the complex relationships between these two spatio-temporal phenomena to provide novel insights into the dynamics of urban systems. Aggregated mobile phone data, which served as a proxy for collective human behavior, was linked with the weather data from climate stations in the case study area, the city of Udine, Northern Italy. To identify and characterize potential patterns within the weather-human relationships, we developed a hybrid approach which integrates several spatio-temporal statistical analysis methods. Thereby we show that explanatory factor analysis, when applied to a number of meteorological variables, can be used to differentiate between normal and adverse weather conditions. Further, we measured the strength of the relationship between the ‘global’ adverse weather conditions and the spatially explicit effective variations in user-generated mobile network traffic for three distinct periods using the Maximal Information Coefficient (MIC). The analyses result in three spatially referenced maps of MICs which reveal interesting insights into collective human dynamics in the context of weather, but also initiate several new scientific challenges. PMID:23012571

Role of climatic factors on damage incidence by Dermolepida albohirtum (Coleoptera: Scarabaeidae), in Burdekin sugarcane fields, Australia.

PubMed

Horsfield, Andrew; Sallam, Mohamed Nader S; Drummond, Frank A; Williams, Don J; Schultz, Rod J

2008-04-01

Inconsistent control of Dermolepida albohirtum (Waterhouse) (Coleoptera: Scarabaeidae) in the period after the removal of organochlorines allowed us to study the impact of climatic variables and insecticide application on subsequent damage in sugarcane (Saccharum spp.). D. albohirtum damage records from the Invicta and Inkerman mill areas of the Burdekin district of North Queensland were compared with climatic averages during spring from 1989 to 2003. D. albohirtum damage demonstrated autocorrelation, indicating that the area of damage will increase from one year to the next if the grub is not effectively controlled. Insecticide use did not significantly impact on the area of damage between 1989 and 2003. Of the climatic variables evaluated, only pan evaporation was significant, and it was inversely related to the subsequent area of grub damage. Therefore, we suggest that weather conditions in spring impact on beetle emergence, feeding, and oviposition. Hot and dry spring weather may reduce beetle activity and ultimately the severity of crop damage, whereas wet and mild spring weather may favor beetle activity and an increase in the area of potential crop damage.

The 3D Mesonet Concept: Extending Networked Surface Meteorological Tower Observations Through Unmanned Aircraft Systems

NASA Astrophysics Data System (ADS)

Chilson, P. B.; Fiebrich, C. A.; Huck, R.; Grimsley, J.; Salazar-Cerreno, J.; Carson, K.; Jacob, J.

2017-12-01

Fixed monitoring sites, such as those in the US National Weather Service Automated Surface Observing System (ASOS) and the Oklahoma Mesonet provide valuable, high temporal resolution information about the atmosphere to forecasters and the general public. The Oklahoma Mesonet is comprised of a network of 120 surface sites providing a wide array of atmospheric measurements up to a height of 10 m with an update time of five minutes. The deployment of small unmanned aircraft to collect in-situ vertical measurements of the atmospheric state in conjunction with surface conditions has potential to significantly expand weather observation capabilities. This concept can enhance the safety of individuals and support commerce through improved observations and short-term forecasts of the weather and other environmental variables in the lower atmosphere. We report on a concept of adding the capability of collecting vertical atmospheric measurements (profiles) through the use of unmanned aerial systems (UAS) at remote Oklahoma sites deemed suitable for this application. While there are a number of other technologies currently available that can provide measurements of one or a few variables, the proposed UAS concept will be expandable and modular to accommodate several different sensor packages and provide accurate in-situ measurements in virtually all weather conditions. Such a system would facilitate off-site maintenance and calibration and would provide the ability to add new sensors as they are developed or as new requirements are identified. The small UAS must be capable of accommodating the weight of all sensor packages and have lighting, communication, and aircraft avoidance systems necessary to meet existing or future FAA regulations. The system must be able to operate unattended, which necessitates the inclusion of risk mitigation measures such as a detect and avoid radar and the ability to transmit and receive transponder signals. Moreover, the system should be able to assess local weather conditions (visibility, surface winds, and cloud height) and the integrity of the vehicle (system diagnostics, fuel level) before takeoff. We provide a notional concept of operations for a 3D Mesonet being considered, describe the technical configuration for one station in the network, and discuss plans for future development.

The influence of weather on migraine – are migraine attacks predictable?

PubMed Central

Hoffmann, Jan; Schirra, Tonio; Lo, Hendra; Neeb, Lars; Reuter, Uwe; Martus, Peter

2015-01-01

Objective The study aimed at elucidating a potential correlation between specific meteorological variables and the prevalence and intensity of migraine attacks as well as exploring a potential individual predictability of a migraine attack based on meteorological variables and their changes. Methods Attack prevalence and intensity of 100 migraineurs were correlated with atmospheric pressure, relative air humidity, and ambient temperature in 4-h intervals over 12 consecutive months. For each correlation, meteorological parameters at the time of the migraine attack as well as their variation within the preceding 24 h were analyzed. For migraineurs showing a positive correlation, logistic regression analysis was used to assess the predictability of a migraine attack based on meteorological information. Results In a subgroup of migraineurs, a significant weather sensitivity could be observed. In contrast, pooled analysis of all patients did not reveal a significant association. An individual prediction of a migraine attack based on meteorological data was not possible, mainly as a result of the small prevalence of attacks. Interpretation The results suggest that only a subgroup of migraineurs is sensitive to specific weather conditions. Our findings may provide an explanation as to why previous studies, which commonly rely on a pooled analysis, show inconclusive results. The lack of individual attack predictability indicates that the use of preventive measures based on meteorological conditions is not feasible. PMID:25642431

Seasonal Forecasts of Extreme Conditions for Wildland Fire Management in Alaska using NMME

NASA Astrophysics Data System (ADS)

Bhatt, U. S.; Bieniek, P.; Thoman, R.; York, A.; Ziel, R.

2016-12-01

The summer of 2015 was the second largest Alaska fire season since 1950 where approximately the land area of Massachusetts burned. The record fire year of 2004 resulted in 6.5 million acres burned and was costly from property loss (> 35M) and emergency personnel (> 17M). In addition to requiring significant resources, wildfire smoke impacts air quality in Alaska and downstream into North America. Fires in Alaska result from lightning strikes coupled with persistent (extreme) dry warm conditions in remote areas with limited fire management and the seasonal climate/weather determine the extent of the fire season in Alaska. Fire managers rely on weather/climate outlooks for allocating staff and resources from days to a season in advance. Though currently few tested products are available at the seasonal scale. Probabilistic forecasts of the expected seasonal climate/weather would aid tremendously in the planning process. Advanced knowledge of both lightning and fuel conditions would assist managers in planning resource allocation for the upcoming season. For fuel conditions, the Canadian Forest Fire Weather Index System (CFFWIS) has been used since 1992 because it better suits the Alaska fire regime than the standard US National Fire Danger Rating System (NFDRS). This CFFWIS is based on early afternoon values of 2-m air temperature, relative humidity, and 10-m winds and daily total precipitation. Extremes of these indices and the variables are used to calculate these indices will be defined in reference to fire weather for the boreal forest. The CFFWIS will be applied and evaluated for the NMME hindcasts. This study will evaluate the quality of the forecasts comparing the hindcast NMME CFFWIS to acres burned in Alaska. Spatial synoptic patterns in the NMME related to fire weather extremes will be constructed using self-organized maps and probabilities of occurrence will be evaluated against acres burned.

Formation and dynamics of hazardous convective weather events in Ukraine

NASA Astrophysics Data System (ADS)

Balabukh, Vera; Malytska, Liudmyla; Bazalieieva, Iuliana

2013-04-01

Atmospheric circulation change observed from the middle of the 70s of the twentieth century in the Northern Hemisphere resulted in changes of weather events formation conditions in different regions. The degree of influence of various factors on the formation of weather events also has changed. This eventually led to an increase in number and intensity of weather events and their variations in time and space. Destructions and damages associated with these events have increased recently and the biggest damages are mainly results of complex convective weather events: showers, hail, squall. Therefore, one of the main tasks of climatology is to study the mechanisms of change repeatability and intensity of these events. The paper considers the conditions of formation of hazardous convective weather phenomena (strong showers, hail, squalls, tornadoes) in Ukraine and their spatial and temporal variability during 1981 - 2010. Research of convection processes was based on daily radiosonde data for the warm season (May-September 1981 - 2010s), reanalysis ERA-Interim ECMWF data for 1989 - 2010 years , daily observations at 187 meteorological stations in Ukraine, as well as observations of the natural phenomena in other regions (different from the meteorological stations). Indices of atmospheric instability, the magnitude of the Convective Available Potential Energy (CAPE), the moisture, the height of the condensation and equilibrium level was used to quantify the intensity of convection. The criteria for the intensity of convection for Ukrainian territory were refined on the basis of these data. Features of the development of convection for various hazardous convective weather events were investigated and identified the necessary conditions for the occurrence of showers, hail, tornadoes and squall in Ukraine. Spatio-temporal variability of convection intensity in Ukraine, its regional characteristics and dynamics for the past 30 year was analyzed. Significant tendency to an increase the average temperature and moisture of the troposphere is observed during 90s of the twentieth century in Ukraine in the warm season that led to the growth of CAPE of the atmosphere, the speed of updrafts, raising the level of condensation and convection, and have increased the instability of the atmosphere. The number and intensity of strong showers, hail, squalls, tornadoes and the number of days with thunderstorms have increased due to such changes in Ukraine. The obtained quantitative criteria of convection will clarify their forecasting methodology, increase forecast accuracy and reduce the amount of uncertainty in predicting type of phenomena for various dangerous convective events.

Consequences of snowy winters on male mating strategies and reproduction in a mountain ungulate.

PubMed

Apollonio, Marco; Brivio, Francesca; Rossi, Iva; Bassano, Bruno; Grignolio, Stefano

2013-09-01

Alternative mating tactics (AMTs) are intrasexual variants in mating behaviour of several species ranging from arthropods to mammals. Male AMTs coexist between and within populations. In particular, male ungulates rarely adopt just one tactic throughout their lifetime. Tactics commonly change according to internal factors (age, body size, condition) and external conditions (weather, resources, predation, animal density). However, the influence of weather has not yet been investigated in upper vertebrates. Such influence may be relevant in species whose rutting period occurs late in fall or in winter, when environmental conditions and the snow cover in particular may vary considerably. We detected two AMTs in Alpine ibex (Capra ibex) males: older and full-grown males mainly adopted the tending tactic, while younger males usually pursued an alternative one (coursing tactic). Weather was found to influence the use of AMTs by males: in snowy mating seasons, the coursing tactic was no longer used due to difficulties in moving through deep snow. In snowy rutting periods, males appeared to delay or even avoid mating activities and a decrease of births was reported in the second part of the following birth season. Snow cover may have a negative effect on population dynamics by reducing the recruitment and on population genetic variability, as a consequence of poorer mating opportunities. Studies on factors affecting mating behaviour and leading to a reduced availability of mates and a decrease in female productivity are especially relevant in species, like Alpine ibex, whose genetic variability is low. Copyright © 2013 Elsevier B.V. All rights reserved.

A model for estimating seasonal trends of ammonia emission from cattle manure applied to grassland in the Netherlands

NASA Astrophysics Data System (ADS)

Huijsmans, J. F. M.; Vermeulen, G. D.; Hol, J. M. G.; Goedhart, P. W.

2018-01-01

Field data on ammonia emission after liquid cattle manure ('slurry') application to grassland were statistically analysed to reveal the effect of manure and field characteristics and of weather conditions in eight consecutive periods after manure application. Logistic regression models, modelling the emission expressed as a percentage of the ammonia still present at the start of each period as the response variable, were developed separately for broadcast spreading, narrow band application (trailing shoe) and shallow injection. Wind speed, temperature, soil type, total ammoniacal nitrogen (TAN) content and dry matter content of the manure, application rate and grass height were selected as significant explanatory variables. Their effects differed for each application method and among periods. Temperature and wind speed were generally the most important drivers for emission. The fitted regression models were used to reveal seasonal trends in NH3 emission employing historical meteorological data for the years 1991-2014. The overall average emission was higher in early and midsummer than in early spring and late summer. This seasonal trend was most pronounced for broadcast spreading followed by narrow band application, and was almost absent for shallow injection. However, due to the large variation in weather conditions, emission on a particular day in early spring can be higher than on a particular day in summer. The analysis further revealed that, in a specific scenario and depending on the application technique, emission could be reduced with 20-30% by restricting manure application to favourable days, i.e. with weather conditions with minimal emission levels.

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

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin

2016-04-01

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

Sensing Site-Specific Variability in Soil and Plant Phosphorus and Other Mineral Nutrients by X-Ray Fluorescence Spectrometry

USDA-ARS?s Scientific Manuscript database

Detection and rapid response to in-season changes of soil nutrient availability and plant needs with weather conditions and site-specific characteristics are essential to the optimal performance of an agronomic crop production system. With recent advances in material science, detector design and se...

Terrain Classification of Norwegian Slab Avalanche Accidents

ERIC Educational Resources Information Center

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

2016-01-01

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

Synthesis of User Needs for Arctic Sea Ice Predictions

NASA Astrophysics Data System (ADS)

Wiggins, H. V.; Turner-Bogren, E. J.; Sheffield Guy, L.

2017-12-01

Forecasting Arctic sea ice on sub-seasonal to seasonal scales in a changing Arctic is of interest to a diverse range of stakeholders. However, sea ice forecasting is still challenging due to high variability in weather and ocean conditions and limits to prediction capabilities; the science needs for observations and modeling are extensive. At a time of challenged science funding, one way to prioritize sea ice prediction efforts is to examine the information needs of various stakeholder groups. This poster will present a summary and synthesis of existing surveys, reports, and other literature that examines user needs for sea ice predictions. The synthesis will include lessons learned from the Sea Ice Prediction Network (a collaborative, multi-agency-funded project focused on seasonal Arctic sea ice predictions), the Sea Ice for Walrus Outlook (a resource for Alaska Native subsistence hunters and coastal communities, that provides reports on weather and sea ice conditions), and other efforts. The poster will specifically compare the scales and variables of sea ice forecasts currently available, as compared to what information is requested by various user groups.

Crash Frequency Analysis Using Hurdle Models with Random Effects Considering Short-Term Panel Data

PubMed Central

Chen, Feng; Ma, Xiaoxiang; Chen, Suren; Yang, Lin

2016-01-01

Random effect panel data hurdle models are established to research the daily crash frequency on a mountainous section of highway I-70 in Colorado. Road Weather Information System (RWIS) real-time traffic and weather and road surface conditions are merged into the models incorporating road characteristics. The random effect hurdle negative binomial (REHNB) model is developed to study the daily crash frequency along with three other competing models. The proposed model considers the serial correlation of observations, the unbalanced panel-data structure, and dominating zeroes. Based on several statistical tests, the REHNB model is identified as the most appropriate one among four candidate models for a typical mountainous highway. The results show that: (1) the presence of over-dispersion in the short-term crash frequency data is due to both excess zeros and unobserved heterogeneity in the crash data; and (2) the REHNB model is suitable for this type of data. Moreover, time-varying variables including weather conditions, road surface conditions and traffic conditions are found to play importation roles in crash frequency. Besides the methodological advancements, the proposed technology bears great potential for engineering applications to develop short-term crash frequency models by utilizing detailed data from field monitoring data such as RWIS, which is becoming more accessible around the world. PMID:27792209

Exceedance of PM10 and ozone concentration limits in Germany - Spatial variability and influence of climate

NASA Astrophysics Data System (ADS)

Heidenreich, Majana; Bernhofer, Christian

2014-05-01

High concentrations of particulate matter (PM) and ground-level ozone (O3) have negative impacts on human health, e.g., increased risk of respiratory disease, and the environment. European Union (EU) air policy and air quality standards led to continuously reduced air pollution problems in recent decades. Nevertheless, the limit values for PM10 (particles with diameter of 10 micrometers or less) and ozone - defined by the directive 2008/50/EC of the European Parliament - are still exceeded frequently. Poor air quality and the exceedance of limits result mainly from the combination of high emissions and unfavourable weather conditions. Datasets from German monitoring stations are used to describe the spatial and temporal variability of the exceedance of concentration limits for PM10 and ozone for the federal states of Germany. Time series are analysed for the period 2000-2012 for PM10 and for the period 1990-2012 for ozone. Furthermore, the influence of weather patterns on the exceedance of concentration limits on a regional scale was investigated. Here, the "objective weather types" of the German Weather Service were used. As expected, for most regions anticyclonic weather types (with a negative cyclonality index for the two levels 950 and 500 hPa) show a high frequency on exeedance days, both for PM10 and ozone. The results could contribute to estimate the future exceedance frequency of concentration limits and to develop possible countermeasures.

Accumulation mechanisms and the weathering of Antarctic equilibrated ordinary chondrites

NASA Astrophysics Data System (ADS)

Benoit, P. H.; Sears, D. W. G.

1999-06-01

Induced thermoluminescence (TL) is used to quantitatively evaluate the degree of weathering of meteorites found in Antarctica. We find a weak correlation between TL sensitivity and descriptions of weathering in hand specimens, the highly weathered meteorites having lower TL sensitivity than unweathered meteorites. Analysis of samples taken throughout large meteorites shows that the heterogeneity in TL sensitivity within meteorite finds is not large relative to the range exhibited by different weathered meteorites. The TL sensitivity values can be restored by minimal acid washing, suggesting the lower TL sensitivities of weathered meteorites reflects thin weathering rims on mineral grains or coating of these grains by iron oxides produced by hydration and oxidation of metal and sulfides. Small meteorites may tend to be more highly weathered than large meteorites at the Allan Hills ice fields. We find that meteorite fragments >150 g may take up to 300,000 years to reach the highest degrees of weathering, while meteorites <150 g require <40,000 years. However, at other fields, local environmental conditions and variability in terrestrial history are more important in determining weathering than size alone. Weathering correlates poorly with surface exposure duration, presumably because weathering occurs primarily during interglacial periods. The Allan Hills locality has served as a fairly stable surface over the last 100,000 years or so and has efficiently preserved both small and large meteorites. Meteorites from Lewis Cliff, however, have experienced extensive weathering, probably because of increased surface melt water from nearby outcrops. Meteorites from the Elephant Moraine locality tend to exhibit only minor degrees of weathering, but small meteorites are less weathered than large meteorites, which we suggest is due to the loss of small meteorites by aeolian transport.

Seasonality of Fire Weather Strongly Influences Fire Regimes in South Florida Savanna-Grassland Landscapes

PubMed Central

Platt, William J.; Orzell, Steve L.; Slocum, Matthew G.

2015-01-01

Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature). We used nonparametric cluster analyses of a 17-year (1993–2009) data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture) to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires) over a 13-year period with fire records (1997–2009). Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with timing of natural lightning ignitions should be useful as a basis for ecological fire management of humid savanna-grassland landscapes worldwide. PMID:25574667

Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

NASA Astrophysics Data System (ADS)

Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

2015-12-01

Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial variability of precipitation will help in the planning and management of the built environment more efficiently.

Seasonality of fire weather strongly influences fire regimes in South Florida savanna-grassland landscapes.

PubMed

Platt, William J; Orzell, Steve L; Slocum, Matthew G

2015-01-01

Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature). We used nonparametric cluster analyses of a 17-year (1993-2009) data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture) to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires) over a 13-year period with fire records (1997-2009). Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with timing of natural lightning ignitions should be useful as a basis for ecological fire management of humid savanna-grassland landscapes worldwide.

Hillslope chemical weathering across Paraná, Brazil: a data mining-GIS hybrid approach

USGS Publications Warehouse

Iwashita, Fabio; Friedel, Michael J.; Filho, Carlos Roberto de Souza; Fraser, Stephen J.

2011-01-01

Self-organizing map (SOM) and geographic information system (GIS) models were used to investigate the nonlinear relationships associated with geochemical weathering processes at local (~100 km2) and regional (~50,000 km2) scales. The data set consisted of 1) 22 B-horizon soil variables: P, C, pH, Al, total acidity, Ca, Mg, K, total cation exchange capacity, sum of exchangeable bases, base saturation, Cu, Zn, Fe, B, S, Mn, gammaspectrometry (total count, potassium, thorium, and uranium) and magnetic susceptibility measures; and 2) six topographic variables: elevation, slope, aspect, hydrological accumulated flux, horizontal curvature and vertical curvature. It is characterized at 304 locations from a quasi-regular grid spaced about 24 km across the state of Paraná. This data base was split into two subsets: one for analysis and modeling (274 samples) and the other for validation (30 samples) purposes. The self-organizing map and clustering methods were used to identify and classify the relations among solid-phase chemical element concentrations and GIS derived topographic models. The correlation between elevation and k-means clusters related the relative position inside hydrologic macro basins, which was interpreted as an expression of the weathering process reaching a steady-state condition at the regional scale. Locally, the chemical element concentrations were related to the vertical curvature representing concave–convex hillslope features, where concave hillslopes with convergent flux tends to be a reducing environment and convex hillslopes with divergent flux, oxidizing environments. Stochastic cross validation demonstrated that the SOM produced unbiased classifications and quantified the relative amount of uncertainty in predictions. This work strengthens the hypothesis that, at B-horizon steady-state conditions, the terrain morphometry were linked with the soil geochemical weathering in a two-way dependent process: the topographic relief was a factor on environmental geochemistry while chemical weathering was for terrain feature delineation.

Hillslope chemical weathering across Paraná, Brazil: A data mining-GIS hybrid approach

NASA Astrophysics Data System (ADS)

Iwashita, Fabio; Friedel, Michael J.; Filho, Carlos Roberto de Souza; Fraser, Stephen J.

2011-09-01

Self-organizing map (SOM) and geographic information system (GIS) models were used to investigate the nonlinear relationships associated with geochemical weathering processes at local (~100 km 2) and regional (~50,000 km 2) scales. The data set consisted of 1) 22 B-horizon soil variables: P, C, pH, Al, total acidity, Ca, Mg, K, total cation exchange capacity, sum of exchangeable bases, base saturation, Cu, Zn, Fe, B, S, Mn, gammaspectrometry (total count, potassium, thorium, and uranium) and magnetic susceptibility measures; and 2) six topographic variables: elevation, slope, aspect, hydrological accumulated flux, horizontal curvature and vertical curvature. It is characterized at 304 locations from a quasi-regular grid spaced about 24 km across the state of Paraná. This data base was split into two subsets: one for analysis and modeling (274 samples) and the other for validation (30 samples) purposes. The self-organizing map and clustering methods were used to identify and classify the relations among solid-phase chemical element concentrations and GIS derived topographic models. The correlation between elevation and k-means clusters related the relative position inside hydrologic macro basins, which was interpreted as an expression of the weathering process reaching a steady-state condition at the regional scale. Locally, the chemical element concentrations were related to the vertical curvature representing concave-convex hillslope features, where concave hillslopes with convergent flux tends to be a reducing environment and convex hillslopes with divergent flux, oxidizing environments. Stochastic cross validation demonstrated that the SOM produced unbiased classifications and quantified the relative amount of uncertainty in predictions. This work strengthens the hypothesis that, at B-horizon steady-state conditions, the terrain morphometry were linked with the soil geochemical weathering in a two-way dependent process: the topographic relief was a factor on environmental geochemistry while chemical weathering was for terrain feature delineation.

Climate change

USGS Publications Warehouse

Cronin, Thomas M.

2016-01-01

Climate change (including climate variability) refers to regional or global changes in mean climate state or in patterns of climate variability over decades to millions of years often identified using statistical methods and sometimes referred to as changes in long-term weather conditions (IPCC, 2012). Climate is influenced by changes in continent-ocean configurations due to plate tectonic processes, variations in Earth’s orbit, axial tilt and precession, atmospheric greenhouse gas (GHG) concentrations, solar variability, volcanism, internal variability resulting from interactions between the atmosphere, oceans and ice (glaciers, small ice caps, ice sheets, and sea ice), and anthropogenic activities such as greenhouse gas emissions and land use and their effects on carbon cycling.

CAL--ERDA program manual. [Building Design Language; LOADS, SYSTEMS, PLANT, ECONOMICS, REPORT, EXECUTIVE, CAL-ERDA

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

Hunn, B. D.; Diamond, S. C.; Bennett, G. A.

1977-10-01

A set of computer programs, called Cal-ERDA, is described that is capable of rapid and detailed analysis of energy consumption in buildings. A new user-oriented input language, named the Building Design Language (BDL), has been written to allow simplified manipulation of the many variables used to describe a building and its operation. This manual provides the user with information necessary to understand in detail the Cal-ERDA set of computer programs. The new computer programs described include: an EXECUTIVE Processor to create computer system control commands; a BDL Processor to analyze input instructions, execute computer system control commands, perform assignments andmore » data retrieval, and control the operation of the LOADS, SYSTEMS, PLANT, ECONOMICS, and REPORT programs; a LOADS analysis program that calculates peak (design) zone and hourly loads and the effect of the ambient weather conditions, the internal occupancy, lighting, and equipment within the building, as well as variations in the size, location, orientation, construction, walls, roofs, floors, fenestrations, attachments (awnings, balconies), and shape of a building; a Heating, Ventilating, and Air-Conditioning (HVAC) SYSTEMS analysis program capable of modeling the operation of HVAC components including fans, coils, economizers, humidifiers, etc.; 16 standard configurations and operated according to various temperature and humidity control schedules. A plant equipment program models the operation of boilers, chillers, electrical generation equipment (diesel or turbines), heat storage apparatus (chilled or heated water), and solar heating and/or cooling systems. An ECONOMIC analysis program calculates life-cycle costs. A REPORT program produces tables of user-selected variables and arranges them according to user-specified formats. A set of WEATHER ANALYSIS programs manipulates, summarizes and plots weather data. Libraries of weather data, schedule data, and building data were prepared.« less

Inter-Annual Variability in Stream Water Temperature, Microclimate and Heat Exchanges: a Comparison of Forest and Moorland Environments

NASA Astrophysics Data System (ADS)

Garner, G.; Hannah, D. M.; Malcolm, I.; Sadler, J. P.

2012-12-01

Riparian forest is recognised as important for moderating stream temperature variability and has the potential to mitigate thermal extremes in a changing climate. Previous research on the heat exchanges controlling water column temperature has often been short-term or seasonally-constrained, with the few multi-year studies limited to a maximum of two years. This study advances previous work by providing a longer-term perspective which allows assessment of inter-annual variability in stream temperature, microclimate and heat exchange dynamics between a semi-natural woodland and a moorland (no trees) reach of the Girnock Burn, a tributary of the Scottish Dee. Automatic weather stations collected 15-minute data over seven consecutive years, which to our knowledge is a unique data set in providing the longest term perspective to date on stream temperature, microclimate and heat exchange processes. Results for spring-summer indicate that the presence of a riparian canopy has a consistent effect between years in reducing the magnitude and variability of mean daily water column temperature and daily net energy totals. Differences in the magnitude and variability in net energy fluxes between the study reaches were driven primarily by fluctuations in net radiation and latent heat fluxes in response to between- and within-year variability in growth of the riparian forest canopy at the forest and prevailing weather conditions at both the forest and moorland. This research provides new insights on the inter-annual variability of stream energy exchanges for moorland and forested reaches under a wide range of climatological and hydrological conditions. The findings therefore provide a more robust process basis for modelling the impact of changes in forest practice and climate change on river thermal dynamics.

Breeding pond selection and movement patterns by eastern spadefoot toads (Scaphiopus holbrookii) in relation to weather and edaphic conditions.

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

Cathryn H. Greenberg; George W. Tanner

2004-08-31

Cathryn H. Greenberg and George W. Tanner. 2004. Breeding pond selection and movement patterns by eastern spadefoot toads (Scaphiopus holbrookii) in relation to weather and edaphic conditions. J. Herp. 38(4):569-577. Abstract: Eastern Spadefoot Toads (Scaphiopus holbrookii) require fish-free, isolated, ephemeral ponds for breeding but otherwise inhabit the surrounding uplands, commonly xeric longleaf pine (Pinus palustris) wiregrass (Aristida beyrichiana). Hence both pond and upland conditions can potentially affect their breeding biology, and population persistence. Hardwood invasion due to fire suppression in sandhills could alter upland and pond suitability by higher hardwood density and increased transpiration. In this paper we explore breedingmore » and neonatal emigration movements in relation to weather, hydrological conditions of ponds, and surrounding upland matrices. We use 9 years of data from continuous monitoring with drift fences and pitfall traps at 8 ephemeral ponds in 2 upland matrices: regularly-burned, savanna-like sandhills (n = 4), and hardwood-invaded sandhills (n = 4). Neither adult nor neonate captures differed between ponds within the 2 upland matrices, suggesting that they are tolerant of upland heterogeneity created by fire frequency. Explosive breeding occurred during 9 periods and in all seasons; adults were captured rarely otherwise. At a landscape-level rainfall, maximum change in barometric pressure, and an interaction between those 2 variables were significant predictors of explosive breeding. At a pond-level, rainfall, change in pond depth during the month prior to breeding, and days since a pond was last dry were significant predictors of adult captures. Transformation date, rather than weather, was associated with neonatal emigrations, which usually were complete within a week. Movement by first-captured adults and neonates was directional, but adult emigrations were apparently not always toward their origin. Our results suggest that Spadefoot Toads are highly adapted to breeding conditions and upland habitat heterogeneity created by weather patterns and fire frequency in Florida sandhills.« less

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

NASA Astrophysics Data System (ADS)

Suriano, Zachary J.

2018-02-01

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

The Predicted Influence of Climate Change on Lesser Prairie-Chicken Reproductive Parameters

PubMed Central

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, Dawn M.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001–2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter’s linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival. PMID:23874549

Testing the Role of Climate Change in Species Decline: Is the Eastern Quoll a Victim of a Change in the Weather?

PubMed Central

Fancourt, Bronwyn A.; Bateman, Brooke L.; VanDerWal, Jeremy; Nicol, Stewart C.; Hawkins, Clare E.; Jones, Menna E.; Johnson, Christopher N.

2015-01-01

To conserve a declining species we first need to diagnose the causes of decline. This is one of the most challenging tasks faced by conservation practitioners. In this study, we used temporally explicit species distribution models (SDMs) to test whether shifting weather can explain the recent decline of a marsupial carnivore, the eastern quoll (Dasyurus viverrinus). We developed an SDM using weather variables matched to occurrence records of the eastern quoll over the last 60 years, and used the model to reconstruct variation through time in the distribution of climatically suitable range for the species. The weather model produced a meaningful prediction of the known distribution of the species. Abundance of quolls, indexed by transect counts, was positively related to the modelled area of suitable habitat between 1990 and 2004. In particular, a sharp decline in abundance from 2001 to 2003 coincided with a sustained period of unsuitable weather over much of the species’ distribution. Since 2004, abundance has not recovered despite a return to suitable weather conditions, and abundance and area of suitable habitat have been uncorrelated. We suggest that fluctuations in weather account for the species’ recent decline, but other unrelated factors have suppressed recovery. PMID:26106887

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

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

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

Optimum space shuttle launch times relative to natural environment

NASA Technical Reports Server (NTRS)

King, R. L.

1977-01-01

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

Mining key elements for severe convection prediction based on CNN

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

The Effects of Various Weather Conditions as a Potential Ischemic Stroke Trigger in Dogs

PubMed Central

Silver, Gena M.

2017-01-01

Stroke is the fifth leading cause of death in the United States, and is the leading cause of serious, long-term disability worldwide. There are at least 795,000 new or recurrent strokes each year, and approximately 85% of all stroke occurrences are ischemic. Unfortunately, companion animals are also at risk for ischemic stroke. Although the exact incidence of ischemic stroke in companion animals is unknown, some studies, and the veterinary information network (VIN), report that approximately 3% of neurological case referrals are due to a stroke. There is a long list of predisposing factors associated with the risk of ischemic stroke in both humans and canines; however, these factors do not explain why a stroke happens at a particular time on a particular day. Our understanding of these potential stroke “triggers” is limited, and the effect of transient environmental exposures may be one such “trigger”. The present study investigated the extent to which the natural occurrence of canine ischemic stroke was related to the weather conditions in the time-period immediately preceding the onset of stroke. The results of the present study demonstrated that the change in weather conditions could be a potential stroke trigger, with the strokes evaluated occurring after periods of rapid, large fluctuations in weather conditions. There are currently no epidemiological data on the seasonal variability of ischemic stroke in dogs, and determining whether canine stroke parallels human stroke would further validate the use of companion dogs as an appropriate naturally occurring model. PMID:29144407

Use of weather data and remote sensing to predict the geographic and seasonal distribution of Phlebotomus papatasi in southwest Asia.

PubMed

Cross, E R; Newcomb, W W; Tucker, C J

1996-05-01

Sandfly fever and leishmaniasis were major causes of infectious disease morbidity among military personnel deployed to the Middle East during World War II. Recently, leishmaniasis has been reported in the United Nations Multinational Forces and Observers in the Sinai. Despite these indications of endemicity, no cases of sandfly fever and only 31 cases of leishmaniasis have been identified among U.S. veterans of the Persian Gulf War. The distribution in the Persian Gulf of the vector, Phlebotomus papatasi, is thought to be highly dependent on environmental conditions, especially temperature and relative humidity. A computer model was developed using the occurrence of P. papatasi as the dependent variable and weather data as the independent variables. The results of this model indicated that the greatest sand fly activity and thus the highest risk of sandfly fever and leishmania infections occurred during the spring/summer months before U.S. troops were deployed to the Persian Gulf. Because the weather model produced probability of occurrence information for locations of the weather stations only, normalized difference vegetation index (NDVI) levels from remotely sensed Advanced Very High Resolution Radiometer satellites were determined for each weather station. From the results of the frequency of NDVI levels by probability of occurrence, the range of NDVI levels for presence of the vector was determined. The computer then identified all pixels within the NDVI range indicated and produced a computer-generated map of the probable distribution of P. papatasi. The resulting map expanded the analysis to areas where there were no weather stations and from which no information was reported in the literature, identifying these areas as having either a high or low probability of vector occurrence.

Impact of weather factors on hand, foot and mouth disease, and its role in short-term incidence trend forecast in Huainan City, Anhui Province.

PubMed

Zhao, Desheng; Wang, Lulu; Cheng, Jian; Xu, Jun; Xu, Zhiwei; Xie, Mingyu; Yang, Huihui; Li, Kesheng; Wen, Lingying; Wang, Xu; Zhang, Heng; Wang, Shusi; Su, Hong

2017-03-01

Hand, foot, and mouth disease (HFMD) is one of the most common communicable diseases in China, and current climate change had been recognized as a significant contributor. Nevertheless, no reliable models have been put forward to predict the dynamics of HFMD cases based on short-term weather variations. The present study aimed to examine the association between weather factors and HFMD, and to explore the accuracy of seasonal auto-regressive integrated moving average (SARIMA) model with local weather conditions in forecasting HFMD. Weather and HFMD data from 2009 to 2014 in Huainan, China, were used. Poisson regression model combined with a distributed lag non-linear model (DLNM) was applied to examine the relationship between weather factors and HFMD. The forecasting model for HFMD was performed by using the SARIMA model. The results showed that temperature rise was significantly associated with an elevated risk of HFMD. Yet, no correlations between relative humidity, barometric pressure and rainfall, and HFMD were observed. SARIMA models with temperature variable fitted HFMD data better than the model without it (sR 2 increased, while the BIC decreased), and the SARIMA (0, 1, 1)(0, 1, 0) 52 offered the best fit for HFMD data. In addition, compared with females and nursery children, males and scattered children may be more suitable for using SARIMA model to predict the number of HFMD cases and it has high precision. In conclusion, high temperature could increase the risk of contracting HFMD. SARIMA model with temperature variable can effectively improve its forecast accuracy, which can provide valuable information for the policy makers and public health to construct a best-fitting model and optimize HFMD prevention.

Impact of weather factors on hand, foot and mouth disease, and its role in short-term incidence trend forecast in Huainan City, Anhui Province

NASA Astrophysics Data System (ADS)

Zhao, Desheng; Wang, Lulu; Cheng, Jian; Xu, Jun; Xu, Zhiwei; Xie, Mingyu; Yang, Huihui; Li, Kesheng; Wen, Lingying; Wang, Xu; Zhang, Heng; Wang, Shusi; Su, Hong

2017-03-01

Hand, foot, and mouth disease (HFMD) is one of the most common communicable diseases in China, and current climate change had been recognized as a significant contributor. Nevertheless, no reliable models have been put forward to predict the dynamics of HFMD cases based on short-term weather variations. The present study aimed to examine the association between weather factors and HFMD, and to explore the accuracy of seasonal auto-regressive integrated moving average (SARIMA) model with local weather conditions in forecasting HFMD. Weather and HFMD data from 2009 to 2014 in Huainan, China, were used. Poisson regression model combined with a distributed lag non-linear model (DLNM) was applied to examine the relationship between weather factors and HFMD. The forecasting model for HFMD was performed by using the SARIMA model. The results showed that temperature rise was significantly associated with an elevated risk of HFMD. Yet, no correlations between relative humidity, barometric pressure and rainfall, and HFMD were observed. SARIMA models with temperature variable fitted HFMD data better than the model without it (s R 2 increased, while the BIC decreased), and the SARIMA (0, 1, 1)(0, 1, 0)52 offered the best fit for HFMD data. In addition, compared with females and nursery children, males and scattered children may be more suitable for using SARIMA model to predict the number of HFMD cases and it has high precision. In conclusion, high temperature could increase the risk of contracting HFMD. SARIMA model with temperature variable can effectively improve its forecast accuracy, which can provide valuable information for the policy makers and public health to construct a best-fitting model and optimize HFMD prevention.

Weather variability and the incidence of cryptosporidiosis: comparison of time series poisson regression and SARIMA models.

PubMed

Hu, Wenbiao; Tong, Shilu; Mengersen, Kerrie; Connell, Des

2007-09-01

Few studies have examined the relationship between weather variables and cryptosporidiosis in Australia. This paper examines the potential impact of weather variability on the transmission of cryptosporidiosis and explores the possibility of developing an empirical forecast system. Data on weather variables, notified cryptosporidiosis cases, and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics for the period of January 1, 1996-December 31, 2004, respectively. Time series Poisson regression and seasonal auto-regression integrated moving average (SARIMA) models were performed to examine the potential impact of weather variability on the transmission of cryptosporidiosis. Both the time series Poisson regression and SARIMA models show that seasonal and monthly maximum temperature at a prior moving average of 1 and 3 months were significantly associated with cryptosporidiosis disease. It suggests that there may be 50 more cases a year for an increase of 1 degrees C maximum temperature on average in Brisbane. Model assessments indicated that the SARIMA model had better predictive ability than the Poisson regression model (SARIMA: root mean square error (RMSE): 0.40, Akaike information criterion (AIC): -12.53; Poisson regression: RMSE: 0.54, AIC: -2.84). Furthermore, the analysis of residuals shows that the time series Poisson regression appeared to violate a modeling assumption, in that residual autocorrelation persisted. The results of this study suggest that weather variability (particularly maximum temperature) may have played a significant role in the transmission of cryptosporidiosis. A SARIMA model may be a better predictive model than a Poisson regression model in the assessment of the relationship between weather variability and the incidence of cryptosporidiosis.

A panel study in congestive heart failure to estimate the short-term effects from personal factors and environmental conditions on oxygen saturation and pulse rate.

PubMed

Goldberg, M S; Giannetti, N; Burnett, R T; Mayo, N E; Valois, M-F; Brophy, J M

2008-10-01

Recent studies suggest that persons with congestive heart failure (CHF) may be at higher risk for short-term effects of air pollution. This daily diary panel study in Montreal, Quebec, was carried out to determine whether oxygen saturation and pulse rate were associated with selected personal factors, weather conditions and air pollution. Thirty-one subjects with CHF participated in this study in 2002 and 2003. Over a 2-month period, the investigators measured their oxygen saturation, pulse rate, weight and temperature each morning and recorded these and other data in a daily diary. Air pollution and weather conditions were obtained from fixed-site monitoring stations. The study made use of mixed regression models, adjusting for within-subject serial correlation and temporal trends, to determine the association between oxygen saturation and pulse rate and personal and environmental variables. Depending on the model, we accounted for the effects of a variety of personal variables (eg, body temperature, salt consumption) as well as nitrogen dioxide (NO2), ozone, maximum temperature and change in barometric pressure at 8:00 from the previous day. In multivariable analyses, the study found that oxygen saturation was reduced when subjects reported that they were ill, consumed salt, or drank liquids on the previous day and had higher body temperatures on the concurrent day (only the latter was statistically significant). Relative humidity and decreased atmospheric pressure from the previous day were associated with oxygen saturation. In univariate analyses, there was negative associations with concentrations of fine particulates, ozone, and sulphur dioxide (SO2), but only SO2 was significant after adjustment for the effects of weather. For pulse rate, no associations were found for the personal variables and in univariate analyses the study found positive associations with NO(2), fine particulates (aerodynamic diameter of 2.5 microm or under, PM(2.5)), SO2, and maximum temperature, although only the latter two were significant after adjustment for environmental effects. The findings from the present investigation suggest that personal and environmental conditions affect intermediate physiological parameters that may affect the health of CHF patients.

Reconstruction of regional climate and climate change in past decades

NASA Astrophysics Data System (ADS)

von Storch, H.; Feser, F.; Weisse, R.; Zahn, M.

2009-12-01

Regional climate models, which are constrained by large scale information (spectral nudging) provided by re-analyses, allow for the construction of a mostly homogeneous description of regional weather statistics since about 1950. The potential of this approach has been demonstrated for Northern Europe. That data set, named CoastDat, does not only contain hourly data on atmospheric variables, in particular wind, but also on marine weather, i.e., short term water level, current and sea state variations. Another example is the multi-decadal variability of Polar Lows in the subarctic waters. The utility of such data sets is broad, from risk assessments related to coastal wind and wave conditions, assessment of determining the causes for regional climate change, a-posteriori analysis of the efficiency of environmental legislation (example: lead). In the paper, the methodology is outlined, examples are provided and the utility of the product discussed.

Uncertainty quantification in downscaling procedures for effective decisions in energy systems

NASA Astrophysics Data System (ADS)

Constantinescu, E. M.

2010-12-01

Weather is a major driver both of energy supply and demand, and with the massive adoption of renewable energy sources and changing economic and producer-consumer paradigms, the management of the next-generation energy systems is becoming ever more challenging. The operational and planning decisions in energy systems are guided by efficiency and reliability, and therefore a central role in these decisions will be played by the ability to obtain weather condition forecasts with accurate uncertainty estimates. The appropriate temporal and spatial resolutions needed for effective decision-making, be it operational or planning, is not clear. It is arguably certain however, that such temporal scales as hourly variations of temperature or wind conditions and ramp events are essential in this process. Planning activities involve decade or decades-long projections of weather. One sensible way to achieve this is to embed regional weather models in a global climate system. This strategy acts as a downscaling procedure. Uncertainty modeling techniques must be developed in order to quantify and minimize forecast errors as well as target variables that impact the decision-making process the most. We discuss the challenges of obtaining a realistic uncertainty quantification estimate using mathematical algorithms based on scalable matrix-free computations and physics-based statistical models. The process of making decisions for energy management systems based on future weather scenarios is a very complex problem. We shall focus on the challenges in generating wind power predictions based on regional weather predictions, and discuss the implications of making the common assumptions about the uncertainty models.

A Geosynchronous Lidar System for Atmospheric Winds and Moisture Measurements

NASA Technical Reports Server (NTRS)

Emmitt, G. D.

2001-01-01

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

Correlation of spring spore concentrations and meteorological conditions in Tulsa, Oklahoma

NASA Astrophysics Data System (ADS)

Troutt, C.; Levetin, E.

Different spore types are abundant in the atmosphere depending on the weather conditions. Ascospores generally follow precipitation, while spore types such as Alternaria and Cladosporium are abundant in dry conditions. This project attempted to correlate fungal spore concentrations with meteorological data from Tulsa, Oklahoma during May 1998 and May 1999. Air samples were collected and analyzed by the 12-traverse method. The spore types included were Cladosporium, Alternaria, Epicoccum, Curvularia, Pithomyces, Drechslera, smut spores, ascospores, basidiospores, and other spores. Weather variables included precipitation levels, temperature, dew point, air pressure, wind speed, wind direction and wind gusts. There were over 242.57 mm of rainfall in May 1999 and only 64.01 mm in May 1998. The most abundant spore types during May 1998 and May 1999 were Cladosporium, ascospores, and basidiospores. Results showed that there were significant differences in the dry-air spora between May 1998 and May 1999. There were twice as many Cladosporium in May 1998 as in May 1999; both ascospores and basidiospores showed little change. Multiple regression analysis was used to determine which meteorological variables influenced spore concentrations. Results showed that there was no single model for all spore types. Different combinations of factors were predictors of concentration for the various fungi examined; however, temperature and dew point seemed to be the most important meteorological factors.

Comparison of Microclimate Simulated weather data to ASHRAE Clear Sky Model and Measured Data

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

Bhandari, Mahabir S.

In anticipation of emerging global urbanization and its impact on microclimate, a need exists to better understand and quantify microclimate effects on building energy use. Satisfaction of this need will require coordinated research of microclimate impacts on and from “human systems.” The Urban Microclimate and Energy Tool (Urban-MET) project seeks to address this need by quantifying and analyzing the relationships among climatic conditions, urban morphology, land cover, and energy use; and using these relationships to inform energy-efficient urban development and planning. Initial research will focus on analysis of measured and modeled energy efficiency of various building types in selected urbanmore » areas and temporal variations in energy use for different urban morphologies under different microclimatic conditions. In this report, we analyze the differences between microclimate weather data sets for the Oak Ridge National Laboratory campus produced by ENVI-met and Weather Research Forecast (WRF) models, the ASHRAE clear sky which defines the maximum amounts of solar radiation that can be expected, and measured data from a weather station on campus. Errors with climate variables and their impact on building energy consumption will be shown for the microclimate simulations to help prioritize future improvement for use in microclimate simulation impacts to energy use of buildings.« less

Influence of Anthropogenic Climate Change on Planetary Wave Resonance and Extreme Weather Events

PubMed Central

Mann, Michael E.; Rahmstorf, Stefan; Kornhuber, Kai; Steinman, Byron A.; Miller, Sonya K.; Coumou, Dim

2017-01-01

Persistent episodes of extreme weather in the Northern Hemisphere summer have been shown to be associated with the presence of high-amplitude quasi-stationary atmospheric Rossby waves within a particular wavelength range (zonal wavenumber 6–8). The underlying mechanistic relationship involves the phenomenon of quasi-resonant amplification (QRA) of synoptic-scale waves with that wavenumber range becoming trapped within an effective mid-latitude atmospheric waveguide. Recent work suggests an increase in recent decades in the occurrence of QRA-favorable conditions and associated extreme weather, possibly linked to amplified Arctic warming and thus a climate change influence. Here, we isolate a specific fingerprint in the zonal mean surface temperature profile that is associated with QRA-favorable conditions. State-of-the-art (“CMIP5”) historical climate model simulations subject to anthropogenic forcing display an increase in the projection of this fingerprint that is mirrored in multiple observational surface temperature datasets. Both the models and observations suggest this signal has only recently emerged from the background noise of natural variability. PMID:28345645

Using a Six Sigma Fishbone Analysis Approach To Evaluate the Effect of Extreme Weather Events on Salmonella Positives in Young Chicken Slaughter Establishments.

PubMed

Linville, John W; Schumann, Douglas; Aston, Christopher; Defibaugh-Chavez, Stephanie; Seebohm, Scott; Touhey, Lucy

2016-12-01

A six sigma fishbone analysis approach was used to develop a machine learning model in SAS, Version 9.4, by using stepwise linear regression. The model evaluated the effect of a wide variety of variables, including slaughter establishment operational measures, normal (30-year average) weather, and extreme weather events on the rate of Salmonella -positive carcasses in young chicken slaughter establishments. Food Safety and Inspection Service (FSIS) verification carcass sampling data, as well as corresponding data from the National Oceanographic and Atmospheric Administration and the Federal Emergency Management Agency, from September 2011 through April 2015, were included in the model. The results of the modeling show that in addition to basic establishment operations, normal weather patterns, differences from normal and disaster events, including time lag weather and disaster variables, played a role in explaining the Salmonella percent positive that varied by slaughter volume quartile. Findings show that weather and disaster events should be considered as explanatory variables when assessing pathogen-related prevalence analysis or research and slaughter operational controls. The apparent significance of time lag weather variables suggested that at least some of the impact on Salmonella rates occurred after the weather events, which may offer opportunities for FSIS or the poultry industry to implement interventions to mitigate those effects.

NOAA Climate Information and Tools for Decision Support Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

2013-12-01

NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to provision of information that will help guide long-term preparedness for severe weather events and extreme conditions as well as climate variability and change GFCS recently summarized examples of existing initiatives to advance provision of climate services in the 2012 publication Climate ExChange. In this publication, NWS introduced the new Local Climate Analysis Tool (LCAT), a tool that is used to conduct local climate studies that are needed to create efficient and reliable guidance for DSS. LCAT allows for analyzing trends in local climate variables and identifying local impacts of climate variability (e.g., ENSO) on weather and water conditions. In addition to LCAT, NWS, working in partnership with the North East Regional Climate center, released xmACIS version 2, a climate data mining tool, for NWS field operations. During this talk we will demonstrate LCAT and xmACIS as well as outline several examples of their application to DSS and its potential use for achieving GFCS goals. The examples include LCAT-based temperature analysis for energy decisions, guidance on weather and water events leading to increased algal blooms and red tide months in advance, local climate sensitivities to droughts, probabilities of hot/cold conditions and their potential impacts on agriculture and fish kills or fish stress.

Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

NASA Astrophysics Data System (ADS)

B, Potgieter A.; D, Rodriguez; B, Power; J, Mclean; P, Davis

2014-02-01

Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (~1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible and 90m for thermal) satellite platforms. Results showed that spatial variations in crop yield were related to a satellite derived canopy stress index (CSIsat) and a moisture stress index (MSIsat). A weather station level canopy stress index (CSIws) calculated at midday was correlated to the CSIsat at late morning. In addition, a strong linear relationship was observed between EVI and LST at point scale throughout the crop growth period. Differences were smallest at anthesis when the canopy closure was highest. This suggests that LST imagery data around flowering could be used to calculate crop stress over large areas of the crop. The harvested yield was related (R2 = 0.67) to CSIsat using a fix date across all fields. This relationship improved (R2 = 0.92) using both indices from all five dates across all fields during the crop growth period. Here we successfully showed that satellite derived crop attributes (CSIsat and MSIsat) can account for most of the variability in final crop yield and that they can be used to predict crop yield at field scales. Applications of these results could enhance the ability of producers to hedge their financial on -farm crop production losses due to in-season water stress by taking crop insurance. This is likely to further improve their adaptive capacity and thus strengthening the long-term viability of the industry domestically and elsewhere.

Agricultural losses related to frost events: use of the 850 hPa level temperature as an explanatory variable of the damage cost

NASA Astrophysics Data System (ADS)

Papagiannaki, K.; Lagouvardos, K.; Kotroni, V.; Papagiannakis, G.

2014-01-01

The objective of this study is to analyze frost damaging events in agriculture, by examining the relationship between the daily minimum temperature at the lower atmosphere (at the pressure level of 850 hPa) and crop production losses. Furthermore, the study suggests a methodological approach for estimating agriculture risk due to frost events, with the aim to estimate the short-term probability and magnitude of frost-related financial losses for different levels of 850 hPa temperature. Compared with near surface temperature forecasts, temperature forecast at the level of 850 hPa is less influenced by varying weather conditions, as well as by local topographical features, thus it constitutes a more consistent indicator of the forthcoming weather conditions. The analysis of the daily monetary compensations for insured crop losses caused by weather events in Greece, during the period 1999-2011, shows that frost is the major meteorological phenomenon with adverse effects on crop productivity in the largest part of the country. Two regions of different geographical latitude are further examined, to account for the differences in the temperature ranges developed within their ecological environment. Using a series of linear and logistic regressions, we found that minimum temperature (at 850 hPa level), grouped in three categories according to its magnitude, and seasonality are significant variables when trying to explain crop damage costs, as well as to predict and quantify the likelihood and magnitude of frost damaging events.

Agricultural losses related to frost events: use of the 850 hPa level temperature as an explanatory variable of the damage cost

NASA Astrophysics Data System (ADS)

Papagiannaki, K.; Lagouvardos, K.; Kotroni, V.; Papagiannakis, G.

2014-09-01

The objective of this study is the analysis of damaging frost events in agriculture, by examining the relationship between the daily minimum temperature in the lower atmosphere (at an isobaric level of 850 hPa) and crop production losses. Furthermore, the study suggests a methodological approach for estimating agriculture risk due to frost events, with the aim of estimating the short-term probability and magnitude of frost-related financial losses for different levels of 850 hPa temperature. Compared with near-surface temperature forecasts, temperature forecasts at the level of 850 hPa are less influenced by varying weather conditions or by local topographical features; thus, they constitute a more consistent indicator of the forthcoming weather conditions. The analysis of the daily monetary compensations for insured crop losses caused by weather events in Greece shows that, during the period 1999-2011, frost caused more damage to crop production than any other meteorological phenomenon. Two regions of different geographical latitudes are examined further, to account for the differences in the temperature ranges developed within their ecological environment. Using a series of linear and logistic regressions, we found that minimum temperature (at an 850 hPa level), grouped into three categories according to its magnitude, and seasonality, are significant variables when trying to explain crop damage costs, as well as to predict and quantify the likelihood and magnitude of damaging frost events.

Remotely Sensed Environmental Conditions and Malaria Mortality in Three Malaria Endemic Regions in Western Kenya.

PubMed

Sewe, Maquins Odhiambo; Ahlm, Clas; Rocklöv, Joacim

2016-01-01

Malaria is an important cause of morbidity and mortality in malaria endemic countries. The malaria mosquito vectors depend on environmental conditions, such as temperature and rainfall, for reproduction and survival. To investigate the potential for weather driven early warning systems to prevent disease occurrence, the disease relationship to weather conditions need to be carefully investigated. Where meteorological observations are scarce, satellite derived products provide new opportunities to study the disease patterns depending on remotely sensed variables. In this study, we explored the lagged association of Normalized Difference Vegetation Index (NVDI), day Land Surface Temperature (LST) and precipitation on malaria mortality in three areas in Western Kenya. The lagged effect of each environmental variable on weekly malaria mortality was modeled using a Distributed Lag Non Linear Modeling approach. For each variable we constructed a natural spline basis with 3 degrees of freedom for both the lag dimension and the variable. Lag periods up to 12 weeks were considered. The effect of day LST varied between the areas with longer lags. In all the three areas, malaria mortality was associated with precipitation. The risk increased with increasing weekly total precipitation above 20 mm and peaking at 80 mm. The NDVI threshold for increased mortality risk was between 0.3 and 0.4 at shorter lags. This study identified lag patterns and association of remote- sensing environmental factors and malaria mortality in three malaria endemic regions in Western Kenya. Our results show that rainfall has the most consistent predictive pattern to malaria transmission in the endemic study area. Results highlight a potential for development of locally based early warning forecasts that could potentially reduce the disease burden by enabling timely control actions.

Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin

NASA Astrophysics Data System (ADS)

Forsythe, N.; Fowler, H. J.; Blenkinsop, S.; Burton, A.; Kilsby, C. G.; Archer, D. R.; Harpham, C.; Hashmi, M. Z.

2014-09-01

Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961-1990) demonstrated the models' skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961-1990) and future (2071-2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed ‘future' weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region.

Climate and weather influences on spatial temporal patterns of mountain pine beetle populations in Washington and Oregon.

PubMed

Preisler, Haiganoush K; Hicke, Jeffrey A; Ager, Alan A; Hayes, Jane L

2012-11-01

Widespread outbreaks of mountain pine beetle in North America have drawn the attention of scientists, forest managers, and the public. There is strong evidence that climate change has contributed to the extent and severity of recent outbreaks. Scientists are interested in quantifying relationships between bark beetle population dynamics and trends in climate. Process models that simulate climate suitability for mountain pine beetle outbreaks have advanced our understanding of beetle population dynamics; however, there are few studies that have assessed their accuracy across multiple outbreaks or at larger spatial scales. This study used the observed number of trees killed by mountain pine beetles per square kilometer in Oregon and Washington, USA, over the past three decades to quantify and assess the influence of climate and weather variables on beetle activity over longer time periods and larger scales than previously studied. Influences of temperature and precipitation in addition to process model output variables were assessed at annual and climatological time scales. The statistical analysis showed that new attacks are more likely to occur at locations with climatological mean August temperatures >15 degrees C. After controlling for beetle pressure, the variables with the largest effect on the odds of an outbreak exceeding a certain size were minimum winter temperature (positive relationship) and drought conditions in current and previous years. Precipitation levels in the year prior to the outbreak had a positive effect, possibly an indication of the influence of this driver on brood size. Two-year cumulative precipitation had a negative effect, a possible indication of the influence of drought on tree stress. Among the process model variables, cold tolerance was the strongest indicator of an outbreak increasing to epidemic size. A weather suitability index developed from the regression analysis indicated a 2.5x increase in the odds of outbreak at locations with highly suitable weather vs. locations with low suitability. The models were useful for estimating expected amounts of damage (total area with outbreaks) and for quantifying the contribution of climate to total damage. Overall, the results confirm the importance of climate and weather on the spatial expansion of bark beetle outbreaks over time.

Impact of Entomophaga maimaiga (Entomophthorales: Entomophthoraceae) on outbreak gypsy moth populations (Lepidoptera: Erebidae): the role of weather.

PubMed

Reilly, James R; Hajek, Ann E; Liebhold, Andrew M; Plymale, Ruth

2014-06-01

The fungal pathogen Entomophaga maimaiga Humber, Shimazu, and Soper is prevalent in gypsy moth [Lymantria dispar (L.)] populations throughout North America. To understand how weather-related variables influence gypsy moth-E. maimaiga interactions in the field, we measured fungal infection rates at 12 sites in central Pennsylvania over 3 yr, concurrently measuring rainfall, soil moisture, humidity, and temperature. Fungal mortality was assessed using both field-collected larvae and laboratory-reared larvae caged on the forest floor. We found significant positive effects of moisture-related variables (rainfall, soil moisture, and relative humidity) on mortality due to fungal infection in both data sets, and significant negative effects of temperature on the mortality of field-collected larvae. Lack of a clear temperature relationship with the mortality of caged larvae may be attributable to differential initiation of infection by resting spores and conidia or to microclimate effects. These relationships may be helpful in understanding how gypsy moth dynamics vary across space and time, and in forecasting how the gypsy moth and fungus will interact as they move into warmer or drier areas, or new weather conditions occur due to climate change.

A new precipitation and meteorological drought climatology based on weather patterns

NASA Astrophysics Data System (ADS)

Richardson, D.; Fowler, H. J.; Kilsby, C. G.; Neal, R.

2017-12-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterise the broad-scale atmospheric circulation over a given region. An analysis of regional UK precipitation and meteorological drought climatology with respect to a set of objectively defined weather patterns is presented. This classification system, introduced last year, is currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. The classification consists of 30 daily patterns derived from North Atlantic Ocean and European mean sea level pressure data. Clustering these 30 patterns yields another set of eight patterns that are intended for use in longer-range applications. Weather pattern definitions and daily occurrences are mapped to the commonly-used Lamb Weather Types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Drought index series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for different drought index thresholds, representing dry, wet and drought conditions. The set of 30 weather patterns is shown to be adequate for precipitation-based analyses in the UK, although the smaller set of clustered patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in the context of precipitation studies. Weather patterns associated with drought over the different UK regions are identified. This has potential forecasting application - if a model (e.g. a global seasonal forecast model) can predict weather pattern occurrences then regional drought outlooks may be derived from the forecasted weather patterns.

Atmosphere-Ionosphere Coupling due to Atmospheric Tides (Julius Bartels Medal Lecture)

NASA Astrophysics Data System (ADS)

Forbes, Jeffrey M.

2016-04-01

Within the last decade, a new realization has arrived on the scene of ionosphere-thermosphere (IT) science: terrestrial weather significantly influences space weather. The aspect of space weather referred to here consists of electron density variability that translates to uncertainties in navigation and communications systems, and neutral density variability that translates to uncertainties in orbital and reentry predictions. In the present context "terrestrial weather" primarily refers to the meteorological conditions that determine the spatial-temporal distribution of tropospheric water vapor and latent heating associated with tropical convection, and the middle atmosphere disturbances associated with sudden stratosphere warmings. The net effect of these processes is a spatially- and temporally-evolving spectrum of waves (gravity waves, tides, planetary waves, Kelvin waves) that grows in amplitude with height and enters the IT system near ~100 km. Some members of the wave spectrum penetrate all the way to the base of the exosphere (ca. 500 km). Along the way, nonlinear interactions between different wave components occur, modifying the interacting waves and giving rise to secondary waves. Finally, the IT wind perturbations carried by the waves can redistribute ionospheric plasma, either through the electric fields generated via the dynamo mechanism between 100 and 150 km, or directly by moving plasma along magnetic field lines at higher levels. Additionally, the signatures of wave-driven dynamo currents are reflected in magnetic perturbations observed at the ground. This is how terrestrial atmospheric variability, through the spectrum of vertically- propagating waves that it produces, can effectively drive IT space weather. The primary objective of this Julius Bartels Lecture is to provide an overview of the global observational evidence for the IT consequences of these upward-propagating waves. In honor of Julius Bartels, who performed much research (including his habilitation thesis) on atmospheric and geomagnetic tides, this talk will emphasize the tidal part of the wave spectrum and its effects on the upper atmosphere.

14 CFR 121.599 - Familiarity with weather conditions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Familiarity with weather conditions. 121... § 121.599 Familiarity with weather conditions. (a) Domestic and flag operations. No aircraft dispatcher may release a flight unless he is thoroughly familiar with reported and forecast weather conditions on...

14 CFR 121.599 - Familiarity with weather conditions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Familiarity with weather conditions. 121... § 121.599 Familiarity with weather conditions. (a) Domestic and flag operations. No aircraft dispatcher may release a flight unless he is thoroughly familiar with reported and forecast weather conditions on...

14 CFR 121.599 - Familiarity with weather conditions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Familiarity with weather conditions. 121... § 121.599 Familiarity with weather conditions. (a) Domestic and flag operations. No aircraft dispatcher may release a flight unless he is thoroughly familiar with reported and forecast weather conditions on...

14 CFR 121.599 - Familiarity with weather conditions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Familiarity with weather conditions. 121... § 121.599 Familiarity with weather conditions. (a) Domestic and flag operations. No aircraft dispatcher may release a flight unless he is thoroughly familiar with reported and forecast weather conditions on...

14 CFR 121.599 - Familiarity with weather conditions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Familiarity with weather conditions. 121... § 121.599 Familiarity with weather conditions. (a) Domestic and flag operations. No aircraft dispatcher may release a flight unless he is thoroughly familiar with reported and forecast weather conditions on...

Identifying Patterns in the Weather of Europe for Source Term Estimation

NASA Astrophysics Data System (ADS)

Klampanos, Iraklis; Pappas, Charalambos; Andronopoulos, Spyros; Davvetas, Athanasios; Ikonomopoulos, Andreas; Karkaletsis, Vangelis

2017-04-01

During emergencies that involve the release of hazardous substances into the atmosphere the potential health effects on the human population and the environment are of primary concern. Such events have occurred in the past, most notably involving radioactive and toxic substances. Examples of radioactive release events include the Chernobyl accident in 1986, as well as the more recent Fukushima Daiichi accident in 2011. Often, the release of dangerous substances in the atmosphere is detected at locations different from the release origin. The objective of this work is the rapid estimation of such unknown sources shortly after the detection of dangerous substances in the atmosphere, with an initial focus on nuclear or radiological releases. Typically, after the detection of a radioactive substance in the atmosphere indicating the occurrence of an unknown release, the source location is estimated via inverse modelling. However, depending on factors such as the spatial resolution desired, traditional inverse modelling can be computationally time-consuming. This is especially true for cases where complex topography and weather conditions are involved and can therefore be problematic when timing is critical. Making use of machine learning techniques and the Big Data Europe platform1, our approach moves the bulk of the computation before any such event taking place, therefore allowing for rapid initial, albeit rougher, estimations regarding the source location. Our proposed approach is based on the automatic identification of weather patterns within the European continent. Identifying weather patterns has long been an active research field. Our case is differentiated by the fact that it focuses on plume dispersion patterns and these meteorological variables that affect dispersion the most. For a small set of recurrent weather patterns, we simulate hypothetical radioactive releases from a pre-known set of nuclear reactor locations and for different substance and temporal parameters, using the Java flavour of the Euratom-supported funded RODOS (Real-time On-line DecisiOn Support) system2 for off-site emergency management after nuclear accidents. Once dispersions have been pre-computed, and immediately after a detected release, the currently observed weather can be matched to the derived weather classes. Since each weather class corresponds to a different plume dispersion pattern, the closest classes to an unseen weather sample, say the current weather, are the most likely to lead us to the release origin. In addressing the above problem, we make use of multiple years of weather reanalysis data from NCAR's version3 of ECMWF's ERA-Interim4. To derive useful weather classes, we evaluate several algorithms, ranging from straightforward unsupervised clustering to more complex methods, including relevant neural-network algorithms, on multiple variables. Variables and feature sets, clustering algorithms and evaluation approaches are all dealt with and presented experimentally. The Big Data Europe platform allows for the implementation and execution of the above tasks in the cloud, in a scalable, robust and efficient way.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

An observational analysis: Tropical relative to Arctic influence on midlatitude weather in the era of Arctic amplification

NASA Astrophysics Data System (ADS)

Cohen, Judah

2016-05-01

The tropics, in general, and El Niño/Southern Oscillation (ENSO) in particular are almost exclusively relied upon for seasonal forecasting. Much less considered and certainly more controversial is the idea that Arctic variability is influencing midlatitude weather. However, since the late 1980s and early 1990s, the Arctic has undergone the most rapid warming observed globally, referred to as Arctic amplification (AA), which has coincided with an observed increase in extreme weather. Analysis of observed trends in hemispheric circulation over the period of AA more closely resembles variability associated with Arctic boundary forcings than with tropical forcing. Furthermore, analysis of intraseasonal temperature variability shows that the cooling in midlatitude winter temperatures has been accompanied by an increase in temperature variability and not a decrease, popularly referred to as "weather whiplash."

Mid-Late Holocene climate variability and fire events in a High Atlantic mountain area in NW Iberia (Picos de Europa)

NASA Astrophysics Data System (ADS)

Ruiz-Fernández, Jesus; Nieuwendam, Alexandre; Oliva, Marc; Lopes, Vera; Cruces, Anabela; Conceição Freitas, Maria; Janeiro, Ana; López-Sáez, José Antonio; Gallinar, David; García-Hernández, Cristina

2016-04-01

In this contribution we present data from a 182 cm-long sedimentary sequence collected in the mid-altitude area of Belbín, a depression dammed by a moraine during the Last Glaciation in the Western Massif of the Picos de Europa (Cantabrian Mountains, NW Spain), in order to reconstruct the environmental changes and the conditioning factors of these changes occurred during the Mid-Late Holocene in this mountain area. The uppermost 60 cm of the sediments have been studied using a multi-proxy analysis including the texture, the organic matter content, the micromorphology of the quartz grains, and the concentration of charcoal particles. The geochronological framework of the environmental and climatic events for the Mid-late Holocene was established with three AMS 14C dates. During the last 6.7 ky cal BP a sequence of environmental changes took place in Belbin area driven by both warmer (between 6.7-5, 3.7-3, 2.6-1.1, 0.87-0.51 and since 0.01 ky cal BP) and colder stages (between 5-3.7, 3-2.6, 1.1-0.87 and 0.51 to 0.01 ky cal BP). The warmer stages were defined by the prevalence of chemical weathering of the quartz grains and relative increases of the C/N ratio. Conversely, during colder stages physical weathering of the quartz grains particles prevailed and the C/N values were lower. During the Late Holocene the sequence shows a progressive increase in the organic matter content, which may be associated with higher temperatures. Higher or lower concentration of charcoal particles according to warmer or colder climatic conditions is not detected, so the fires that have occurred in the area were likely to be related to human-induced fire management for grazing purposes. The period with the most frequent fire events occurred between 3.5 and 3 ky cal BP during the Bronze Age. Other significant peaks of charcoal particles occurred at ca. 2.6, 0.71 and 0.36 ky cal BP. This study shows evidence that the environmental changes occurred during the Mid-Late Holocene in this area of the Cantabrian Mountains are both conditioned by climate variability and human activity. Also, it has been demonstrated the relationship between the type of quartz grains, the weathering intensity (chemical and physical) and the concentrations of charcoal particles. There is a clear relation between the samples that evidence high intensity of chemical and physical weathering with higher average of charcoal particles concentration. Climatic conditions have an important role in weathering intensity, through the combination of silt abundance and cryogenic weathering, but in our study this is not the case, therefore fire most possibly modified local environmental conditions making quartz grains more vulnerable to post-fire situations. This emphasizes the important role of the fires in the micromorphology of quartz grains.

A Study of the Relationship between Weather Variables and Electric Power Demand inside a Smart Grid/Smart World Framework

PubMed Central

Hernández, Luis; Baladrón, Carlos; Aguiar, Javier M.; Calavia, Lorena; Carro, Belén; Sánchez-Esguevillas, Antonio; Cook, Diane J.; Chinarro, David; Gómez, Jorge

2012-01-01

One of the main challenges of today's society is the need to fulfill at the same time the two sides of the dichotomy between the growing energy demand and the need to look after the environment. Smart Grids are one of the answers: intelligent energy grids which retrieve data about the environment through extensive sensor networks and react accordingly to optimize resource consumption. In order to do this, the Smart Grids need to understand the existing relationship between energy demand and a set of relevant climatic variables. All smart “systems” (buildings, cities, homes, consumers, etc.) have the potential to employ their intelligence for self-adaptation to climate conditions. After introducing the Smart World, a global framework for the collaboration of these smart systems, this paper presents the relationship found at experimental level between a range of relevant weather variables and electric power demand patterns, presenting a case study using an agent-based system, and emphasizing the need to consider this relationship in certain Smart World (and specifically Smart Grid and microgrid) applications.

Do weather changes influence pain levels in women with fibromyalgia, and can psychosocial variables moderate these influences?

NASA Astrophysics Data System (ADS)

Smedslund, Geir; Eide, Hilde; Kristjansdottir, Ólöf Birna; Nes, Andrea Aparecida Gonçalves; Sexton, Harold; Fors, Egil A.

2014-09-01

The aim of this study was to examine the association between fibromyalgia pain and weather, and to investigate whether psychosocial factors influence this relationship. Women with chronic widespread pain/fibromyalgia ( N = 50) enrolled in a larger study, were recruited from a 4-week inpatient rehabilitation program in Norway ( 2009-2010), and reported their pain and psychological factors up to three times per day (morning, afternoon, evening) for 5 weeks. These ratings were then related to the official local weather parameters. Barometric pressure recorded simultaneously impacted pain significantly while temperature, relative humidity, and solar flux did not. No psychological variables influenced the weather-pain interaction. No weather parameter predicted change in the subsequent pain measures. The magnitude of the inverse association between pain and barometric pressure was very small, and none of the psychological variables studied influenced the association between pain and barometric pressure. All in all, the evidence for a strong weather-pain association in fibromyalgia seems limited at best.

Optimum space shuttle launch times relative to natural environment

NASA Technical Reports Server (NTRS)

King, R. L.

1977-01-01

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

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

PubMed Central

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

2014-01-01

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

Spatial and Temporal Dynamics of Aphids (Hemiptera: Aphididae) in the Columbia Basin and Northeastern Oregon.

PubMed

Klein, Mathew L; Rondon, Silvia I; Walenta, Darrin L; Zeb, Qamar; Murphy, Alexzandra F

2017-08-01

Aphid species, such as the potato aphid, Macrosiphum euphorbiae Thomas, and the green peach aphid, Myzus persicae Sulzer, are routinely considered the most important pests of potatoes. Potato aphid, green peach aphid, and more recently, other aphids such as the bird cherry-oat aphid Rhopalosiphum padi L. have been identified as vectors of multiple plant pathogenic viruses in potatoes. Since 2006, an area-wide trapping network consisting of ∼60 sites was developed through collaboration between researchers, extension faculty, and stakeholders, to monitor aphid populations in the Columbia Basin of Oregon (Umatilla and Morrow counties) and in northeastern Oregon (Union and Baker counties). Over a 9-yr period (2006 to 2014), aphid specimens were collected weekly using yellow bucket traps and specimens were then identified and counted to determine population levels during the growing season (May-September). Thus, aphid population data were compiled and subjected to spatial and temporal distribution analysis. Weather data, obtained from an established network of weather stations located in the monitoring areas, were used in a nonparametric multiplicative regression analysis to determine which abiotic variables may impact aphid populations. Weather conditions were characterized using confidence intervals (CIs) established based on weather data from 1999 to 2005 for each environmental variable. Aphid populations were found to have a heterogeneous distribution in most years; a few sites had high aphid populations while low numbers were observed at most sites; aphids were also found to correlate with several abiotic variables, namely, elevation, previous season temperature, and previous season dew point. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Evaluating the performance of ENVI-met model in diurnal cycles for different meteorological conditions

NASA Astrophysics Data System (ADS)

Acero, Juan A.; Arrizabalaga, Jon

2018-01-01

Urban areas are known to modify meteorological variables producing important differences in small spatial scales (i.e. microscale). These affect human thermal comfort conditions and the dispersion of pollutants, especially those emitted inside the urban area, which finally influence quality of life and the use of public open spaces. In this study, the diurnal evolution of meteorological variables measured in four urban spaces is compared with the results provided by ENVI-met (v 4.0). Measurements were carried out during 3 days with different meteorological conditions in Bilbao in the north of the Iberian Peninsula. The evaluation of the model accuracy (i.e. the degree to which modelled values approach measured values) was carried out with several quantitative difference metrics. The results for air temperature and humidity show a good agreement of measured and modelled values independently of the regional meteorological conditions. However, in the case of mean radiant temperature and wind speed, relevant differences are encountered highlighting the limitation of the model to estimate these meteorological variables precisely during diurnal cycles, in the considered evaluation conditions (sites and weather).

Weather variability, tides, and Barmah Forest virus disease in the Gladstone region, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S; McMichael, Anthony J; Dale, Pat; Tong, Shilu

2006-05-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (b=0.15, p-value<0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (b=-1.03, p-value=0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Evaluation of Candidate Millimeter Wave Sensors for Synthetic Vision

NASA Technical Reports Server (NTRS)

Alexander, Neal T.; Hudson, Brian H.; Echard, Jim D.

1994-01-01

The goal of the Synthetic Vision Technology Demonstration Program was to demonstrate and document the capabilities of current technologies to achieve safe aircraft landing, take off, and ground operation in very low visibility conditions. Two of the major thrusts of the program were (1) sensor evaluation in measured weather conditions on a tower overlooking an unused airfield and (2) flight testing of sensor and pilot performance via a prototype system. The presentation first briefly addresses the overall technology thrusts and goals of the program and provides a summary of MMW sensor tower-test and flight-test data collection efforts. Data analysis and calibration procedures for both the tower tests and flight tests are presented. The remainder of the presentation addresses the MMW sensor flight-test evaluation results, including the processing approach for determination of various performance metrics (e.g., contrast, sharpness, and variability). The variation of the very important contrast metric in adverse weather conditions is described. Design trade-off considerations for Synthetic Vision MMW sensors are presented.

Seasonal bird traffic between Grand Teton National Park and western Mexico

Treesearch

Martin L. Cody

2005-01-01

This paper presents data on variations in the breeding densities of birds in Grand Teton National Park, Wyoming, and evaluates these variations among years, habitats, and as functions of the migratory status of the breeding birds. Breeding opportunities certainly vary with the extremely variable weather conditions in the park year-to-year, and part of the variation in...

Spatial and temporal ecology of oak toads (Bufo quercicus) on a Florida landscape

Treesearch

Cathryn H. Greenberg; George W. Tanner

2005-01-01

We used data from 10 years of continuous, concurrent monitoring of oak toads at eight isolated, ephemeral ponds in Florida longleaf pine-wiregrass uplands to address: (1): did weather variables affect movement patterns of oak toads? (2) did pond hydrology and the condition of surrounding uplands affect pond selection by adults or juvenile recruitment? (3) were...

Exploring the use of WRF-3DVar for Estimating reference evapotranspiration in semi arid regions

NASA Astrophysics Data System (ADS)

Bray, Michaela; Liu, Jia; Abdulhamza, Ali; Bocklemann-Evans, Bettina

2013-04-01

Evapotranspiration is an important process in hydrology and is central to the analysis of water balances and water resource management. Significant water losses can occur in large drainage basins under semi arid climate conditions, moreover with the lack of measured data, the exact losses are hard to quantify. Since direct measurements for evapotranspiration are difficult to obtain it is common to estimate the process by using evapotranspiration models such as the Priestley-Taylor model, Shuttleworth -Wallace model and the FAO Penmann-Monteith. However these models depend on several atmospheric variables such as atmospheric pressure, wind speed, air temperature, net radiation and relative humidity. Some of these variables are also difficult to acquire from in-situ measurements; in addition these measurements provide local information which need to be interpolated to cover larger catchment areas over long time scales. Mesoscale Numerical Weather Prediction (NWP) modelling has become more accessible to the hydrometeorological community in recent years and is frequently used for modelling precipitation at the catchment scale. However these NWPs can also provide the atmospheric variables needed for evapotranspiration estimation at finer resolutions than can be attained from in situ measurements, offering a practical water resource tool. Moreover there is evidence that assimilation of real time observations can help improve the accuracy of mesoscale weather modelling which in turn would improve the overall evapotranspiration estimate. This study explores the effect of data assimilation in the Weather Research and Forecasting (WRF) model to derive evapotranspiration estimates for the Tigris water basin, Iraq. Two types of traditional observations, SYNOP and SOUND are assimilated by WRF-3DVAR.which contain surface and upper-level measurements of pressure, temperature, humidity and wind. The downscaled weather variables are used to determine evapostranspiration estimates and compared with observed evapostranspiration data measured by Class A evaporation pan.

Analysis of Numerical Weather Predictions of Reference Evapotranspiration and Precipitation

NASA Astrophysics Data System (ADS)

Bughici, Theodor; Lazarovitch, Naftali; Fredj, Erick; Tas, Eran

2017-04-01

This study attempts to improve the forecast skill of the evapotranspiration (ET0) and Precipitation for the purpose of crop irrigation management over Israel using the Weather Research and Forecasting (WRF) Model. Optimized crop irrigation, in term of timing and quantities, decreases water and agrochemicals demand. Crop water demands depend on evapotranspiration and precipitation. The common method for computing reference evapotranspiration, for agricultural needs, ET0, is according to the FAO Penman-Monteith equation. The weather variables required for ET0 calculation (air temperature, relative humidity, wind speed and solar irradiance) are estimated by the WRF model. The WRF Model with two-way interacting domains at horizontal resolutions of 27, 9 and 3 km is used in the study. The model prediction was performed in an hourly time resolution and a 3 km spatial resolution, with forecast lead-time of up to four days. The WRF prediction of these variables have been compared against measurements from 29 meteorological stations across Israel for the year 2013. The studied area is small but with strong climatic gradient, diverse topography and variety of synoptic conditions. The forecast skill that was used for forecast validation takes into account the prediction bias, mean absolute error and root mean squared error. The forecast skill of the variables was almost robust to lead time, except for precipitation. The forecast skill was tested across stations with respect to topography and geographic location and for all stations with respect to seasonality and synoptic weather system determined by employing a semi-objective synoptic systems classification to the forecasted days. It was noticeable that forecast skill of some of the variables was deteriorated by seasonality and topography. However, larger impacts in the ET0 skill scores on the forecasted day are achieved by a synoptic based forecast. These results set the basis for increasing the robustness of ET0 to synoptic effects and for more precise crop irrigation over Israel.

Weather conditions drive dynamic habitat selection in a generalist predator.

PubMed

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

2014-01-01

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

Weather analysis and interpretation procedures developed for the US/Canada wheat and barley exploratory experiment

NASA Technical Reports Server (NTRS)

Trenchard, M. H. (Principal Investigator)

1980-01-01

Procedures and techniques for providing analyses of meteorological conditions at segments during the growing season were developed for the U.S./Canada Wheat and Barley Exploratory Experiment. The main product and analysis tool is the segment-level climagraph which depicts temporally meteorological variables for the current year compared with climatological normals. The variable values for the segment are estimates derived through objective analysis of values obtained at first-order station in the region. The procedures and products documented represent a baseline for future Foreign Commodity Production Forecasting experiments.

Sensor performance and weather effects modeling for intelligent transportation systems (ITS) applications

NASA Astrophysics Data System (ADS)

Everson, Jeffrey H.; Kopala, Edward W.; Lazofson, Laurence E.; Choe, Howard C.; Pomerleau, Dean A.

1995-01-01

Optical sensors are used for several ITS applications, including lateral control of vehicles, traffic sign recognition, car following, autonomous vehicle navigation, and obstacle detection. This paper treats the performance assessment of a sensor/image processor used as part of an on-board countermeasure system to prevent single vehicle roadway departure crashes. Sufficient image contrast between objects of interest and backgrounds is an essential factor influencing overall system performance. Contrast is determined by material properties affecting reflected/radiated intensities, as well as weather and visibility conditions. This paper discusses the modeling of these parameters and characterizes the contrast performance effects due to reduced visibility. The analysis process first involves generation of inherent road/off- road contrasts, followed by weather effects as a contrast modification. The sensor is modeled as a charge coupled device (CCD), with variable parameters. The results of the sensor/weather modeling are used to predict the performance on an in-vehicle warning system under various levels of adverse weather. Software employed in this effort was previously developed for the U.S. Air Force Wright Laboratory to determine target/background detection and recognition ranges for different sensor systems operating under various mission scenarios.

The influence of climate variability on chemical composition of European wines: a regional scale study (Italy and Slovenia)

NASA Astrophysics Data System (ADS)

Barbante, Carlo; Polo, Fabio; Cozzi, Giulio; Ogrinc, Nives; Turetta, Clara

2016-04-01

Climate change is having an increasing influence on vine phenology and grape composition, affecting vinifications, wine chemistry and the quality of productions. Wine grape cultivation provides a good test case for measuring indirect impacts mediated by changes in agriculture, because viticulture is sensitive to climate and is concentrated in Mediterranean climate regions that are global biodiversity hotspots. Moreover, on a regional level and on a shorter time scale, the seasonal weather conditions modify the quality of yields determining the final properties of wine. In the present research, we studied wines from Italy and Slovenia with the purpose of differentiating them by the different vintages (from 2009 to 2012), which are supposed to be influenced by temperature and rain during each year's growing season. Specific chemical techniques were used, in particular mass spectrometry (ICP-MS) and isotopic mass spectrometry (IRMS), both of which are usually employed to detect wine adulterations and to establish the geographical provenance of wines. In particular, we investigated the relationship between macro- and micro-elements, Rare Earth Elements and stable isotopes [δ13C, δ18O, (D/H)I, (D/H)II]. The datasets were examined via statistical techniques to show their relation to weather conditions as well as their mutual connection. Italian and Slovenian wines were distinguished, with the exception of few samples, by both TEs and REEs results. This separation, due to different elemental compositions, may be justified as being part of two distinct environmental and geographical belongings (terroir) but also to the processes of wine production, from the harvest to the bottling, which have certainly interfered and characterized the products. In the case of Italian wines the weather conditions were evidenced with an important separation of stable isotopes which they confirmed to be very sensitive Regarding Slovenian wines, the studied regions were characterized of three very different environments, and the elemental measurements resulted very useful. However, it was not possible to separate the different wine regions using elemental composition while the vintages were clearly evidenced. The results of this work were not able to confirm the mass spectrometry and the isotopic mass spectrometry to be useful to distinguish a wine for a specific region while they were able to separate vintages growth in different weather conditions. In conclusion of the work we can furthermore suggest from our data that weather conditions showed to have more influence in the chemical composition of wines than the environmental contribution. Moreover, the more is different a year in terms of weather conditions, the more the techniques of analysis can show the separation of the wines made in that year. However, has been not possible distinguish vintages produced in years of similar weather conditions.

a Weather Monitoring System for Application to Apple and Corn Production

NASA Astrophysics Data System (ADS)

Stirm, Walter Leroy

Many crop management decisions are based on weather -crop development relationships. Daily weather data is currently used in most crop development research and applied models. Present weather and computer technology now makes possible monitoring of crop development on a realtime basis. This research tests a method of computing crop sensitive temperatures for corn and apple using standard hourly meteorological data. The method also makes use of detailed plant physiological stage measurements to determine timing of vital cultural operations tied to the observed weather conditions. The sensitive temperature method incorporates very short term weather variability accounting for changes in the cloud cover, radiation rates, evaporative cooling and other factors involved in the plant's energy balance. The relationship of plant and weather measurements are also used to determine corn emergence, corn grain drydown rate and fruit harvest duration. The monitoring system also incorporates a crop growth unit forecast technique employing short and medium range temperature forecasts of the National Weather Service. The projections of growth units are made for five and ten days into the future. Predicted growth unit accumulations are compared to historical growth unit accumulations to determine the forecast stage. The sensitive temperature crop monitoring system removes some of the error involved in evaluation of growth units by average daily temperature. Carry over maximum and minimums, extended duration of warm or cool periods within the day and disruption of diurnal temperature curve by passage of fronts are eliminated.

Phase-dependent climate-predator interactions explain three decades of variation in neonatal caribou survival.

PubMed

Bastille-Rousseau, Guillaume; Schaefer, James A; Lewis, Keith P; Mumma, Matthew A; Ellington, E Hance; Rayl, Nathaniel D; Mahoney, Shane P; Pouliot, Darren; Murray, Dennis L

2016-03-01

Climate can have direct and indirect effects on population dynamics via changes in resource competition or predation risk, but this influence may be modulated by density- or phase-dependent processes. We hypothesized that for ungulates, climatic conditions close to parturition have a greater influence on the predation risk of neonates during population declines, when females are already under nutritional stress triggered by food limitation. We examined the presence of phase-dependent climate-predator (PDCP) interactions on neonatal ungulate survival by comparing spatial and temporal fluctuations in climatic conditions, cause-specific mortality and per capita resource limitation. We determined cause-specific fates of 1384 caribou (Rangifer tarandus) from 10 herds in Newfoundland, spanning more than 30 years during periods of numerical increase and decline, while exposed to predation from black bears (Ursus americanus) and coyotes (Canis latrans). We conducted Cox proportional hazards analysis for competing risks, fit as a function of weather metrics, to assess pre- and post-partum climatic influences on survival on herds in population increase and decline phases. We used cumulative incidence functions to compare temporal changes in risk from predators. Our results support our main hypothesis; when caribou populations increased, weather conditions preceding calving were the main determinants of cause-specific mortality, but when populations declined, weather conditions during calving also influenced predator-driven mortality. Cause-specific analysis showed that weather conditions can differentially affect predation risk between black bears and coyotes with specific variables increasing the risk from one species and decreasing the risk from the other. For caribou, nutritional stress appears to increase predation risk on neonates, an interaction which is exacerbated by susceptibility to climatic events. These findings support the PDCP interactions framework, where maternal body condition influences susceptibility to climate-related events and, subsequently, risk from predation. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Profiles of Volatile Compounds in Black Currant (Ribes nigrum) Cultivars with Special Focus on Influence of Growth Latitude and Weather Conditions.

PubMed

Marsol-Vall, Alexis; Kortesniemi, Maaria Katariina; Karhu, Saila; Kallio, Heikki; Yang, Baoru

2018-06-25

The volatile profile of three blackcurrant (Ribes nigrum L.) cultivars grown in Finland and their response to growth latitude and weather conditions were studied over an eight-year period by headspace solid-phase microextraction (HS-SPME) followed by gas chromatographic-mass spectrometric (GC-MS) analysis. Monoterpene hydrocarbons and oxygenated monoterpenes were the major classes of volatiles. The cultivar 'Melalahti' presented lower content of volatiles compared with 'Ola' and 'Mortti', the two latter showing a very similar composition. Higher contents of volatiles were found in berries cultivated at higher latitude (66° 34' N) than in those from the southern location (60° 23' N). Among the meteorological variables, radiation and temperature during the last month before harvest were negatively linked with the volatile content. Storage time had a negative impact on the amount of blackcurrant volatiles.

Mars Radiation Surface Model

NASA Astrophysics Data System (ADS)

Alzate, N.; Grande, M.; Matthiae, D.

2017-09-01

Planetary Space Weather Services (PSWS) within the Europlanet H2020 Research Infrastructure have been developed following protocols and standards available in Astrophysical, Solar Physics and Planetary Science Virtual Observatories. Several VO-compliant functionalities have been implemented in various tools. The PSWS extends the concepts of space weather and space situational awareness to other planets in our Solar System and in particular to spacecraft that voyage through it. One of the five toolkits developed as part of these services is a model dedicated to the Mars environment. This model has been developed at Aberystwyth University and the Institut fur Luft- und Raumfahrtmedizin (DLR Cologne) using modeled average conditions available from Planetocosmics. It is available for tracing propagation of solar events through the Solar System and modeling the response of the Mars environment. The results have been synthesized into look-up tables parameterized to variable solar wind conditions at Mars.

Adverse weather conditions and fatal motor vehicle crashes in the United States, 1994-2012.

PubMed

Saha, Shubhayu; Schramm, Paul; Nolan, Amanda; Hess, Jeremy

2016-11-08

Motor vehicle crashes are a leading cause of injury mortality. Adverse weather and road conditions have the potential to affect the likelihood of motor vehicle fatalities through several pathways. However, there remains a dearth of assessments associating adverse weather conditions to fatal crashes in the United States. We assessed trends in motor vehicle fatalities associated with adverse weather and present spatial variation in fatality rates by state. We analyzed the Fatality Analysis Reporting System (FARS) datasets from 1994 to 2012 produced by the National Highway Traffic Safety Administration (NHTSA) that contains reported weather information for each fatal crash. For each year, we estimated the fatal crashes that were associated with adverse weather conditions. We stratified these fatalities by months to examine seasonal patterns. We calculated state-specific rates using annual vehicle miles traveled data for all fatalities and for those related to adverse weather to examine spatial variations in fatality rates. To investigate the role of adverse weather as an independent risk factor for fatal crashes, we calculated odds ratios for known risk factors (e.g., alcohol and drug use, no restraint use, poor driving records, poor light conditions, highway driving) to be reported along with adverse weather. Total and adverse weather-related fatalities decreased over 1994-2012. Adverse weather-related fatalities constituted about 16 % of total fatalities on average over the study period. On average, 65 % of adverse weather-related fatalities happened between November and April, with rain/wet conditions more frequently reported than snow/icy conditions. The spatial distribution of fatalities associated with adverse weather by state was different than the distribution of total fatalities. Involvement of alcohol or drugs, no restraint use, and speeding were less likely to co-occur with fatalities during adverse weather conditions. While adverse weather is reported for a large number of motor vehicle fatalities for the US, the type of adverse weather and the rate of associated fatality vary geographically. These fatalities may be addressed and potentially prevented by modifying speed limits during inclement weather, improving road surfacing, ice and snow removal, and providing transit alternatives, but the impact of potential interventions requires further research.

75 FR 8353 - Waiver of Filing Deadline Due to Adverse Weather Conditions

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-24

... FEDERAL COMMUNICATIONS COMMISSION Waiver of Filing Deadline Due to Adverse Weather Conditions... weather conditions, the Federal Communications Commission closed early on Friday, February 5, and closed... closings and disruptions caused by the weather in the Washington, DC area, all paper and electronic filings...

WIRE: Weather Intelligence for Renewable Energies

NASA Astrophysics Data System (ADS)

Heimo, A.; Cattin, R.; Calpini, B.

2010-09-01

Renewable energies such as wind and solar energy will play an important, even decisive role in order to mitigate and adapt to the projected dramatic consequences to our society and environment due to climate change. Due to shrinking fossil resources, the transition to more and more renewable energy shares is unavoidable. But, as wind and solar energy are strongly dependent on highly variable weather processes, increased penetration rates will also lead to strong fluctuations in the electricity grid which need to be balanced. Proper and specific forecasting of ‘energy weather' is a key component for this. Therefore, it is today appropriate to scientifically address the requirements to provide the best possible specific weather information for forecasting the energy production of wind and solar power plants within the next minutes up to several days. Towards such aims, Weather Intelligence will first include developing dedicated post-processing algorithms coupled with weather prediction models and with past and/or online measurement data especially remote sensing observations. Second, it will contribute to investigate the difficult relationship between the highly intermittent weather dependent power production and concurrent capacities such as transport and distribution of this energy to the end users. Selecting, resp. developing surface-based and satellite remote sensing techniques well adapted to supply relevant information to the specific post-processing algorithms for solar and wind energy production short-term forecasts is a major task with big potential. It will lead to improved energy forecasts and help to increase the efficiency of the renewable energy productions while contributing to improve the management and presumably the design of the energy grids. The second goal will raise new challenges as this will require first from the energy producers and distributors definitions of the requested input data and new technologies dedicated to the management of power plants and electricity grids and second from the meteorological measurement community to deliver suitable, short term high quality forecasts to fulfill these requests with emphasis on highly variable weather conditions and spatially distributed energy productions often located in complex terrain. This topic has been submitted for a new COST Action under the title "Short-Term High Resolution Wind and Solar Energy Production Forecasts".

Linking the climatic and geochemical controls on global soil carbon cycling

NASA Astrophysics Data System (ADS)

Doetterl, Sebastian; Stevens, Antoine; Six, Johan; Merckx, Roel; Van Oost, Kristof; Casanova Pinto, Manuel; Casanova-Katny, Angélica; Muñoz, Cristina; Boudin, Mathieu; Zagal Venegas, Erick; Boeckx, Pascal

2015-04-01

Climatic and geochemical parameters are regarded as the primary controls for soil organic carbon (SOC) storage and turnover. However, due to the difference in scale between climate and geochemical-related soil research, the interaction of these key factors for SOC dynamics have rarely been assessed. Across a large geochemical and climatic transect in similar biomes in Chile and the Antarctic Peninsula we show how abiotic geochemical soil features describing soil mineralogy and weathering pose a direct control on SOC stocks, concentration and turnover and are central to explaining soil C dynamics at larger scales. Precipitation and temperature had an only indirect control by regulating geochemistry. Soils with high SOC content have low specific potential CO2 respiration rates, but a large fraction of SOC that is stabilized via organo-mineral interactions. The opposite was observed for soils with low SOC content. The observed differences for topsoil SOC stocks along this transect of similar biomes but differing geo-climatic site conditions are of the same magnitude as differences observed for topsoil SOC stocks across all major global biomes. Using precipitation and a set of abiotic geochemical parameters describing soil mineralogy and weathering status led to predictions of high accuracy (R2 0.53-0.94) for different C response variables. Partial correlation analyses revealed that the strength of the correlation between climatic predictors and SOC response variables decreased by 51 - 83% when controlling for geochemical predictors. In contrast, controlling for climatic variables did not result in a strong decrease in the strength of the correlations of between most geochemical variables and SOC response variables. In summary, geochemical parameters describing soil mineralogy and weathering were found to be essential for accurate predictions of SOC stocks and potential CO2 respiration, while climatic factors were of minor importance as a direct control, but are important through governing soil weathering and geochemistry. In conclusion, we pledge for a stronger implementation of geochemical soil properties to predict SOC stocks on a global scale. Understanding the effects of climate (temperature and precipitation) change on SOC dynamics also requires good understanding of the relationship between climate and soil geochemistry.

Little Ice Age climatic erraticism as an analogue for future enhanced hydroclimatic variability across the American Southwest

PubMed Central

Loisel, Julie; MacDonald, Glen M.; Thomson, Marcus J.

2017-01-01

The American Southwest has experienced a series of severe droughts interspersed with strong wet episodes over the past decades, prompting questions about future climate patterns and potential intensification of weather disruptions under warming conditions. Here we show that interannual hydroclimatic variability in this region has displayed a significant level of non-stationarity over the past millennium. Our tree ring-based analysis of past drought indicates that the Little Ice Age (LIA) experienced high interannual hydroclimatic variability, similar to projections for the 21st century. This is contrary to the Medieval Climate Anomaly (MCA), which had reduced variability and therefore may be misleading as an analog for 21st century warming, notwithstanding its warm (and arid) conditions. Given past non-stationarity, and particularly erratic LIA, a ‘warm LIA’ climate scenario for the coming century that combines high precipitation variability (similar to LIA conditions) with warm and dry conditions (similar to MCA conditions) represents a plausible situation that is supported by recent climate simulations. Our comparison of tree ring-based drought analysis and records from the tropical Pacific Ocean suggests that changing variability in El Niño Southern Oscillation (ENSO) explains much of the contrasting variances between the MCA and LIA conditions across the American Southwest. Greater ENSO variability for the 21st century could be induced by a decrease in meridional sea surface temperature gradient caused by increased greenhouse gas concentration, as shown by several recent climate modeling experiments. Overall, these results coupled with the paleo-record suggests that using the erratic LIA conditions as benchmarks for past hydroclimatic variability can be useful for developing future water-resource management and drought and flood hazard mitigation strategies in the Southwest. PMID:29036207

Tracking near-surface atmospheric conditions using an infrasound network.

PubMed

Marcillo, O; Johnson, J B

2010-07-01

Continuous volcanic infrasound signal was recorded on a three-microphone network at Kilauea in July 2008 and inverted for near-surface horizontal winds. Inter-station phase delays, determined by signal cross-correlation, vary by up to 4% and are attributable to variable atmospheric conditions. The results suggest two predominant weather regimes during the study period: (1) 6-9 m/s easterly trade winds and (2) lower-intensity 2-5 m/s mountain breezes from Mauna Loa. The results demonstrate the potential of using infrasound for tracking local averaged meteorological conditions, which has implications for modeling plume dispersal and quantifying gas flux.

VARIABLE CHARGE SOILS: MINERALOGY AND CHEMISTRY

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

Van Ranst, Eric; Qafoku, Nikolla; Noble, Andrew

2016-09-19

Soils rich in particles with amphoteric surface properties in the Oxisols, Ultisols, Alfisols, Spodosols and Andisols orders (1) are considered to be variable charge soils (2) (Table 1). The term “variable charge” is used to describe organic and inorganic soil constituents with reactive surface groups whose charge varies with pH and ionic concentration and composition of the soil solution. Such groups are the surface carboxyl, phenolic and amino functional groups of organic materials in soils, and surface hydroxyl groups of Fe and Al oxides, allophane and imogolite. The hydroxyl surface groups are also present on edges of some phyllosilicate mineralsmore » such as kaolinite, mica, and hydroxyl-interlayered vermiculite. The variable charge is developed on the surface groups as a result of adsorption or desorption of ions that are constituents of the solid phase, i.e., H+, and the adsorption or desorption of solid-unlike ions that are not constituents of the solid phase. Highly weathered soils and subsoils (e.g., Oxisols and some Ultisols, Alfisols and Andisols) may undergo isoelectric weathering and reach a “zero net charge” stage during their development. They usually have a slightly acidic to acidic soil solution pH, which is close to either the point of zero net charge (PZNC) (3) or the point of zero salt effect (PZSE) (3). They are characterized by high abundances of minerals with a point of zero net proton charge (PZNPC) (3) at neutral and slightly basic pHs; the most important being Fe and Al oxides and allophane. Under acidic conditions, the surfaces of these minerals are net positively charged. In contrast, the surfaces of permanent charge phyllosilicates are negatively charged regardless of ambient conditions. Variable charge soils therefore, are heterogeneous charge systems.« less

Spring snow conditions on Arctic sea ice north of Svalbard, during the Norwegian Young Sea ICE (N-ICE2015) expedition

NASA Astrophysics Data System (ADS)

Gallet, Jean-Charles; Merkouriadi, Ioanna; Liston, Glen E.; Polashenski, Chris; Hudson, Stephen; Rösel, Anja; Gerland, Sebastian

2017-10-01

Snow is crucial over sea ice due to its conflicting role in reflecting the incoming solar energy and reducing the heat transfer so that its temporal and spatial variability are important to estimate. During the Norwegian Young Sea ICE (N-ICE2015) campaign, snow physical properties and variability were examined, and results from April until mid-June 2015 are presented here. Overall, the snow thickness was about 20 cm higher than the climatology for second-year ice, with an average of 55 ± 27 cm and 32 ± 20 cm on first-year ice. The average density was 350-400 kg m-3 in spring, with higher values in June due to melting. Due to flooding in March, larger variability in snow water equivalent was observed. However, the snow structure was quite homogeneous in spring due to warmer weather and lower amount of storms passing over the field camp. The snow was mostly consisted of wind slab, faceted, and depth hoar type crystals with occasional fresh snow. These observations highlight the more dynamic character of evolution of snow properties over sea ice compared to previous observations, due to more variable sea ice and weather conditions in this area. The snowpack was isothermal as early as 10 June with the first onset of melt clearly identified in early June. Based on our observations, we estimate than snow could be accurately represented by a three to four layers modeling approach, in order to better consider the high variability of snow thickness and density together with the rapid metamorphose of the snow in springtime.

Weather and climate applications for rangeland restoration planning

USDA-ARS?s Scientific Manuscript database

Rangeland ecosystems generally have an arid or semi-arid climatology, and are characterized by relatively high variability in seasonal and annual patterns of precipitation. Weather variability during seedling establishment is universally acknowledged as a principal determinant of rangeland seeding...

Guidelines for disseminating road weather messages.

DOT National Transportation Integrated Search

2010-06-01

The tremendous growth in the amount of available weather and road condition informationincluding devices that gather weather information, models and forecasting tools for predicting weather conditions, and electronic devices used by travelersha...

Weather and childbirth: A further search for relationships

NASA Astrophysics Data System (ADS)

Driscoll, Dennis M.

1995-09-01

Previous attempts to find relationships between weather and parturition (childbirth) and its onset (the beginning of labor pains) have revealed, firstly, limited but statistically significant relationships between weather conditions much colder than the day before, with high winds and low pressure, and increased onsets; and secondly, increased numbers of childbirths during periods of atmospheric pressure rise (highly statistically significant). To test these findings, this study examined weather data coincident childbirth data from a hospital at Bryan-College Station, Texas (for a period of 30 cool months from 1987 to 1992). Tests for (1) days of cold fronts, (2) a day before and a day after the cold front, (3) days with large temperature increases, and (4) decreases from the day before revealed no relationship with mean daily rate of onset. Cold days with high winds and low pressure had significantly fewer onsets, a result that is the opposite of previous findings. The postulated relationship between periods of pressure rise and increased birth frequency was negative, i.e., significantly fewer births occurred at those times — again, the opposite of the apparent occurrence in an earlier study. The coincidence of diurnal variations in both atmospheric pressure and frequency of childbirths, was shown to account for fairly strong negative associations between the two variables. This same reasoning might explain the positive association found in an earlier study. A comparison has been made between childbirth and onset as the response variable, and the advantage is emphasized of using data from women whose labor is not induced.

The use of a high resolution model in a private environment.

NASA Astrophysics Data System (ADS)

van Dijke, D.; Malda, D.

2009-09-01

The commercial organisation MeteoGroup uses high resolution modelling for multiple purposes. MeteoGroup uses the Weather Research and Forecasting Model (WRF®1). WRF is used in the operational environment of several MeteoGroup companies across Europe. It is also used in hindcast studies, for example hurricane tracking, wind climate computation and deriving boundary conditions for air quality models. A special operational service was set up for our tornado chasing team that uses high resolution flexible WRF data to chase for super cells and tornados in the USA during spring. Much effort is put into the development and improvement of the pre- and post-processing of the model. At MeteoGroup the static land-use data has been extended and adjusted to improve temperature and wind forecasts. The system has been modified such that sigma level input data from the global ECMWF model can be used for initialisation. By default only pressure level data could be used. During the spin-up of the model synoptical observations are nudged. A program to adjust possible initialisation errors of several surface parameters in coastal areas has been implemented. We developed an algorithm that computes cloud fractions using multiple direct model output variables. Forecasters prefer to use weather codes for their daily forecasts to detect severe weather. For this usage we developed model weather codes using a variety of direct model output and our own derived variables. 1 WRF® is a registered trademark of the University Corporation for Atmospheric Research (UCAR)

Do GCM's predict the climate.... Or the low frequency weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Schertzer, D.; Varon, D.

2012-04-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500 - 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT vary in power law manners ≈ Δt**H the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale (Δt). At longer scales Δt >τw (≈ 10 days) H changes sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime. In this regime, the spectrum is a relatively flat "plateau", it's variability is low, stable, corresponding to our usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, once again H>0, so that the variability increases with scale: the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, to define "climate states" as fluctuations at scale τc and then "climate change" as the fluctuations at longer periods (Δt>τc). We show that the intermediate low frequency weather regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched so that only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by stochastic cascade models of weather, but also by control runs (i.e. without climate forcing) of GCM based climate forecasting systems including those of the Institut Pierre Simon Laplace (Paris) and the Earth Forecasting System (Hamburg). In order for these systems to go beyond simply predicting low frequency weather i.e. in order for them to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. Using statistical scaling techniques we examine the scale dependence of fluctuations from forced and unforced GCM outputs, including from the ECHO-G and EFS simulations in the Millenium climate reconstruction project and compare this with data, multiproxies and paleo data. Our general conclusion is that the models systematically underestimate the multidecadal, multicentennial scale variability.

Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia

PubMed Central

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S.; McMichael, Anthony J.; Dale, Pat; Tong, Shilu

2006-01-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention. PMID:16675420

Modelling Pseudocalanus elongatus stage-structured population dynamics embedded in a water column ecosystem model for the northern North Sea

NASA Astrophysics Data System (ADS)

Moll, Andreas; Stegert, Christoph

2007-01-01

This paper outlines an approach to couple a structured zooplankton population model with state variables for eggs, nauplii, two copepodites stages and adults adapted to Pseudocalanus elongatus into the complex marine ecosystem model ECOHAM2 with 13 state variables resolving the carbon and nitrogen cycle. Different temperature and food scenarios derived from laboratory culture studies were examined to improve the process parameterisation for copepod stage dependent development processes. To study annual cycles under realistic weather and hydrographic conditions, the coupled ecosystem-zooplankton model is applied to a water column in the northern North Sea. The main ecosystem state variables were validated against observed monthly mean values. Then vertical profiles of selected state variables were compared to the physical forcing to study differences between zooplankton as one biomass state variable or partitioned into five population state variables. Simulated generation times are more affected by temperature than food conditions except during the spring phytoplankton bloom. Up to six generations within the annual cycle can be discerned in the simulation.

Assessing reference evapotranspiration at regional scale based on remote sensing, weather forecast and GIS tools

NASA Astrophysics Data System (ADS)

Ramírez-Cuesta, J. M.; Cruz-Blanco, M.; Santos, C.; Lorite, I. J.

2017-03-01

Reference evapotranspiration (ETo) is a key component in efficient water management, especially in arid and semi-arid environments. However, accurate ETo assessment at the regional scale is complicated by the limited number of weather stations and the strict requirements in terms of their location and surrounding physical conditions for the collection of valid weather data. In an attempt to overcome this limitation, new approaches based on the use of remote sensing techniques and weather forecast tools have been proposed. Use of the Land Surface Analysis Satellite Application Facility (LSA SAF) tool and Geographic Information Systems (GIS) have allowed the design and development of innovative approaches for ETo assessment, which are especially useful for areas lacking available weather data from weather stations. Thus, by identifying the best-performing interpolation approaches (such as the Thin Plate Splines, TPS) and by developing new approaches (such as the use of data from the most similar weather station, TS, or spatially distributed correction factors, CITS), errors as low as 1.1% were achieved for ETo assessment. Spatial and temporal analyses reveal that the generated errors were smaller during spring and summer as well as in homogenous topographic areas. The proposed approaches not only enabled accurate calculations of seasonal and daily ETo values, but also contributed to the development of a useful methodology for evaluating the optimum number of weather stations to be integrated into a weather station network and the appropriateness of their locations. In addition to ETo, other variables included in weather forecast datasets (such as temperature or rainfall) could be evaluated using the same innovative methodology proposed in this study.

Effects of weather conditions on emergency ambulance calls for acute coronary syndromes

NASA Astrophysics Data System (ADS)

Vencloviene, Jone; Babarskiene, Ruta; Dobozinskas, Paulius; Siurkaite, Viktorija

2015-08-01

The aim of this study was to evaluate the relationship between weather conditions and daily emergency ambulance calls for acute coronary syndromes (ACS). The study included data on 3631 patients who called the ambulance for chest pain and were admitted to the department of cardiology as patients with ACS. We investigated the effect of daily air temperature ( T), barometric pressure (BP), relative humidity, and wind speed (WS) to detect the risk areas for low and high daily volume (DV) of emergency calls. We used the classification and regression tree method as well as cluster analysis. The clusters were created by applying the k-means cluster algorithm using the standardized daily weather variables. The analysis was performed separately during cold (October-April) and warm (May-September) seasons. During the cold period, the greatest DV was observed on days of low T during the 3-day sequence, on cold and windy days, and on days of low BP and high WS during the 3-day sequence; low DV was associated with high BP and decreased WS on the previous day. During June-September, a lower DV was associated with low BP, windless days, and high BP and low WS during the 3-day sequence. During the warm period, the greatest DV was associated with increased BP and changing WS during the 3-day sequence. These results suggest that daily T, BP, and WS on the day of the ambulance call and on the two previous days may be prognostic variables for the risk of ACS.

Carbonate Mineral Weathering Contributions to the HCO3- Flux from Headwater Mid-latitude Streams in the Face of Increasing Atmospheric CO2

NASA Astrophysics Data System (ADS)

Szramek, K.; Ogrinc, N.; Walter, L. M.

2007-12-01

As anthropogenic liberated CO2 increases in the atmosphere, landscape level responses of the carbon cycle to perturbations associated with global warming are likely to be observed in carbonate bearing regions. Within physically open weathering environments, carbonate (calcite and dolomite) mineral solubility is proportional to pCO2 and inversely proportional to temperature, with the solubility of dolomite progressively greater than calcite below 25°C. Changes in weathering zone CO2 occur as CO2 drawdown is increased due to CO2 fertilization effects on plant growth, to warmer mean annual temperatures, or to land use changes. The rise in weathering zone CO2 will significantly augment the open system solubility of carbonate minerals and increase the DIC content of surface waters (unconfined groundwaters and rivers). The thermodynamic relationships between calcite and dolomite indicate the further need to examine the role of dolomite on the global riverine DIC budget. On a continental scale, the global weathering budget indicates the importance of northern hemisphere landmasses to riverine fluxes of Ca2+, Mg2+ and DIC as HCO3-. The results of a hydrogeochemical study of carbonate mineral equilibria and weathering fluxes for headwater streams within the Danube, the James and the St. Lawrence River Basins is presented. Available long-term geochemical and discharge data along with detailed catchment geochemical views of surface water and soil weathering zones were determined to examine the historical and current contribution of carbonate weathering to the geochemical fluctuations of the these headwater regions and the ability of these watersheds to maintain current conditions in the facing of increasing CO2. In order to gauge how these streams with variable climates, land use practices, lithologies, and weathering zone thicknesses compare to each other, river runoff and HCO3- concentrations are normalized to catchment area. The resulting carbonate weathering intensity on a global scale, shows the study regions exceeding the world average by factors of between 2 to 20. Within each stream, variability of HCO3- concentrations are minimal over a wide range of discharges indicating that carbonate weathering is not limited by solubility. A closer look at dolomite weathering contributions estimated from riverine Mg2+ fluxes exceeds the world average by factors between 2 to 15. Our results indicate that both calcite and dolomite mineral weathering within temperate zone watersheds will be able to carry an increased flux of HCO3- to the ocean as global atmospheric CO2 increases. In addition this work reinforces the significant contribution of dolomite weathering to the global HCO3- flux.

Development of a predictive model to estimate the effect of soil solarization on survival of soilborne inoculum of Phytophthora ramorum and Phytophthora pini

Treesearch

Fumiaki Funahashi; Jennifer L. Parke

2017-01-01

Soil solarization has been shown to be an effective tool to manage Phytophthora spp. within surface soils, but estimating the minimum time required to complete local eradication under variable weather conditions remains unknown. A mathematical model could help predict the effectiveness of solarization at different sites and soil depths....

Guidelines for disseminating road weather advisory & control information.

DOT National Transportation Integrated Search

2012-06-01

The tremendous growth in the amount of available weather and road condition informationincluding devices that gather weather information, models and forecasting tools for predicting weather conditions, and electronic devices used by travelersha...

Seasonality in trauma admissions - Are daylight and weather variables better predictors than general cyclic effects?

PubMed

Røislien, Jo; Søvik, Signe; Eken, Torsten

2018-01-01

Trauma is a leading global cause of death, and predicting the burden of trauma admissions is vital for good planning of trauma care. Seasonality in trauma admissions has been found in several studies. Seasonal fluctuations in daylight hours, temperature and weather affect social and cultural practices but also individual neuroendocrine rhythms that may ultimately modify behaviour and potentially predispose to trauma. The aim of the present study was to explore to what extent the observed seasonality in daily trauma admissions could be explained by changes in daylight and weather variables throughout the year. Retrospective registry study on trauma admissions in the 10-year period 2001-2010 at Oslo University Hospital, Ullevål, Norway, where the amount of daylight varies from less than 6 hours to almost 19 hours per day throughout the year. Daily number of admissions was analysed by fitting non-linear Poisson time series regression models, simultaneously adjusting for several layers of temporal patterns, including a non-linear long-term trend and both seasonal and weekly cyclic effects. Five daylight and weather variables were explored, including hours of daylight and amount of precipitation. Models were compared using Akaike's Information Criterion (AIC). A regression model including daylight and weather variables significantly outperformed a traditional seasonality model in terms of AIC. A cyclic week effect was significant in all models. Daylight and weather variables are better predictors of seasonality in daily trauma admissions than mere information on day-of-year.

An analysis of yield stability in a conservation agriculture system

USDA-ARS?s Scientific Manuscript database

Climate models predict increasing growing-season weather variability, with negative consequences for crop production. Maintaining agricultural productivity despite variability in weather (i.e., crop yield stability) will be critical to meeting growing global demand. Conservation agriculture is an ...

Weather variability and adaptive management for rangeland restoration

USDA-ARS?s Scientific Manuscript database

Inherent weather variability in upland rangeland systems requires relatively long-term goal setting, and contingency planning for partial success or failure in any given year. Rangeland plant communities are dynamic systems and successional planning is essential for achieving and maintaining system...

Solar-terrestrial influences on weather and climate; Proceedings of the Symposium, Ohio State University, Columbus, Ohio, August 24-28, 1978

NASA Technical Reports Server (NTRS)

Mccormac, B. M. (Editor); Seliga, T. A.

1979-01-01

The book contains most of the invited papers and contributions presented at the symposium/workshop on solar-terrestrial influences on weather and climate. Four main issues dominate the activities of the symposium: whether solar variability relationships to weather and climate is a fundamental scientific question to which answers may have important implications for long-term weather and climate prediction; the sun-weather relationships; other potential solar influences on weather including the 11-year sunspot cycle, the 27-day solar rotation, and special solar events such as flares and coronal holes; and the development of practical use of solar variability as a tool for weather and climatic forecasting, other than through empirical approaches. Attention is given to correlation topics; solar influences on global circulation and climate models; lower and upper atmospheric coupling, including electricity; planetary motions and other indirect factors; experimental approaches to sun-weather relationships; and the role of minor atmospheric constituents.

Analysis of weather condition influencing fire regime in Italy

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

The Application of Synoptic Weather Forecasting Rules to Selected Weather Situations in the United States.

ERIC Educational Resources Information Center

Kohler, Fred E.

The document describes the use of weather maps and data in teaching introductory college courses in synoptic meteorology. Students examine weather changes at three-hour intervals from data obtained from the "Monthly Summary of Local Climatological Data." Weather variables in the local summary include sky cover, air temperature, dew point, relative…

Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

NASA Astrophysics Data System (ADS)

Sanchez-Gomez, Emilia; Somot, S.; Déqué, M.

2009-10-01

One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.

[Effects of environmental factors on evapotranspiration characteristics of Haloxylon ammodendron plantation in the Minqin oasis-desert ectone, Northwest China.

PubMed

Zhang, Xiao Yan; Chu, Jian Min; Meng, Ping; Zheng, Ning; Yao, Zeng Wang; Wang, He Song; Jiang, Sheng Xiu

2016-08-01

This study continuously measured the evapotranspiration (ET) of degraded Haloxylon ammodendron shrub plantation of Minqin oasis-desert ectone using an eddy covariance system for ET, and TDR for soil moisture profile, analyzing ET in relation to the weather conditions and describing the responses of ET to the microclimate variables in different weather from July 2014 to June 2015. Results showed that the hourly ET dynamics had an apparent seasonal trend in the growing season. This trend gradually increased in the beginning of season from the low level of non-growing season, reached its maximum peak value (0.07 mm·h -1 ) in the most physiologically active period, and decreased to the minimum peak value (0.01 mm·h -1 ) in December. The diurnal change in ET of the plantation depended on the weather conditions. The ET fluctuated less with a small magnitude in a cloud day, but fluctuated obviously with a greater magnitude after rain if weather was clear. After a strong rainfall (>9 mm·d -1 ), ET increased sharply to a high level of 28 folds prior to rain, at which it took four clear days to gradually decease to the pre-rain ET level. The yearly ET over H. ammodendron plantation was 108 mm, equivalent to 98% of annual precipitation. Soil moisture was the water source for ET. Therefore, soil moisture was the dominant factor for theET over the plantation. Net radiation, photosynthesis active radiation, air temperature, and vapor pressure deficit were the microclimate variables to drive the transpiration of vegetation and evaporation over the soil surface, being the major factors forET over the plantation. The regression equation of ET to the dominant factor and major factors had a coefficient of multiple determination (R 2 ) over 0.80.

46 CFR 45.187 - Weather limitations.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Weather limitations. 45.187 Section 45.187 Shipping... River Barges on Lake Michigan Routes § 45.187 Weather limitations. (a) Tows on the Burns Harbor route must operate during fair weather conditions only. (b) The weather limits (ice conditions, wave height...

46 CFR 45.187 - Weather limitations.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 2 2012-10-01 2012-10-01 false Weather limitations. 45.187 Section 45.187 Shipping... River Barges on Lake Michigan Routes § 45.187 Weather limitations. (a) Tows on the Burns Harbor route must operate during fair weather conditions only. (b) The weather limits (ice conditions, wave height...

46 CFR 45.187 - Weather limitations.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 2 2014-10-01 2014-10-01 false Weather limitations. 45.187 Section 45.187 Shipping... River Barges on Lake Michigan Routes § 45.187 Weather limitations. (a) Tows on the Burns Harbor route must operate during fair weather conditions only. (b) The weather limits (ice conditions, wave height...

46 CFR 45.187 - Weather limitations.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 2 2011-10-01 2011-10-01 false Weather limitations. 45.187 Section 45.187 Shipping... River Barges on Lake Michigan Routes § 45.187 Weather limitations. (a) Tows on the Burns Harbor route must operate during fair weather conditions only. (b) The weather limits (ice conditions, wave height...

46 CFR 45.187 - Weather limitations.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 2 2013-10-01 2013-10-01 false Weather limitations. 45.187 Section 45.187 Shipping... River Barges on Lake Michigan Routes § 45.187 Weather limitations. (a) Tows on the Burns Harbor route must operate during fair weather conditions only. (b) The weather limits (ice conditions, wave height...

Disruptions of El Niño–Southern Oscillation teleconnections by the Madden–Julian Oscillation

USGS Publications Warehouse

Hoell, Andrew; Barlow, Mathew; Wheeler, Mathew; Funk, Christopher C.

2014-01-01

The El Niño–Southern Oscillation (ENSO) is the leading mode of interannual variability, with global impacts on weather and climate that have seasonal predictability. Research on the link between interannual ENSO variability and the leading mode of intraseasonal variability, the Madden–Julian oscillation (MJO), has focused mainly on the role of MJO initiating or terminating ENSO. We use observational analysis and modeling to show that the MJO has an important simultaneous link to ENSO: strong MJO activity significantly weakens the atmospheric branch of ENSO. For weak MJO conditions relative to strong MJO conditions, the average magnitude of ENSO-associated tropical precipitation anomalies increases by 63%, and the strength of hemispheric teleconnections increases by 58%. Since the MJO has predictability beyond three weeks, the relationships shown here suggest that there may be subseasonal predictability of the ENSO teleconnections to continental circulation and precipitation.

Tactical Versus Strategic Behavior: General Aviation Piloting in Convective Weather Scenarios

NASA Technical Reports Server (NTRS)

Latorella, Kara A.; Chamberlain, James P.

2002-01-01

We commonly describe environments and behavioral responses to environmental conditions as 'tactical' and 'strategic.' However theoretical research defining relevant environmental characteristics is rare, as are empirical investigations that would inform such theory. This paper discusses General Aviation (GA) pilots' descriptions of tactical/strategic conditions with respect to weather flying, and evaluates their ratings along a tactical/strategic scale in response to real convective weather scenarios experienced during a flight experiment with different weather information cues. Perceived risk was significantly associated with ratings for all experimental conditions. In addition, environmental characteristics were found to be predictive of ratings for Traditional IMC (instrument meteorological conditions), i.e., aural weather information only, and Traditional VMC (visual meteorological conditions), i.e., aural information and an external view. The paper also presents subjects' comments regarding use of Graphical Weather Information Systems (GWISs) to support tactical and strategic weather flying decisions and concludes with implications for the design and use of GWISs.

Nonlinear dynamics of global atmospheric and Earth-system processes

NASA Technical Reports Server (NTRS)

Saltzman, Barry; Ebisuzaki, Wesley; Maasch, Kirk A.; Oglesby, Robert; Pandolfo, Lionel

1990-01-01

Researchers are continuing their studies of the nonlinear dynamics of global weather systems. Sensitivity analyses of large-scale dynamical models of the atmosphere (i.e., general circulation models i.e., GCM's) were performed to establish the role of satellite-signatures of soil moisture, sea surface temperature, snow cover, and sea ice as crucial boundary conditions determining global weather variability. To complete their study of the bimodality of the planetary wave states, they are using the dynamical systems approach to construct a low-order theoretical explanation of this phenomenon. This work should have important implications for extended range forecasting of low-frequency oscillations, elucidating the mechanisms for the transitions between the two wave modes. Researchers are using the methods of jump analysis and attractor dimension analysis to examine the long-term satellite records of significant variables (e.g., long wave radiation, and cloud amount), to explore the nature of mode transitions in the atmosphere, and to determine the minimum number of equations needed to describe the main weather variations with a low-order dynamical system. Where feasible they will continue to explore the applicability of the methods of complex dynamical systems analysis to the study of the global earth-system from an integrative viewpoint involving the roles of geochemical cycling and the interactive behavior of the atmosphere, hydrosphere, and biosphere.

Poorly Crystalline, Iron-Bearing Aluminosilicates and Their Importance on Mars

NASA Technical Reports Server (NTRS)

Baker, L. L.; Strawn, D. G.; McDaniel, P. A.; Nickerosn, R. N.; Bishop, J. L.; Ming, D. W.; Morris, Richard V.

2011-01-01

Martian rocks and sediments contain weathering products including evaporite salts and clay minerals that only form as a result of interaction between rocks and water [1-6]. These weathering products are key to studying the history of water on Mars because their type, abundance and location provide clues to past conditions on the surface of the planet, as well as to the possible location of present-day reservoirs of water. Weathering of terrestrial volcanic rocks similar to those on Mars produces nano-sized, variably hydrated aluminosilicate and iron oxide minerals [7-10] including allophane, imogolite, halloysite, hisingerite, and ferrihydrite. The nanoaluminosilicates can contain isomorphically substituted Fe, which affects their spectral and physical properties. Detection and quantification of such minerals in natural environments on earth is difficult due to their variable chemical composition and lack of long-range crystalline order [9, 11, 12]. Despite the difficulty in characterizing these materials, they are common on Earth, and data from orbital remote sensing and rover-based instruments suggest that they are also present on Mars [9, 10, 13-17]. Their accurate detection and quantification require a better understanding of how composition affects their spectral properties. We present here the results of XAFS spectroscopy; these results will be corroborated with planned Mossbauer and reflectance spectroscopy.

Using weather data to improve decision-making

USDA-ARS?s Scientific Manuscript database

Weather in the western United States is relatively dry and highly variable. The consequences of this variability can be effectively dealt with through the process of adaptive management which includes contingency planning for partial restoration success or restoration failure in any given year. Pr...

Improving the performance of air-conditioning systems in an ASEAN (Association of South East Asian Nations) climate

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

Busch, J.F.; Warren, M.L.

1988-09-01

This paper describes an analysis of air conditioning performance under hot and humid tropical climate conditions appropriate to the Association of South East Asian Nations (ASEAN) countries. This region, with over 280 million people, has one of the fastest economic and energy consumption growth rates in the world. The work reported here is aimed at estimating the conservation potential derived from good design and control of air conditioning systems in commercial buildings. To test the performance of different air conditioning system types and control options, whole building energy performance was simulated using DOE-2. The 5100 m/sup 2/ (50,000 ft/sup 2/)more » prototype office building module was previously used in earlier commercial building energy standards analysis for Malaysia and Singapore. In general, the weather pattern for ASEAN countries is uniform, with hot and humid air masses known as ''monsoons'' dictating the weather patterns. Since a concentration of cities occurs near the tip of the Malay peninsula, hourly temperature, humidity, and wind speed data for Kuala Lumpur was used for the analysis. Because of the absence of heating loads in ASEAN regions, we have limited air conditioning configurations to two pipe fan coil, constant volume, variable air volume, powered induction, and ceiling bypass configurations. Control strategies were varied to determine the conservation potential in both energy use and peak electric power demands. Sensitivities including fan control, pre-cooling and night ventilation, supply air temperature control, zone temperature set point, ventilation and infiltration, daylighting and internal gains, and system sizing were examined and compared with a base case which was a variable air volume system with no reheat or economizer. Comfort issues, such as over-cooling and space humidity, were also examined.« less

Weather Condition dominates the Regional PM2.5 Pollutions in the Eastern Coastal Provinces of China during winter

NASA Astrophysics Data System (ADS)

Cai, Zhe; Jiang, Fei; Chen, Jingming; Jiang, Ziqiang

2017-04-01

China has been suffering from severe particulate matter (PM) pollution in recent years. Both pollution area and pollution levels are increasing gradually. The PM pollution episodes not only occur in the traditional developed areas like Yangtze River Delta (YRD) and Beijing-Tianjin-Hebei (BTH) region, but also frequently happen in the whole eastern coastal provinces (ECPs) of China. Based on hourly PM2.5 concentrations during December 2013 February 2014 of 55 cities located in the ECPs, we investigated the spatial and temporal variabilities of PM2.5 concentrations and the corresponding meteorological conditions during winter. The results shown that basically the seasonal mean concentrations over the whole ECPs exceeded the China's national standard of 75 μg/m3, and the most polluted area with mean concentrations greater than 150 μg/m3 were located in the southwest of Hebei and the west of Shandong provinces. From December to February, there was a decrease trend for the PM2.5 pollution in most areas, especially in the YRD region, while the PM2.5 concentrations over north of Hebei province increased. The spatial distributions and monthly variations are strongly related to the weather conditions. Overall, severe PM pollution was corresponding to a stable weather condition, i.e., small Sea Level Pressure (SLP) gradient, lower Planetary Boundary Layer (PBL) height and weaker wind fields. Statistics shown that the changes of mean PM2.5 concentrations over the ECPs region usually lagged behind the variations of PBL height and wind speeds about 12 18 hours. The variations of weather conditions could explain about 71% (R2) of the overall changes of PM2.5 concentrations in the ECPs region. This study gives a full insight into the PM2.5 pollution in the area of eastern coastal provinces of China during winter, which would be helpful to predict and control the PM2.5 pollution for this area in the future.

Effects of synoptic patterns on atmospheric chemistry and aerosols during the Arctic Ocean Expedition 1996

NASA Astrophysics Data System (ADS)

Nilsson, E. Douglas; Barr, Sumner

2001-12-01

The atmospheric program on the Arctic Ocean Expedition of July through September 1996 (AOE-96) was focused on aerosol climate feedback. The expedition took place close to the saddle point between a semipersistent anticyclonic ridge from near Scandinavia to the Arctic coast of eastern Siberia and a trough from the Canadian archipelago across the pole to north central Siberia. The weather varied from anticyclonic clear-sky conditions to cyclonic cloudy conditions, and 13 identifiable migratory features (frontal bands, wave disturbances) clearly influenced local weather, clouds, atmospheric transport, and chemistry. This includes an explosive polar cyclone, born at the lateral heat gradient between Greenland and the pack ice rather than between open sea and the pack ice. The synoptic scale weather systems caused the strongest variability in trace gases (O3 in particular) and aerosols, and also strong variability in the cloud cover. The formation of air masses over the pack ice primarily depends on if there is cyclonic (convergent) or anticyclonic (divergent) flow. Cyclonic flow resulted in a modified marine air mass loaded with vapor, but with low aerosol number concentrations owing to frequent clouds and fogs and efficient cloud scavenging of the aerosol. Anticyclonic flow resulted in almost continental air masses with clear sky, long residence time over the pack ice and subsidence slowly replacing the boundary layer with free tropospheric air, low vapor concentrations, but large aerosol number in lack of efficient cloud scavenging. The synoptic variability and advection from south of the ice edge were weaker than during the predecessor International Arctic Ocean Expedition in 1991 (IAOE-91), when on average the sampled air spent 55 hours over the pack ice compared to more than 120 hours during AOE-96, owing to exceptionally high cyclone activity in 1991. This caused a large difference in atmospheric transport, chemistry, and aerosols between the two expeditions.

Effects of genotype, latitude, and weather conditions on the composition of sugars, sugar alcohols, fruit acids, and ascorbic acid in sea buckthorn (Hippophaë rhamnoides ssp. mongolica) berry juice.

PubMed

Zheng, Jie; Yang, Baoru; Trépanier, Martin; Kallio, Heikki

2012-03-28

Sea buckthorn berries (Hippophaë rhamnoides ssp. mongolica) of nine varieties were collected from three growth locations in five inconsecutive years (n = 152) to study the compositional differences of sugars, sugar alcohols, fruit acids, and ascorbic acid in berries of different genotypes. Fructose and glucose (major sugars) were highest in Chuiskaya and Vitaminaya among the varieties studied, respectively. Malic acid and quinic acid (major acids) were highest in Pertsik and Vitaminaya, respectively. Ascorbic acid was highest in Oranzhevaya and lowest in Vitaminaya. Berry samples of nine varieties collected from two growth locations in five years (n = 124) were combined to study the effects of latitude and weather conditions on the composition of H. rhamnoides ssp. mongolica. Sea buckthorn berries grown at lower latitude had higher levels of total sugar and sugar/acid ratio and a lower level of total acid and were supposed to have better sensory properties than those grown at higher latitude. Glucose, quinic acid, and ascorbic acid were hardly influenced by weather conditions. The other components showed various correlations with temperature, radiation, precipitation, and humidity variables. In addition, fructose, sucrose, and myo-inositol correlated positively with each other and showed negative correlation with malic acid on the basis of all the samples studied (n = 152).

Metal stable isotopes in weathering and hydrology: Chapter 10

USGS Publications Warehouse

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

2014-01-01

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

Testing and Evaluation of Preliminary Design Guidelines for Disseminating Road Weather Advisory & Control Information

DOT National Transportation Integrated Search

2012-06-01

The tremendous growth in the amount of available weather and road condition informationincluding devices that gather weather information, models and forecasting tools for predicting weather conditions, and electronic devices used by travelersha...

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Interannual Atmospheric Variability Simulated by a Mars GCM: Impacts on the Polar Regions

NASA Technical Reports Server (NTRS)

Bridger, Alison F. C.; Haberle, R. M.; Hollingsworth, J. L.

2003-01-01

It is often assumed that in the absence of year-to-year dust variations, Mars weather and climate are very repeatable, at least on decadal scales. Recent multi-annual simulations of a Mars GCM reveal however that significant interannual variations may occur with constant dust conditions. In particular, interannual variability (IAV) appears to be associated with the spectrum of atmospheric disturbances that arise due to baroclinic instability. One quantity that shows significant IAV is the poleward heat flux associated with these waves. These variations and their impacts on the polar heat balance will be examined here.

Acute Low Back Pain? Do Not Blame the Weather-A Case-Crossover Study.

PubMed

Beilken, Keira; Hancock, Mark J; Maher, Chris G; Li, Qiang; Steffens, Daniel

2017-06-01

To investigate the influence of various weather parameters on the risk of developing a low back pain (LBP) episode. Case-crossover study. Primary care clinics in Sydney, Australia. 981 participants with a new episode of acute LBP. Weather parameters were obtained from the Australian Bureau of Meteorology. Odds ratios (OR) and 95% confidence intervals (95% CI) were derived comparing two exposure variables in the case window-(1) the average of the weather variable for the day prior to pain onset and (2) the change in the weather variable from 2 days prior to 1 day prior to pain onset-with exposures in two control windows (1 week and 1 month before the case window). The weather parameters of precipitation, humidity, wind speed, wind gust, wind direction, and air pressure were not associated with the onset of acute LBP. For one of the four analyses, higher temperature slightly increased the odds of pain onset. Common weather parameters that had been previously linked to musculoskeletal pain, such as precipitation, humidity, wind speed, wind gust, wind direction, and air pressure, do not increase the risk of onset for LBP. © 2016 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Optimization of agricultural field workability predictions for improved risk management

USDA-ARS?s Scientific Manuscript database

Risks introduced by weather variability are key considerations in agricultural production. The sensitivity of agriculture to weather variability is of special concern in the face of climate change. In particular, the availability of workable days is an important consideration in agricultural practic...

Importance of scale, land cover, and weather on the abundance of bird species in a managed forest

USGS Publications Warehouse

Grinde, Alexis R.; Hiemi, Gerald J.; Sturtevant, Brian R.; Panci, Hannah; Thogmartin, Wayne E.; Wolter, Peter

2017-01-01

Climate change and habitat loss are projected to be the two greatest drivers of biodiversity loss over the coming century. While public lands have the potential to increase regional resilience of bird populations to these threats, long-term data are necessary to document species responses to changes in climate and habitat to better understand population vulnerabilities. We used generalized linear mixed models to determine the importance of stand-level characteristics, multi-scale land cover, and annual weather factors to the abundance of 61 bird species over a 20-year time frame in Chippewa National Forest, Minnesota, USA. Of the 61 species modeled, we were able to build final models with R-squared values that ranged from 26% to 69% for 37 species; the remaining 24 species models had issues with convergence or low explanatory power (R-squared < 20%). Models for the 37 species show that stand-level characteristics, land cover factors, and annual weather effects on species abundance were species-specific and varied within guilds. Forty-one percent of the final species models included stand-level characteristics, 92% included land cover variables at the 200 m scale, 51% included land cover variables at the 500 m scale, 46% included land cover variables at the 1000 m scale, and 38% included weather variables in best models. Three species models (8%) included significant weather and land cover interaction terms. Overall, models indicated that aboveground tree biomass and land cover variables drove changes in the majority of species. Of those species models including weather variables, more included annual variation in precipitation or drought than temperature. Annual weather variability was significantly more likely to impact abundance of species associated with deciduous forests and bird species that are considered climate sensitive. The long-term data and models we developed are particularly suited to informing science-based adaptive forest management plans that incorporate climate sensitivity, aim to conserve large areas of forest habitat, and maintain an historical mosaic of cover types for conserving a diverse and abundant avian assemblage.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Geoelectrical characterisation of basement aquifers: the case of Iberekodo, southwestern Nigeria

NASA Astrophysics Data System (ADS)

Aizebeokhai, Ahzegbobor P.; Oyeyemi, Kehinde D.

2018-03-01

Basement aquifers, which occur within the weathered and fractured zones of crystalline bedrocks, are important groundwater resources in tropical and subtropical regions. The development of basement aquifers is complex owing to their high spatial variability. Geophysical techniques are used to obtain information about the hydrologic characteristics of the weathered and fractured zones of the crystalline basement rocks, which relates to the occurrence of groundwater in the zones. The spatial distributions of these hydrologic characteristics are then used to map the spatial variability of the basement aquifers. Thus, knowledge of the spatial variability of basement aquifers is useful in siting wells and boreholes for optimal and perennial yield. Geoelectrical resistivity is one of the most widely used geophysical methods for assessing the spatial variability of the weathered and fractured zones in groundwater exploration efforts in basement complex terrains. The presented study focuses on combining vertical electrical sounding with two-dimensional (2D) geoelectrical resistivity imaging to characterise the weathered and fractured zones in a crystalline basement complex terrain in southwestern Nigeria. The basement aquifer was delineated, and the nature, extent and spatial variability of the delineated basement aquifer were assessed based on the spatial variability of the weathered and fractured zones. The study shows that a multiple-gradient array for 2D resistivity imaging is sensitive to vertical and near-surface stratigraphic features, which have hydrological implications. The integration of resistivity sounding with 2D geoelectrical resistivity imaging is efficient and enhances near-surface characterisation in basement complex terrain.

Weather Augmented Risk Determination (WARD) System

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Do GCM's Predict the Climate.... Or the Low Frequency Weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Varon, D.; Schertzer, D. J.

2011-12-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500- 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT ≈ ΔtH the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale. At longer scales Δt >τw (≈ 10 days) they change sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime the spectrum is a relatively flat "plateau", it's variability is that of the usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, again H>0, the variability again increases with scale. This is the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, "climate states", as fluctuations at scale τc and "climate change" as the fluctuations at longer periods >τc). We show that the intermediate regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched, only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by weather cascade models, but also by control runs (i.e. without climate forcing) of GCM's (including IPSL and ECHAM GCM's). In order for GCM's to go beyond simply predicting this low frequency weather so as to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. We examine this using wavelet analyses of forced and unforced GCM outputs, including the ECHO-G simulation used in the Millenium project. For example, we find that climate scenarios with large CO2 increases do give rise to a climate regime but that Hc>1 i.e. much larger than that of natural variability which for temperatures has Hc≈0.4. In comparison, the (largely volcanic) forcing of the ECHO-G Millenium simulation is fairly realistic (Hc≈0.4), although it is not clear that this mechanism can explain the even lower frequency variability found in the paleotemperature series, nor is it clear that this is compatible with low frequency solar or orbital forcings.

Quantifying the effect of interannual ocean variability on the attribution of extreme climate events to human influence

NASA Astrophysics Data System (ADS)

Risser, Mark D.; Stone, Dáithí A.; Paciorek, Christopher J.; Wehner, Michael F.; Angélil, Oliver

2017-11-01

In recent years, the climate change research community has become highly interested in describing the anthropogenic influence on extreme weather events, commonly termed "event attribution." Limitations in the observational record and in computational resources motivate the use of uncoupled, atmosphere/land-only climate models with prescribed ocean conditions run over a short period, leading up to and including an event of interest. In this approach, large ensembles of high-resolution simulations can be generated under factual observed conditions and counterfactual conditions that might have been observed in the absence of human interference; these can be used to estimate the change in probability of the given event due to anthropogenic influence. However, using a prescribed ocean state ignores the possibility that estimates of attributable risk might be a function of the ocean state. Thus, the uncertainty in attributable risk is likely underestimated, implying an over-confidence in anthropogenic influence. In this work, we estimate the year-to-year variability in calculations of the anthropogenic contribution to extreme weather based on large ensembles of atmospheric model simulations. Our results both quantify the magnitude of year-to-year variability and categorize the degree to which conclusions of attributable risk are qualitatively affected. The methodology is illustrated by exploring extreme temperature and precipitation events for the northwest coast of South America and northern-central Siberia; we also provides results for regions around the globe. While it remains preferable to perform a full multi-year analysis, the results presented here can serve as an indication of where and when attribution researchers should be concerned about the use of atmosphere-only simulations.

How potentially predictable are midlatitude ocean currents?

PubMed Central

Nonaka, Masami; Sasai, Yoshikazu; Sasaki, Hideharu; Taguchi, Bunmei; Nakamura, Hisashi

2016-01-01

Predictability of atmospheric variability is known to be limited owing to significant uncertainty that arises from intrinsic variability generated independently of external forcing and/or boundary conditions. Observed atmospheric variability is therefore regarded as just a single realization among different dynamical states that could occur. In contrast, subject to wind, thermal and fresh-water forcing at the surface, the ocean circulation has been considered to be rather deterministic under the prescribed atmospheric forcing, and it still remains unknown how uncertain the upper-ocean circulation variability is. This study evaluates how much uncertainty the oceanic interannual variability can potentially have, through multiple simulations with an eddy-resolving ocean general circulation model driven by the observed interannually-varying atmospheric forcing under slightly different conditions. These ensemble “hindcast” experiments have revealed substantial uncertainty due to intrinsic variability in the extratropical ocean circulation that limits potential predictability of its interannual variability, especially along the strong western boundary currents (WBCs) in mid-latitudes, including the Kuroshio and its eastward extention. The intrinsic variability also greatly limits potential predictability of meso-scale oceanic eddy activity. These findings suggest that multi-member ensemble simulations are essential for understanding and predicting variability in the WBCs, which are important for weather and climate variability and marine ecosystems. PMID:26831954

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Catalog of Air Force Weather Technical Documents, 1941-2006

DTIC Science & Technology

2006-05-19

radiosondes in current use in USA. Elementary discussion of statistical terms and concepts used for expressing accuracy or error is discussed. AWS TR 105...Techniques, Appendix B: Vorticity—An Elementary Discussion of the Concept, August 1956, 27pp. Formerly AWSM 105– 50/1A. Provides the necessary back...steps involved in ordinary multiple linear regression. Conditional probability is calculated using transnormalized variables in the multivariate normal

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

NASA Astrophysics Data System (ADS)

Eck, Pamela

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

Spatial synchrony of local populations has increased in association with the recent Northern Hemisphere climate trend.

PubMed

Post, Eric; Forchhammer, Mads C

2004-06-22

According to ecological theory, populations whose dynamics are entrained by environmental correlation face increased extinction risk as environmental conditions become more synchronized spatially. This prediction is highly relevant to the study of ecological consequences of climate change. Recent empirical studies have indicated, for example, that large-scale climate synchronizes trophic interactions and population dynamics over broad spatial scales in freshwater and terrestrial systems. Here, we present an analysis of century-scale, spatially replicated data on local weather and the population dynamics of caribou in Greenland. Our results indicate that spatial autocorrelation in local weather has increased with large-scale climatic warming. This increase in spatial synchrony of environmental conditions has been matched, in turn, by an increase in the spatial synchrony of local caribou populations toward the end of the 20th century. Our results indicate that spatial synchrony in environmental conditions and the populations influenced by them are highly variable through time and can increase with climatic warming. We suggest that if future warming can increase population synchrony, it may also increase extinction risk.

Preventing cold-related morbidity and mortality in a changing climate

PubMed Central

Conlon, Kathryn C; Rajkovich, Nicholas B; White-Newsome, Jalonne L; Larsen, Larissa; Neill, Marie S O

2011-01-01

Winter weather patterns are anticipated to become more variable with increasing average global temperatures. Research shows that excess morbidity and mortality occurs during cold weather periods. We critically reviewed evidence relating temperature variability, health outcomes, and adaptation strategies to cold weather. Health outcomes included cardiovascular-, respiratory-, cerebrovascular-, and all-cause morbidity and mortality. Individual and contextual risk factors were assessed to highlight associations between individual- and neighborhood- level characteristics that contribute to a person’s vulnerability to variability in cold weather events. Epidemiologic studies indicate that the populations most vulnerable to variations in cold winter weather are the elderly, rural and, generally, populations living in moderate winter climates. Fortunately, cold-related morbidity and mortality are preventable and strategies exist for protecting populations from these adverse health outcomes. We present a range of adaptation strategies that can be implemented at the individual, building, and neighborhood level to protect vulnerable populations from cold-related morbidity and mortality. The existing research justifies the need for increased outreach to individuals and communities for education on protective adaptations in cold weather. We propose that future climate change adaptation research couple building energy and thermal comfort models with epidemiological data to evaluate and quantify the impacts of adaptation strategies. PMID:21592693

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

PubMed

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

2016-12-01

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

A Bayesian hierarchical model with spatial variable selection: the effect of weather on insurance claims

PubMed Central

Scheel, Ida; Ferkingstad, Egil; Frigessi, Arnoldo; Haug, Ola; Hinnerichsen, Mikkel; Meze-Hausken, Elisabeth

2013-01-01

Climate change will affect the insurance industry. We develop a Bayesian hierarchical statistical approach to explain and predict insurance losses due to weather events at a local geographic scale. The number of weather-related insurance claims is modelled by combining generalized linear models with spatially smoothed variable selection. Using Gibbs sampling and reversible jump Markov chain Monte Carlo methods, this model is fitted on daily weather and insurance data from each of the 319 municipalities which constitute southern and central Norway for the period 1997–2006. Precise out-of-sample predictions validate the model. Our results show interesting regional patterns in the effect of different weather covariates. In addition to being useful for insurance pricing, our model can be used for short-term predictions based on weather forecasts and for long-term predictions based on downscaled climate models. PMID:23396890

Untangling the contribution of aspect, drainage position and elevation to the spatial variability of fine surface fuels in south east Australian forests

NASA Astrophysics Data System (ADS)

Sheridan, Gary; nyman, petter; Duff, Tom; Baillie, Craig; Bovill, William; Lane, Patrick; Tolhurst, Kevin

2015-04-01

The prediction of fuel moisture content is important for estimating the rate of spread of wildfires, the ignition probability of firebrands, and for the efficient scheduling of prescribed fire. The moisture content of fine surface fuels varies spatially at large scales (10's to 100's km) due to variation in meteorological variables (eg. temperature, relative humidity, precipitation). At smaller scales (100's of metres) in steep topography spatial variability is attributed to topographic influences that include differences in radiation due to aspect and slope, differences in precipitation, temperature and relative humidity due to elevation, and differences in soil moisture due to hillslope drainage position. Variable forest structure and canopy shading adds further to the spatial variability in surface fuel moisture. In this study we aim to combine daily 5km resolution gridded weather data with 20m resolution DEM and vegetation structure data to predict the spatial variability of fine surface fuels in steep topography. Microclimate stations were established in south east Australia to monitor surface fine fuel moisture continuously (every 15 minutes) using newly developed instrumented litter packs, in addition to temperature and relative humidity measurements inside the litter pack, and measurement of precipitation and energy inputs above and below the forest canopy. Microclimate stations were established across a gradient of aspect (5 stations), drainage position (7 stations), elevation (15 stations), and canopy cover conditions (6 stations). The data from this extensive network of microclimate stations across a broad spectrum of topographic conditions is being analysed to enable the downscaling of gridded weather data to spatial scales that are relevant to the connectivity of wildfire fuels and to the scheduling and outcome of prescribed fires. The initial results from the first year of this study are presented here.

Lincoln Laboratory demonstrates highly accurate vehicle localization under adverse weather conditions

DTIC Science & Technology

2016-05-25

2016 Lincoln Laboratory demonstrates highly accurate vehicle localization under adverse weather conditions A ground-penetrating radar system...the problems limiting the development and adoption of self-driving vehicles: how can a vehicle navigate to stay within its lane when bad weather ... weather conditions, but it is challenging, even impossible, for them to work when snow covers the markings and surfaces or precipitation obscures points

Seeing is Believing? An Examination of Perceptions of Local Weather Conditions and Climate Change Among Residents in the U.S. Gulf Coast.

PubMed

Shao, Wanyun; Goidel, Kirby

2016-11-01

What role do objective weather conditions play in coastal residents' perceptions of local climate shifts and how do these perceptions affect attitudes toward climate change? While scholars have increasingly investigated the role of weather and climate conditions on climate-related attitudes and behaviors, they typically assume that residents accurately perceive shifts in local climate patterns. We directly test this assumption using the largest and most comprehensive survey of Gulf Coast residents conducted to date supplemented with monthly temperature data from the U.S. Historical Climatology Network and extreme weather events data from National Climatic Data Center. We find objective conditions have limited explanatory power in determining perceptions of local climate patterns. Only the 15- and 19-year hurricane trends and decadal summer temperature trend have some effects on perceptions of these weather conditions, while the decadal trend of total number of extreme weather events and 15- and 19-year winter temperature trends are correlated with belief in climate change. Partisan affiliation, in contrast, plays a powerful role affecting individual perceptions of changing patterns of air temperatures, flooding, droughts, and hurricanes, as well as belief in the existence of climate change and concern for future consequences. At least when it comes to changing local conditions, "seeing is not believing." Political orientations rather than local conditions drive perceptions of local weather conditions and these perceptions-rather than objectively measured weather conditions-influence climate-related attitudes. © 2016 Society for Risk Analysis.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Associations between weather conditions during the first 45 days after feedlot arrival and daily respiratory disease risks in autumn-placed feeder cattle in the United States.

PubMed

Cernicchiaro, N; Renter, D G; White, B J; Babcock, A H; Fox, J T

2012-04-01

Data on associations between weather conditions and bovine respiratory disease (BRD) morbidity in autumn-placed feedlot cattle are sparse. The goal of our study was to quantify how different weather variables during corresponding lag periods (considering up to 7 d before the day of disease measure) were associated with daily BRD incidence during the first 45 d of the feeding period based on a post hoc analysis of existing feedlot operational data. Our study population included 1,904 cohorts of feeder cattle (representing 288,388 total cattle) that arrived to 9 US commercial feedlots during September to November in 2005 to 2007. There were 24,947 total cases of initial respiratory disease (animals diagnosed by the feedlots with BRD and subsequently treated with an antimicrobial). The mean number of BRD cases during the study period (the first 45 d after arrival) was 0.3 cases per day per cohort (range = 0 to 53.0), and cumulative BRD incidence risks ranged from 0 to 36% within cattle cohorts. Data were analyzed with a multivariable mixed-effects binomial regression model. Results indicate that several weather factors (maximum wind speed, mean wind chill temperature, and temperature change in different lag periods) were significantly (P < 0.05) associated with increased daily BRD incidence, but their effects depended on several cattle demographic factors (month of arrival, BRD risk code, BW class, and cohort size). In addition, month and year of arrival, sex of the cohort, days on feed, mean BW of the cohort at entry, predicted BRD risk designation of the cohort (high or low risk), cohort size, and the interaction between BRD risk code and arrival year were significantly (P < 0.05) associated with daily BRD incidence. Our results demonstrate that weather conditions are significantly associated with BRD risk in populations of feedlot cattle. Defining these conditions for specific cattle populations may enable cattle health managers to predict and potentially manage these effects more effectively; further, estimates of effects may contribute to the development of quantitative predictive models for this important disease syndrome.

Seasonal weather-related decision making for cattle production in the Northern Great Plains

USDA-ARS?s Scientific Manuscript database

High inter-annual variability of seasonal weather patterns can greatly affect forage and therefore livestock production in the Northern Great Plains. This variability can make it difficult for ranchers to set yearly stocking rates, particularly in advance of the grazing season. To better understand ...

Statistical analysis of agronomical factors and weather conditions influencing deoxynivalenol levels in oats in Scandinavia.

PubMed

Lindblad, M; Börjesson, T; Hietaniemi, V; Elen, O

2012-01-01

The relationship between weather data and agronomical factors and deoxynivalenol (DON) levels in oats was examined with the aim of developing a predictive model. Data were collected from a total of 674 fields during periods of up to 10 years in Finland, Norway and Sweden, and included DON levels in the harvested oats crop, agronomical factors and weather data. The results show that there was a large regional variation in DON levels, with higher levels in one region in Norway compared with other regions in Norway, Finland and Sweden. In this region the median DON level was 1000 ng g⁻¹ and the regulatory limit for human consumption (1750 ng g⁻¹) was exceeded in 28% of the samples. In other regions the median DON levels ranged from 75 to 270 ng g⁻¹, and DON levels exceeded 1750 ng g⁻¹ in 3-8% of the samples. Including more variables than region in a multiple regression model only increased the adjusted coefficient of determination from 0.17 to 0.24, indicating that very little of the variation in DON levels could be explained by weather data or agronomical factors. Thus, it was not possible to predict DON levels based on the variables included in this study. Further studies are needed to solve this problem. Apparently the infection and/or growth of DON producing Fusarium species are promoted in certain regions. One possibility may be to study the species distribution of fungal communities and their changes during the oats cultivation period in more detail.

Using regression analysis to predict emergency patient volume at the Indianapolis 500 mile race.

PubMed

Bowdish, G E; Cordell, W H; Bock, H C; Vukov, L F

1992-10-01

Emergency physicians often plan and provide on-site medical care for mass gatherings. Most of the mass gathering literature is descriptive. Only a few studies have looked at factors such as crowd size, event characteristics, or weather in predicting numbers and types of patients at mass gatherings. We used regression analysis to relate patient volume on Race Day at the Indianapolis Motor Speedway to weather conditions and race characteristics. Race Day weather data for the years 1983 to 1989 were obtained from the National Oceanic and Atmospheric Administration. Data regarding patients treated on 1983 to 1989 Race Days were obtained from the facility hospital (Hannah Emergency Medical Center) data base. Regression analysis was performed using weather factors and race characteristics as independent variables and number of patients seen as the dependent variable. Data from 1990 were used to test the validity of the model. There was a significant relationship between dew point (which is calculated from temperature and humidity) and patient load (P less than .01). Dew point, however, failed to predict patient load during the 1990 race. No relationships could be established between humidity, sunshine, wind, or race characteristics and number of patients. Although higher dew point was associated with higher patient load during the 1983 to 1989 races, dew point was a poor predictor of patient load during the 1990 race. Regression analysis may be useful in identifying relationships between event characteristics and patient load but is probably inadequate to explain the complexities of crowd behavior and too simplified to use as a prediction tool.

The relationship between wind power, electricity demand and winter weather patterns in Great Britain

NASA Astrophysics Data System (ADS)

Thornton, Hazel E.; Scaife, Adam A.; Hoskins, Brian J.; Brayshaw, David J.

2017-06-01

Wind power generation in Great Britain has increased markedly in recent years. However due to its intermittency its ability to provide power during periods of high electricity demand has been questioned. Here we characterise the winter relationship between electricity demand and the availability of wind power. Although a wide range of wind power capacity factors is seen for a given demand, the average capacity factor reduces by a third between low and high demand. However, during the highest demand average wind power increases again, due to strengthening easterly winds. The nature of the weather patterns affecting Great Britain are responsible for this relationship. High demand is driven by a range of high pressure weather types, each giving cold conditions, but variable wind power availability. Offshore wind power is sustained at higher levels and offers a more secure supply compared to that onshore. However, during high demand periods in Great Britain neighbouring countries may struggle to provide additional capacity due to concurrent low temperatures and low wind power availability.

Environmental factors affecting feed intake of steers in different housing systems in the summer

NASA Astrophysics Data System (ADS)

Koknaroglu, H.; Otles, Z.; Mader, T.; Hoffman, M. P.

2008-07-01

A total of 188 yearling steers of predominantly Angus and Hereford breeds, with mean body weight of 299 kg, were used in this study, which started on 8 April and finished on 3 October, to assess the effects of environmental factors on feed intake of steers in various housing systems. Housing consisted of outside lots with access to overhead shelter, outside lots with no overhead shelter and a cold confinement building. Ad libitum corn, 2.27 kg of 35% dry matter whole plant sorghum silage and 0.68 kg of a 61% protein-vitamin-mineral supplement was offered. Feed that was not consumed was measured to determine feed intake. The temperature data were recorded by hygro-thermographs. Hourly temperatures and humidity were used to develop weather variables. Regression analysis was used and weather variables were regressed on dry matter intake (DMI). When addition of a new variable did not improve R 2 more than one unit, then the number of variables in the model was truncated. Cattle in confinement had lower DMI than those in open lots and those in open lots with access to an overhead shelter ( P < 0.05). Cattle in outside lots with access to overhead shelter had similar DMI compared to those in open lots ( P = 0.065). Effect of heat was predominantly displayed in August in the three housing systems. In terms of explaining variation in DMI, in outside lots with access to overhead shelter, average and daytime temperatures were important factors, whereas in open lots, nocturnal, peak and average temperatures were important factors. In confinement buildings, the previous day’s temperature and humidity index were the most important factors explaining variation in DMI. Results show the effect of housing and weather variables on DMI in summer and when considering these results, cattle producers wishing to improve cattle feedlot performance should consider housing conditions providing less stress or more comfort.

Thermal comfort in Quebec City, Canada: sensitivity analysis of the UTCI and other popular thermal comfort indices in a mid-latitude continental city.

PubMed

Provençal, Simon; Bergeron, Onil; Leduc, Richard; Barrette, Nathalie

2016-04-01

The newly developed Universal Thermal Climate Index (UTCI), along with the physiological equivalent temperature (PET), the humidex (HX) and the wind chill index (WC), was calculated in Quebec City, Canada, a city with a strong seasonal climatic variability, over a 1-year period. The objective of this study is twofold: evaluate the operational benefits of implementing the UTCI for a climate monitoring program of public comfort and health awareness as opposed to relying on traditional and simple indices, and determine whether thermal comfort monitoring specific to dense urban neighborhoods is necessary to adequately fulfill the goals of the program. In order to do so, an analysis is performed to evaluate each of these indices' sensitivity to the meteorological variables that regulate them in different environments. Overall, the UTCI was found to be slightly more sensitive to mean radiant temperature, moderately more sensitive to humidity and much more sensitive to wind speed than the PET. This dynamic changed slightly depending on the environment and the season. In hot weather, the PET was found to be more sensitive to mean radiant temperature and therefore reached high values that could potentially be hazardous more frequently than the UTCI and the HX. In turn, the UTCI's stronger sensitivity to wind speed makes it a superior index to identify potentially hazardous weather in winter compared to the PET and the WC. Adopting the UTCI broadly would be an improvement over the traditionally popular HX and WC indices. The urban environment produced favorable conditions to sustain heat stress conditions, where the indices reached high values more frequently there than in suburban locations, which advocates for weather monitoring specific to denser urban areas.

Thermal comfort in Quebec City, Canada: sensitivity analysis of the UTCI and other popular thermal comfort indices in a mid-latitude continental city

NASA Astrophysics Data System (ADS)

Provençal, Simon; Bergeron, Onil; Leduc, Richard; Barrette, Nathalie

2016-04-01

The newly developed Universal Thermal Climate Index (UTCI), along with the physiological equivalent temperature (PET), the humidex (HX) and the wind chill index (WC), was calculated in Quebec City, Canada, a city with a strong seasonal climatic variability, over a 1-year period. The objective of this study is twofold: evaluate the operational benefits of implementing the UTCI for a climate monitoring program of public comfort and health awareness as opposed to relying on traditional and simple indices, and determine whether thermal comfort monitoring specific to dense urban neighborhoods is necessary to adequately fulfill the goals of the program. In order to do so, an analysis is performed to evaluate each of these indices' sensitivity to the meteorological variables that regulate them in different environments. Overall, the UTCI was found to be slightly more sensitive to mean radiant temperature, moderately more sensitive to humidity and much more sensitive to wind speed than the PET. This dynamic changed slightly depending on the environment and the season. In hot weather, the PET was found to be more sensitive to mean radiant temperature and therefore reached high values that could potentially be hazardous more frequently than the UTCI and the HX. In turn, the UTCI's stronger sensitivity to wind speed makes it a superior index to identify potentially hazardous weather in winter compared to the PET and the WC. Adopting the UTCI broadly would be an improvement over the traditionally popular HX and WC indices. The urban environment produced favorable conditions to sustain heat stress conditions, where the indices reached high values more frequently there than in suburban locations, which advocates for weather monitoring specific to denser urban areas.

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

PubMed Central

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

2005-01-01

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

Heat and Humidity in the City: Neighborhood Heat Index Variability in a Mid-Sized City in the Southeastern United States

PubMed Central

Hass, Alisa L.; Ellis, Kelsey N.; Reyes Mason, Lisa; Hathaway, Jon M.; Howe, David A.

2016-01-01

Daily weather conditions for an entire city are usually represented by a single weather station, often located at a nearby airport. This resolution of atmospheric data fails to recognize the microscale climatic variability associated with land use decisions across and within urban neighborhoods. This study uses heat index, a measure of the combined effects of temperature and humidity, to assess the variability of heat exposure from ten weather stations across four urban neighborhoods and two control locations (downtown and in a nearby nature center) in Knoxville, Tennessee, USA. Results suggest that trees may negate a portion of excess urban heat, but are also associated with greater humidity. As a result, the heat index of locations with more trees is significantly higher than downtown and areas with fewer trees. Trees may also reduce heat stress by shading individuals from incoming radiation, though this is not considered in this study. Greater amounts of impervious surfaces correspond with reduced evapotranspiration and greater runoff, in terms of overall mass balance, leading to a higher temperature, but lower relative humidity. Heat index and relative humidity were found to significantly vary between locations with different tree cover and neighborhood characteristics for the full study time period as well as for the top 10% of heat index days. This work demonstrates the need for high-resolution climate data and the use of additional measures beyond temperature to understand urban neighborhood exposure to extreme heat, and expresses the importance of considering vulnerability differences among residents when analyzing neighborhood-scale impacts. PMID:26761021

Heat and Humidity in the City: Neighborhood Heat Index Variability in a Mid-Sized City in the Southeastern United States.

PubMed

Hass, Alisa L; Ellis, Kelsey N; Reyes Mason, Lisa; Hathaway, Jon M; Howe, David A

2016-01-11

Daily weather conditions for an entire city are usually represented by a single weather station, often located at a nearby airport. This resolution of atmospheric data fails to recognize the microscale climatic variability associated with land use decisions across and within urban neighborhoods. This study uses heat index, a measure of the combined effects of temperature and humidity, to assess the variability of heat exposure from ten weather stations across four urban neighborhoods and two control locations (downtown and in a nearby nature center) in Knoxville, Tennessee, USA. Results suggest that trees may negate a portion of excess urban heat, but are also associated with greater humidity. As a result, the heat index of locations with more trees is significantly higher than downtown and areas with fewer trees. Trees may also reduce heat stress by shading individuals from incoming radiation, though this is not considered in this study. Greater amounts of impervious surfaces correspond with reduced evapotranspiration and greater runoff, in terms of overall mass balance, leading to a higher temperature, but lower relative humidity. Heat index and relative humidity were found to significantly vary between locations with different tree cover and neighborhood characteristics for the full study time period as well as for the top 10% of heat index days. This work demonstrates the need for high-resolution climate data and the use of additional measures beyond temperature to understand urban neighborhood exposure to extreme heat, and expresses the importance of considering vulnerability differences among residents when analyzing neighborhood-scale impacts.

Global meteorological influences on the record UK rainfall of winter 2013-14

NASA Astrophysics Data System (ADS)

Knight, Jeff R.; Maidens, Anna; Watson, Peter A. G.; Andrews, Martin; Belcher, Stephen; Brunet, Gilbert; Fereday, David; Folland, Chris K.; Scaife, Adam A.; Slingo, Julia

2017-07-01

The UK experienced record average rainfall in winter 2013-14, leading to widespread and prolonged flooding. The immediate cause of this exceptional rainfall was a very strong and persistent cyclonic atmospheric circulation over the North East Atlantic Ocean. This was related to a very strong North Atlantic jet stream which resulted in numerous damaging wind storms. These exceptional meteorological conditions have led to renewed questions about whether anthropogenic climate change is noticeably influencing extreme weather. The regional weather pattern responsible for the extreme UK winter coincided with highly anomalous conditions across the globe. We assess the contributions from various possible remote forcing regions using sets of ocean-atmosphere model relaxation experiments, where winds and temperatures are constrained to be similar to those observed in winter 2013-14 within specified atmospheric domains. We find that influences from the tropics were likely to have played a significant role in the development of the unusual extra-tropical circulation, including a role for the tropical Atlantic sector. Additionally, a stronger and more stable stratospheric polar vortex, likely associated with a strong westerly phase of the stratospheric Quasi-Biennial Oscillation (QBO), appears to have contributed to the extreme conditions. While intrinsic climatic variability clearly has the largest effect on the generation of extremes, results from an analysis which segregates circulation-related and residual rainfall variability suggest that emerging climate change signals made a secondary contribution to extreme rainfall in winter 2013-14.

Fire behavior, fuel treatments, and fire suppression on the Hayman Fire - Part 1: Fire weather, meteorology, and climate

Treesearch

Larry Bradshaw; Roberta Bartlette; John McGinely; Karl Zeller

2003-01-01

The Hayman Fire in June 2002 was heavily influenced by antecedent regional weather conditions, culminating in a series of daily weather events that aligned to produce widely varying fire behavior. This review of weather conditions associated with the Hayman Fire consists of two parts: 1) A brief overview of prior conditions as described by a regional climate review and...

[The influence of the climatic and weather conditions on the mechanisms underlying the formation of enhanced meteosensitivity (a literature review)].

PubMed

Uyanaeva, A I; Tupitsyna, Yu Yu; Rassulova, M A; Turova, E A; Lvova, N V; Ajrapetova, N S

The present review concerns the problem of the influence of the climatic conditions on the human body, the creation of the medical weather forecast service, the development of non-pharmacological methods for the correction of meteopathic disorders, and the reduction of the risk of the complications provoked by the unfavourable weather conditions. The literature data are used to analyse the influence of climatic and weather factors on the formation of enhanced meteosensitivity and the development of exacerbations of chronic non-communicable diseases under the influence of weather conditions. It is concluded that marked changes of the weather may lead to an increased frequency of exacerbations of the chronic non-communicable diseases. The influence of weather and climate on human health is becoming an increasingly important factor under the current conditions bearing in mind the modern tendency toward variations of the global climatic conditions and their specific regional manifestations. The authors emphasize the necessity of the identification and evaluation of the predictors of the development of high meteosensitivity for the prognostication of the risks of the meteopathic reactions and the complications associated with the changes in weather conditions as well as the importance of the improvement of the existing and the development of new methods for the non-pharmacological prevention and correction of enhanced meteosensitivity with the application of the natural and preformed physical factors.

Validation of crowdsourced automatic rain gauge measurements in Amsterdam

NASA Astrophysics Data System (ADS)

de Vos, Lotte; Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

2016-04-01

The increasing number of privately owned weather stations and the facilitating role the internet to make this data publicly available, has led to several online platforms that collect and visualize crowdsourced weather data. This has resulted in ever increasing freely available datasets of weather measurements generated by amateur weather enthusiasts. Because of the lack of quality control and the frequent absence of metadata, these measurements are often considered as unreliable. Given the often large variability of weather variables in space and time, and the generally low number of official weather stations, this growing quantity of crowdsourced data may become an important additional source of information. Amateur weather observations have become more frequent over the past decade due to weather stations becoming more user-friendly and affordable. The variables measured by these weather stations are temperature, pressure and dew point, and in some cases wind and rainfall. Meteorological data from crowdsourced automatic weather stations in cities have primarily been used to examine the urban heat island effect. Thus far, these studies have focused on the comparison of the crowdsourced station temperature measurements with a nearby WMO-standard weather station, which is often located in a rural area or the outskirts of a city, generally not being representative of the city center. Instead of temperature, the rainfall measurements by the stations are examined. This research focuses on the combined ability of a large number of privately owned weather stations in an urban setting to correctly monitor rainfall. A set of 64 automatic weather stations distributed over Amsterdam (The Netherlands) that have at least 3 months of precipitation measurement during one year are evaluated. Precipitation measurements from stations are compared to a merged radar-gauge precipitation product. Disregarding sudden jumps in station measured precipitation, the accumulative rainfall over time in most stations showed an underestimation of rainfall compared to the accumulative values found in the corresponding radar pixel of the reference. Special consideration is given to the identification of faulty measurements without the need to obtain additional meta-data, such as setup and surroundings. This validation will show the potential of crowdsourced automatic weather stations for future urban rainfall monitoring.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Atmospheric mold spore counts in relation to meteorological parameters

NASA Astrophysics Data System (ADS)

Katial, R. K.; Zhang, Yiming; Jones, Richard H.; Dyer, Philip D.

Fungal spore counts of Cladosporium, Alternaria, and Epicoccum were studied during 8 years in Denver, Colorado. Fungal spore counts were obtained daily during the pollinating season by a Rotorod sampler. Weather data were obtained from the National Climatic Data Center. Daily averages of temperature, relative humidity, daily precipitation, barometric pressure, and wind speed were studied. A time series analysis was performed on the data to mathematically model the spore counts in relation to weather parameters. Using SAS PROC ARIMA software, a regression analysis was performed, regressing the spore counts on the weather variables assuming an autoregressive moving average (ARMA) error structure. Cladosporium was found to be positively correlated (P<0.02) with average daily temperature, relative humidity, and negatively correlated with precipitation. Alternaria and Epicoccum did not show increased predictability with weather variables. A mathematical model was derived for Cladosporium spore counts using the annual seasonal cycle and significant weather variables. The model for Alternaria and Epicoccum incorporated the annual seasonal cycle. Fungal spore counts can be modeled by time series analysis and related to meteorological parameters controlling for seasonallity; this modeling can provide estimates of exposure to fungal aeroallergens.

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

PubMed Central

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

2017-01-01

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

Sunspots, Space Weather and Climate

NASA Technical Reports Server (NTRS)

Hathaway, David H.

2009-01-01

Four hundred years ago this year the telescope was first used for astronomical observations. Within a year, Galileo in Italy and Harriot in England reported seeing spots on the surface of the Sun. Yet, it took over 230 years of observations before a Swiss amateur astronomer noticed that the sunspots increased and decreased in number over a period of about 11 years. Within 15 years of this discovery of the sunspot cycle astronomers made the first observations of a flare on the surface of the Sun. In the 150 years since that discovery we have learned much about sunspots, the sunspot cycle, and the Sun s explosive events - solar flares, prominence eruptions and coronal mass ejections that usually accompany the sunspots. These events produce what is called Space Weather. The conditions in space are dramatically affected by these events. Space Weather can damage our satellites, harm our astronauts, and affect our lives here on the surface of planet Earth. Long term changes in the sunspot cycle have been linked to changes in our climate as well. In this public lecture I will give an introduction to sunspots, the sunspot cycle, space weather, and the possible impact of solar variability on our climate.

The link between eddy-driven jet variability and weather regimes in the North Atlantic-European sector

NASA Astrophysics Data System (ADS)

Madonna, E.; Li, C.; Grams, C. M.; Woollings, T.

2017-12-01

Understanding the variability of the North Atlantic eddy-driven jet is key to unravelling the dynamics, predictability and climate change response of extratropical weather in the region. This study aims to 1) reconcile two perspectives on wintertime variability in the North Atlantic-European sector and 2) clarify their link to atmospheric blocking. Two common views of wintertime variability in the North Atlantic are the zonal-mean framework comprising three preferred locations of the eddy-driven jet (southern, central, northern), and the weather regime framework comprising four classical North Atlantic-European regimes (Atlantic ridge AR, zonal ZO, European/Scandinavian blocking BL, Greenland anticyclone GA). We use a k-means clustering algorithm to characterize the two-dimensional variability of the eddy-driven jet stream, defined by the lower tropospheric zonal wind in the ERA-Interim reanalysis. The first three clusters capture the central jet and northern jet, along with a new mixed jet configuration; a fourth cluster is needed to recover the southern jet. The mixed cluster represents a split or strongly tilted jet, neither of which is well described in the zonal-mean framework, and has a persistence of about one week, similar to the other clusters. Connections between the preferred jet locations and weather regimes are corroborated - southern to GA, central to ZO, and northern to AR. In addition, the new mixed cluster is found to be linked to European/Scandinavian blocking, whose relation to the eddy-driven jet was previously unclear. The results highlight the necessity of bridging from weather to climate scales for a deeper understanding of atmospheric circulation variability.

Road Weather and Connected Vehicles

NASA Astrophysics Data System (ADS)

Pisano, P.; Boyce, B. C.

2015-12-01

On average, there are over 5.8 M vehicle crashes each year of which 23% are weather-related. Weather-related crashes are defined as those crashes that occur in adverse weather or on slick pavement. The vast majority of weather-related crashes happen on wet pavement (74%) and during rainfall (46%). Connected vehicle technologies hold the promise to transform road-weather management by providing improved road weather data in real time with greater temporal and geographic accuracy. This will dramatically expand the amount of data that can be used to assess, forecast, and address the impacts that weather has on roads, vehicles, and travelers. The use of vehicle-based measurements of the road and surrounding atmosphere with other, more traditional weather data sources, and create road and atmospheric hazard products for a variety of users. The broad availability of road weather data from mobile sources will vastly improve the ability to detect and forecast weather and road conditions, and will provide the capability to manage road-weather response on specific roadway links. The RWMP is currently demonstrating how weather, road conditions, and related vehicle data can be used for decision making through an innovative Integrated Mobile Observations project. FHWA is partnering with 3 DOTs (MN, MI, & NV) to pilot these applications. One is a mobile alerts application called the Motorists Advisories and Warnings (MAW) and a maintenance decision support application. These applications blend traditional weather information (e.g., radar, surface stations) with mobile vehicle data (e.g., temperature, brake status, wiper status) to determine current weather conditions. These weather conditions, and other road-travel-relevant information, are provided to users via web and phone applications. The MAW provides nowcasts and short-term forecasts out to 24 hours while the EMDSS application can provide forecasts up to 72 hours in advance. The three DOTs have placed readers and external road weather sensors on their maintenance fleet vehicles to collect vehicular and meteorological data. Data from all three states is sent to a processing system called the Pikalert® Vehicle Data Translator (VDT) that quality checks and uses the data to infer current and forecasted weather conditions.

Integrated site-specific quantification of faecal bacteria and detection of DNA markers in faecal contamination source tracking as a microbial risk tracking tool in urban Lake ecosystems

NASA Astrophysics Data System (ADS)

Donde, Oscar Omondi; Tian, Cuicui; Xiao, Bangding

2017-11-01

The presence of feacal-derived pathogens in water is responsible for several infectious diseases and deaths worldwide. As a solution, sources of fecal pollution in waters must be accurately assessed, properly determined and strictly controlled. However, the exercise has remained challenging due to the existing overlapping characteristics by different members of faecal coliform bacteria and the inadequacy of information pertaining to the contribution of seasonality and weather condition on tracking the possible sources of pollution. There are continued efforts to improve the Faecal Contamination Source Tracking (FCST) techniques such as Microbial Source Tracking (MST). This study aimed to make contribution to MST by evaluating the efficacy of combining site specific quantification of faecal contamination indicator bacteria and detection of DNA markers while accounting for seasonality and weather conditions' effects in tracking the major sources of faecal contamination in a freshwater system (Donghu Lake, China). The results showed that the use of cyd gene in addition to lacZ and uidA genes differentiates E. coli from other closely related faecal bacteria. The use of selective media increases the pollution source tracking accuracy. BSA addition boosts PCR detection and increases FCST efficiency. Seasonality and weather variability also influence the detection limit for DNA markers.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The sensitivity of snowfall to weather states over Sweden

NASA Astrophysics Data System (ADS)

Norin, Lars; Devasthale, Abhay; L'Ecuyer, Tristan S.

2017-09-01

For a high-latitude country like Sweden snowfall is an important contributor to the regional water cycle. Furthermore, snowfall impacts surface properties, affects atmospheric thermodynamics, has implications for traffic and logistics management, disaster preparedness, and also impacts climate through changes in surface albedo and turbulent heat fluxes. For Sweden it has been shown that large-scale atmospheric circulation patterns, or weather states, are important for precipitation variability. Although the link between atmospheric circulation patterns and precipitation has been investigated for rainfall there are no studies focused on the sensitivity of snowfall to weather states over Sweden.In this work we investigate the response of snowfall to eight selected weather states. These weather states consist of four dominant wind directions together with cyclonic and anticyclonic circulation patterns and enhanced positive and negative phases of the North Atlantic Oscillation. The presented analysis is based on multiple data sources, such as ground-based radar measurements, satellite observations, spatially interpolated in situ observations, and reanalysis data. The data from these sources converge to underline the sensitivity of falling snow over Sweden to the different weather states.In this paper we examine both average snowfall intensities and snowfall accumulations associated with the different weather states. It is shown that, even though the heaviest snowfall intensities occur during conditions with winds from the south-west, the largest contribution to snowfall accumulation arrives with winds from the south-east. Large differences in snowfall due to variations in the North Atlantic Oscillation are shown as well as a strong effect of cyclonic and anticyclonic circulation patterns. Satellite observations are used to reveal the vertical structures of snowfall during the different weather states.

Analyzing pedestrian crash injury severity under different weather conditions.

PubMed

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

2017-05-19

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

A population-based study of the associations of stroke occurrence with weather parameters in Siberia, Russia (1982-92).

PubMed

Feigin, V L; Nikitin, Y P; Bots, M L; Vinogradova, T E; Grobbee, D E

2000-03-01

Previous studies have established a seasonal variation in stroke occurrence, but none have assessed the influence of inclement weather conditions on stroke incidence in a general population of Russia. We performed a stroke population-based study in the Oktiabrsky District of Novosibirsk, Siberia, Russia. Included in the analysis were 1929 patients with their first occurrence of ischemic stroke (IS), 215 patients with their first occurrence of intracerebral hemorrhage (ICH) and 64 patients with their first occurrence of subarachnoid hemorrhage (SAH): all patients were aged between 25 and 74 years. The cumulative daily occurrence of total strokes and stroke subtypes was evaluated in relation to aggregated daily mean values of ambient temperature, relative humidity and air pressure by means of Poisson regression analysis to estimate the rate ratio (RR) with corresponding confidence interval (CI) and to identify the weather parameters of most importance. In a multivariate analysis, with adjustment for the effects of season, solar and geomagnetic activity, and age of the patients, low ambient temperature (RR 1.32; 95% CI 1.05-1.66) and mean value of air pressure (RR 0.986; 95% CI 0.972-0.999) were important predictors of IS occurrence, while mild ambient temperature (RR 1.52; 95% CI 1. 04-2.22) was an important predictor of ICH occurrence. No relationship between SAH occurrence and any one of the weather parameters studied was revealed. There was no interaction between any meteorological variables that was statistically significant. Inclement weather conditions are associated with the occurrence of IS and ICH in Siberia, Russia. Among the meteorological parameters studied, low ambient temperature and mean air pressure are the most important predictors of IS occurrence, whereas the occurrence of ICH is associated with mild ambient temperature. There is no association between any one of the weather parameters studied and the occurrence of SAH.

A comparison of four years of limnology in the Sawtooth Lakes with emphasis on fertilization in Redfish Lake

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

Budy, P.; Luecke, C.; Wurtsbaugh, W.A.

1996-05-01

Included in this section of the report on limnology of Lakes in the Snake River Plain are descriptions of four years of limnological sampling to compare inter and intra annual variability in lake productivity to evaluate potential rearing conditions for juvenile sockeyed salmon. Data was used to evaluate the effects of nutrient enhancement, annual weather patterns, and planktivore consumption on lake productivity.

A biology-driven receptor model for daily pollen allergy risk in Korea based on Weibull probability density function

NASA Astrophysics Data System (ADS)

Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo

2017-02-01

Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.

A biology-driven receptor model for daily pollen allergy risk in Korea based on Weibull probability density function.

PubMed

Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo

2017-02-01

Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.

MAVEN observations of the solar cycle 24 space weather conditions at Mars

NASA Astrophysics Data System (ADS)

Lee, C. O.; Hara, T.; Halekas, J. S.; Thiemann, E.; Chamberlin, P.; Eparvier, F.; Lillis, R. J.; Larson, D. E.; Dunn, P. A.; Espley, J. R.; Gruesbeck, J.; Curry, S. M.; Luhmann, J. G.; Jakosky, B. M.

2017-03-01

The Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft has been continuously observing the variability of solar soft X-rays and EUV irradiance, monitoring the upstream solar wind and interplanetary magnetic field conditions and measuring the fluxes of solar energetic ions and electrons since its arrival to Mars. In this paper, we provide a comprehensive overview of the space weather events observed during the first ˜1.9 years of the science mission, which includes the description of the solar and heliospheric sources of the space weather activity. To illustrate the variety of upstream conditions observed, we characterize a subset of the event periods by describing the Sun-to-Mars details using observations from the MAVEN solar Extreme Ultraviolet Monitor, solar energetic particle (SEP) instrument, Solar Wind Ion Analyzer, and Magnetometer together with solar observations using near-Earth assets and numerical solar wind simulation results from the Wang-Sheeley-Arge-Enlil model for some global context of the event periods. The subset of events includes an extensive period of intense SEP electron particle fluxes triggered by a series of solar flares and coronal mass ejection (CME) activity in December 2014, the impact by a succession of interplanetary CMEs and their associated SEPs in March 2015, and the passage of a strong corotating interaction region (CIR) and arrival of the CIR shock-accelerated energetic particles in June 2015. However, in the context of the weaker heliospheric conditions observed throughout solar cycle 24, these events were moderate in comparison to the stronger storms observed previously at Mars.

Rock Erodibility as a Dynamic Variable Driven by the Interplay between Erosion and Weathering in Bedrock Channels: Examples from Great Falls, Virginia, USA

NASA Astrophysics Data System (ADS)

Hancock, G. S.; Huettenmoser, J.; Shobe, C. M.; Eppes, M. C.

2016-12-01

Rock erodibility in channels is a primary control on the stresses required to erode bedrock (e.g., Sklar and Dietrich, 2001). Erodibility tends to be treated as a uniform and fixed variable at the scale of channel cross-sections, particularly in models of channel profile evolution. Here we present field data supporting the hypothesis (Hancock et al., 2011) that erodibility is a dynamic variable, driven by the interplay between erosion rate and weathering processes within cross-sections. We hypothesize that rock weathering varies in cross-sections from virtually unweathered in the thalweg, where frequent stripping removes weathered rock, to a degree of weathering determined by the frequency of erosive events higher on the channel margin. We test this hypothesis on three tributaries to the Potomac River underlain by similar bedrock but with varying erosion rates ( 0.01 to 0.8 m/ky). At multiple heights within three cross-sections on three tributaries, we measured compressive strength with a Schmidt hammer, surface roughness with a contour gage, and density and length of visible cracks. Compressive strength decreased with height in all nine cross-sections by 10% to 50%, and surface roughness increased with height in seven cross-sections by 25% - 45%, with the remaining two showing minimal change. Crack density increased with height in the three cross-sections measured. Taken together these data demonstrate increases in weathering intensity, and presumably, rock erodibility, with height. The y-intercept of the relation between height and the three measured variables were nearly identical, suggesting that thalweg erodibility was similar on each channel, as predicted, even though erodibility higher in the cross-section were markedly different. The rate at which the three variables changed with height in each cross-section is strongly related to stream power. Assuming stream power is a reasonable surrogate for erosion rate, this result implies that erosion rate can be a primary influence on the distribution of erodibility within channel cross-sections. We conclude that the interplay between rates of erosion and weathering produces spatial as well as temporal variability in erodibility which, in turn, influences channel form and gradient.

How reliable is the offline linkage of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model?

EPA Science Inventory

The aim for this research is to evaluate the ability of the offline linkage of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model to produce hydrological, e.g. evaporation (ET), soil moisture (SM), runoff, and baseflow. First, the VIC mo...

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

PubMed Central

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

2016-01-01

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

Statistical characteristics of mudflows in the piedmont areas of Uzbekistan and the role of the synoptic processes for the formation of mudflows

NASA Astrophysics Data System (ADS)

Mamadjanova, Gavkhar; Leckebusch, Gregor C.

2016-04-01

Mudflows are formed almost every year in the territory of Uzbekistan and neighbouring countries. They represent a major threat to human life and settlements and can significantly damage infrastructure. In general, in addition to elevated soil moisture conditions, severe local rainfall events (e.g., 15 mm of precipitation in 12 hours) and associated air temperature conditions are understood to be the main factors in the formation of mudflows in the piedmont areas of Uzbekistan. The main purpose of this study is to understand factors on local and synoptic to hemispheric scales, which cause mudflow variability on interannual and longer time scales. To fulfil this objective, in a first step historical data of mudflow occurrences (mainly March to August) in Uzbekistan provided by the Centre of Hydro-meteorological Service of the Republic of Uzbekistan (Uzhydromet) for more than 140 years are statistically analysed. During the investigation period a total of around 3000 mudflow events were observed with about 21 events per year on average and a maximum of 168 mudflows in 1930. To understand principle factors steering the variability of mudflow occurrences, synoptic scale circulation weather types (CWT) over Central Asia and Uzbekistan are investigated. The majority of mudflows (22%) occur during the advection of westerly airflow when moist air from Central and Southern Europe reaches Uzbekistan. This objectively classified synoptic situation can be related to one of the 15 primary synoptic circulation types over the Central Asia and Uzbekistan which were subjectively derived by Bugayev and Giorgio in 1930-40s (Bugayev et al., 1957), thus confirming the validity of this approach. By means of the CWT approach, we further analyse that on mudflow-days the frequencies of cyclonic, westerly, south-westerly and north-westerly stream flows are increased in comparison to the climatological frequency of occurrence of these circulation weather types. Details of the necessary and sufficient meteorological conditions within a CWT class are investigated. Further studies will investigate and identify key factors steering the variability in CWT frequency variability over Central Asia on longer timescales and how these are related to known major variability modes in the climate system.

7 CFR 1945.20 - Making EM loans available.

Code of Federal Regulations, 2011 CFR

2011-01-01

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

Evaluation of Software Simulation of Road Weather Information System.

DOT National Transportation Integrated Search

2016-09-01

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

Effects of atmospheric variability on energy utilization and conservation. [Space heating energy demand modeling; Program HEATLOAD

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

Reiter, E.R.; Johnson, G.R.; Somervell, W.L. Jr.

Research conducted between 1 July 1975 and 31 October 1976 is reported. A ''physical-adaptive'' model of the space-conditioning demand for energy and its response to changes in weather regimes was developed. This model includes parameters pertaining to engineering factors of building construction, to weather-related factors, and to socio-economic factors. Preliminary testing of several components of the model on the city of Greeley, Colorado, yielded most encouraging results. Other components, especially those pertaining to socio-economic factors, are still under development. Expansion of model applications to different types of structures and larger regions is presently underway. A CRT-display model for energy demandmore » within the conterminous United States also has passed preliminary tests. A major effort was expended to obtain disaggregated data on energy use from utility companies throughout the United States. The study of atmospheric variability revealed that the 22- to 26-day vacillation in the potential and kinetic energy modes of the Northern Hemisphere is related to the behavior of the planetary long-waves, and that the midwinter dip in zonal available potential energy is reflected in the development of blocking highs. Attempts to classify weather patterns over the eastern and central United States have proceeded satisfactorily to the point where testing of our method for longer time periods appears desirable.« less

The Heat Strain of Various Athletic Surfaces: A Comparison Between Observed and Modeled Wet-Bulb Globe Temperatures.

PubMed

Pryor, J Luke; Pryor, Riana R; Grundstein, Andrew; Casa, Douglas J

2017-11-01

  The National Athletic Trainers' Association recommends using onsite wet-bulb globe temperature (WBGT) measurement to determine whether to modify or cancel physical activity. However, not all practitioners do so and instead they may rely on the National Weather Service (NWS) to monitor weather conditions.   To compare regional NWS WBGT estimates with local athletic-surface readings and compare WBGT measurements among various local athletic surfaces.   Observational study.   Athletic fields.   Measurements from 2 identical WBGT devices were averaged on 10 athletic surfaces within an NWS station reporting radius. Athletic surfaces consisted of red and black all-weather tracks (track), blue and black hard tennis courts (tennis), nylon-knit artificial green turf, green synthetic turfgrass, volleyball sand, softball clay, natural grass (grass), and a natural lake (water). Measurements (n = 143 data pairs) were taken over 18 days (May through September) between 1 pm and 4:30 pm in direct sunlight 1.2 m above ground. The starting location was counterbalanced across surfaces. The NWS weather data were entered into an algorithm to model NWS WBGT.   Black tennis, black track, red track, and volleyball sand WBGT recordings were greater than NWS estimates ( P ≤ .05). When all athletic-surface measurements were combined, NWS (26.85°C ± 2.93°C) underestimated athletic-surface WBGT measurements (27.52°C ± 3.13°C; P < .001). The range of difference scores (-4.42°C to 6.14°C) and the absolute mean difference (1.71°C ± 1.32°C) were large. The difference between the onsite and NWS WBGT measurements resulted in misclassification of the heat-safety activity category 45% (65/143) of the time ([Formula: see text]= 3.857, P = .05). The WBGT of water was 1.4°C to 2.7°C lower than that of all other athletic surfaces ( P = .04). We observed no other differences among athletic surfaces but noted large WBGT measurement variability among athletic playing surfaces.   Clinicians should use an onsite WBGT device to determine environmental conditions and the need for modification of athletic events, especially as environmental conditions worsen. Given the large WBGT variability among athletic surfaces, WBGT measurements should be obtained from each athletic surface.

Low frequency North Atlantic SST variability: Weather noise forcing and coupled response

NASA Astrophysics Data System (ADS)

Fan, Meizhu

A method to diagnose the causes of low frequency SST variability is developed, tested and applied in an ideal case and real climate. In the ideal case, a free simulation of the COLA CGCM is taken as synthetic observations. For real climate, we take NCEP reanalysis atmospheric data and Reynolds SST as observations. Both the synthetic and actual observation data show that weather noise is the main component of atmospheric variability at subtropics and high-latitude. Diagnoses of results from the ideal case suggest that most of the synthetic observed SST variability can be reproduced by the weather noise surface fluxes forcing. This includes the "observed" low frequency SST patterns in the North Atlantic and their corresponding time evolution. Among all the noise surface fluxes, heat flux plays a major role. The results from simulations using actual observations also suggest that the observed SST variability is mostly atmospheric weather noise forced. The regional atmospheric noise forcing, especially the heat flux noise forcing, is the major source of the low frequency SST variability in the North Atlantic. The observed SST tripole mode has about a 12 year period and it can be reasonably reproduced by the weather noise forcing in terms of its period, spatial pattern and variance. Based on our diagnosis, it is argued that the SST tripole is mainly forced by local atmospheric heat flux noise. The gyre circulation plays a secondary role: the anomalous gyre circulation advects mean thermal features across the inter-gyre boundary, and the mean gyre advection carries SST anomalies along the inter-gyre boundary. The diagnosis is compared with a delayed oscillator theory. We find that the delayed oscillator theory is not supported and that the SST tripole mode is forced by weather noise heat flux noise. However, the result may be model dependent.

Improving Seasonal Crop Monitoring and Forecasting for Soybean and Corn in Iowa

NASA Astrophysics Data System (ADS)

Togliatti, K.; Archontoulis, S.; Dietzel, R.; VanLoocke, A.

2016-12-01

Accurately forecasting crop yield in advance of harvest could greatly benefit farmers, however few evaluations have been conducted to determine the effectiveness of forecasting methods. We tested one such method that used a combination of short-term weather forecasting from the Weather Research and Forecasting Model (WRF) to predict in season weather variables, such as, maximum and minimum temperature, precipitation and radiation at 4 different forecast lengths (2 weeks, 1 week, 3 days, and 0 days). This forecasted weather data along with the current and historic (previous 35 years) data from the Iowa Environmental Mesonet was combined to drive Agricultural Production Systems sIMulator (APSIM) simulations to forecast soybean and corn yields in 2015 and 2016. The goal of this study is to find the forecast length that reduces the variability of simulated yield predictions while also increasing the accuracy of those predictions. APSIM simulations of crop variables were evaluated against bi-weekly field measurements of phenology, biomass, and leaf area index from early and late planted soybean plots located at the Agricultural Engineering and Agronomy Research Farm in central Iowa as well as the Northwest Research Farm in northwestern Iowa. WRF model predictions were evaluated against observed weather data collected at the experimental fields. Maximum temperature was the most accurately predicted variable, followed by minimum temperature and radiation, and precipitation was least accurate according to RMSE values and the number of days that were forecasted within a 20% error of the observed weather. Our analysis indicated that for the majority of months in the growing season the 3 day forecast performed the best. The 1 week forecast came in second and the 2 week forecast was the least accurate for the majority of months. Preliminary results for yield indicate that the 2 week forecast is the least variable of the forecast lengths, however it also is the least accurate. The 3 day and 1 week forecast have a better accuracy, with an increase in variability.

Analysis of winter weather conditions and their potential impact on wind farm operations

NASA Astrophysics Data System (ADS)

Novakovskaia, E.; Treinish, L. A.; Praino, A.

2009-12-01

Severe weather conditions have two primary impacts on wind farm operations. The first relates to understanding potential damage to the turbines themselves and what actions are required to mitigate the effects. The second is recognizing what conditions may lead to a full or partial shutdown of the wind farm with sufficient lead time to determine the likely inability to meet energy generation committments. Ideally, wind forecasting suitable for wind farm operations should be of sufficient fidelity to resolve features within the boundary layer that lead to either damaging conditions or useful power generation. Given the complexity of the site-specific factors that effect the boundary layer at the scale of typical land-based wind farm locations such as topography, vegetation, land use, soil conditions, etc., which may vary with turbine design and layout within the farm, enabling reliable forecasts of too little or too much wind is challenging. A potential solution should involve continuous updates of alert triggering criteria through analysis of local wind patterns and probabilistic risk assessment for each location. To evaluate this idea, we utilize our operational mesoscale prediction system, dubbed “Deep Thunder”, developed at the IBM Thomas J. Watson Research Center. In particular, we analyze winter-time near-surface winds in upstate New York, where four similar winds farms are located. Each of these farms were built at roughly the same time and utilize similar turbines. Given the relative uncertainty associated with numerical weather prediction at this scale, and the difference in risk assessment due to the two primary impacts of severe weather, probabilistic forecasts are a prerequisite. Hence, we have employed ensembles of weather scenarios, which are based on the NCAR WRF-ARW modelling system. The set of ensemble members was composed with variations in the choices of physics and parameterization schemes, and source of background fields for initial conditions with horizontal grid resolutions in the one to two km range. In addition, the vertical grid structure was defined to ensure at least ten levels within the boundary layer and two from the bottom to the top of the turbine. This approach enables us to estimate the variability of winds at the farms and how it is distributed over the region. Further, we analyze the potential differences in structural risks at these farms during the 2009 winter season, and whether such differences in wind and weather patterns should be considered in choice of turbine design, installation and operations. We believe that this methodology can be extended to provide an estimate for mean annual energy production at a wind farm with the potential to improve the quality of siting and layout.

Weather data for simplified energy calculation methods. Volume II. Middle United States: TRY data

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

Olsen, A.R.; Moreno, S.; Deringer, J.

1984-08-01

The objective of this report is to provide a source of weather data for direct use with a number of simplified energy calculation methods available today. Complete weather data for a number of cities in the United States are provided for use in the following methods: degree hour, modified degree hour, bin, modified bin, and variable degree day. This report contains sets of weather data for 22 cities in the continental United States using Test Reference Year (TRY) source weather data. The weather data at each city has been summarized in a number of ways to provide differing levels ofmore » detail necessary for alternative simplified energy calculation methods. Weather variables summarized include dry bulb and wet bulb temperature, percent relative humidity, humidity ratio, wind speed, percent possible sunshine, percent diffuse solar radiation, total solar radiation on horizontal and vertical surfaces, and solar heat gain through standard DSA glass. Monthly and annual summaries, in some cases by time of day, are available. These summaries are produced in a series of nine computer generated tables.« less

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

Massada, Avi Bar; Radeloff, Volker C.; Stewart, Susan I.; Hawbaker, Todd J.

2009-01-01

The rapid growth of housing in and near the wildland–urban interface (WUI) increases wildfirerisk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfirerisk to a 60,000 ha WUI area in northwesternWisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfirerisk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfirerisk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfirerisk and those most vulnerable under extreme weather conditions.

Operational evapotranspiration mapping using remote sensing and weather datasets: a new parameterization for the SSEB approach

USGS Publications Warehouse

Senay, Gabriel B.; Bohms, Stefanie; Singh, Ramesh K.; Gowda, Prasanna H.; Velpuri, Naga Manohar; Alemu, Henok; Verdin, James P.

2013-01-01

The increasing availability of multi-scale remotely sensed data and global weather datasets is allowing the estimation of evapotranspiration (ET) at multiple scales. We present a simple but robust method that uses remotely sensed thermal data and model-assimilated weather fields to produce ET for the contiguous United States (CONUS) at monthly and seasonal time scales. The method is based on the Simplified Surface Energy Balance (SSEB) model, which is now parameterized for operational applications, renamed as SSEBop. The innovative aspect of the SSEBop is that it uses predefined boundary conditions that are unique to each pixel for the "hot" and "cold" reference conditions. The SSEBop model was used for computing ET for 12 years (2000-2011) using the MODIS and Global Data Assimilation System (GDAS) data streams. SSEBop ET results compared reasonably well with monthly eddy covariance ET data explaining 64% of the observed variability across diverse ecosystems in the CONUS during 2005. Twelve annual ET anomalies (2000-2011) depicted the spatial extent and severity of the commonly known drought years in the CONUS. More research is required to improve the representation of the predefined boundary conditions in complex terrain at small spatial scales. SSEBop model was found to be a promising approach to conduct water use studies in the CONUS, with a similar opportunity in other parts of the world. The approach can also be applied with other thermal sensors such as Landsat.

Atmospheric monitoring and model applications at the Pierre Auger Observatory

NASA Astrophysics Data System (ADS)

Keilhauer, Bianca

2015-03-01

The Pierre Auger Observatory detects high-energy cosmic rays with energies above ˜1017 eV. It is built as a multi-hybrid detector measuring extensive air showers with different techniques. For the reconstruction of extensive air showers, the atmospheric conditions at the site of the Observatory have to be known quite well. This is particularly true for reconstructions based on data obtained by the fluorescence technique. For these data, not only the weather conditions near ground are relevant, most important are altitude-dependent atmospheric profiles. The Pierre Auger Observatory has set up a dedicated atmospheric monitoring programme at the site in the Mendoza province, Argentina. Beyond this, exploratory studies were performed in Colorado, USA, for possible installations in the northern hemisphere. In recent years, the atmospheric monitoring programme at the Pierre Auger Observatory was supplemented by applying data from atmospheric models. Both GDAS and HYSPLIT are developments by the US weather department NOAA and the data are freely available. GDAS is a global model of the atmospheric state parameters on a 1 degree geographical grid, based on real-time measurements and numeric weather predictions, providing a full altitude-dependent data set every 3 hours. HYSPLIT is a powerful tool to track the movement of air masses at various heights, and with it the aerosols. Combining local measurements of the atmospheric state variables and aerosol scattering with the given model data, advanced studies about atmospheric conditions can be performed and high precision air shower reconstructions are achieved.

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

The Analysis, Numerical Simulation, and Diagnosis of Extratropical Weather Systems

DTIC Science & Technology

1999-09-30

The Analysis, Numerical Simulation, and Diagnosis of Extratropical Weather Systems Dr. Melvyn A. Shapiro NOAA/Environmental Technology Laboratory...formulation, and numerical prediction of the life cycles of synoptic-scale and mesoscale extratropical weather systems, including the influence of planetary...scale inter-annual and intra-seasonal variability on their evolution. These weather systems include: extratropical oceanic and land-falling cyclones

A portable station for recording fire weather data

Treesearch

John R. Murray; Clive M. Countryman

1968-01-01

A portable station for recording fire weather data has been developed for use in wildland fires, prescribed burns, evaluating sites for fire weather stations, and fire research. Housed in a mechanic's tool box, the station weighs about 60 pounds. One man can have it ready to operate in about 15 minutes. The unit can record five weather variables, but additional...

Weather data for simplified energy calculation methods. Volume IV. United States: WYEC data

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

Olsen, A.R.; Moreno, S.; Deringer, J.

The objective of this report is to provide a source of weather data for direct use with a number of simplified energy calculation methods available today. Complete weather data for a number of cities in the United States are provided for use in the following methods: degree hour, modified degree hour, bin, modified bin, and variable degree day. This report contains sets of weather data for 23 cities using Weather Year for Energy Calculations (WYEC) source weather data. Considerable overlap is present in cities (21) covered by both the TRY and WYEC data. The weather data at each city hasmore » been summarized in a number of ways to provide differing levels of detail necessary for alternative simplified energy calculation methods. Weather variables summarized include dry bulb and wet bulb temperature, percent relative humidity, humidity ratio, wind speed, percent possible sunshine, percent diffuse solar radiation, total solar radiation on horizontal and vertical surfaces, and solar heat gain through standard DSA glass. Monthly and annual summaries, in some cases by time of day, are available. These summaries are produced in a series of nine computer generated tables.« less

Application of dynamical systems theory to global weather phenomena revealed by satellite imagery

NASA Technical Reports Server (NTRS)

Saltzman, Barry; Ebisuzaki, Wesley; Maasch, Kirk A.; Oglesby, Robert; Pandolfo, Lionel; Tang, Chung-Muh

1989-01-01

Theoretical studies of low frequency and seasonal weather variability; dynamical properties of observational and general circulation model (GCM)-generated records; effects of the hydrologic cycle and latent heat release on extratropical weather; and Earth-system science studies are summarized.

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

NASA Astrophysics Data System (ADS)

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

2010-09-01

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

Validating the Airspace Concept Evaluation System for Different Weather Days

NASA Technical Reports Server (NTRS)

Zelinski, Shannon; Meyn, Larry

2006-01-01

This paper extends the process for validating the Airspace Concept Evaluation System using real-world historical flight operational data. System inputs such as flight plans and airport en-route capacities, are generated and processed to create a realistic reproduction of a single day's operations within the National Airspace System. System outputs such as airport throughput, delays, and en-route sector loads are then compared to real world operational metrics and delay statistics for the reproduced day. The process is repeated for 4 historical days with high and low traffic volume and delay attributed to weather. These 4 days are simulated using default en-route capacities and variable en-route capacities used to emulate weather. The validation results show that default enroute capacity simulations are closer to real-world data for low weather days than high weather days. The use of reduced variable enroute capacities adds a large delay bias to ACES but delay trends between weather days are better represented.

Local weather, regional climate, and annual survival of the northern spotted owl

USGS Publications Warehouse

Glenn, E.M.; Anthony, R.G.; Forsman, E.D.; Olson, G.S.

2011-01-01

We used an information-theoretical approach and Cormack-Jolly-Seber models for open populations in program MARK to examine relationships between survival rates of Northern Spotted Owls and a variety of local weather variables and long-term climate variables. In four of the six populations examined, survival was positively associated with wetter than normal conditions during the growing season or high summer temperatures. At the three study areas located at the highest elevations, survival was positively associated with winter temperature but also had a negative or quadratic relation with the number of storms and winter precipitation. A metaanalysis of all six areas combined indicated that annual survival was most strongly associated with phase shifts in the Southern Oscillation and Pacific Decadal Oscillation, which reflect large-scale temperature and precipitation patterns in this region. Climate accounted for a variable amount (1-41%) of the total process variation in annual survival but for more year-to-year variation (3-66%) than did spatial variation among owl territories (0-7%). Negative associations between survival and cold, wet winters and nesting seasons were similar to those found in other studies of the Spotted Owl. The relationships between survival and growing-season precipitation and regional climate patterns, however, had not been reported for this species previously. Climate-change models for the first half of the 21st century predict warmer, wetter winters and hotter, drier summers for the Pacific Northwest. Our results indicate that these conditions could decrease Spotted Owl survival in some areas. Copyright ?? The Cooper Ornithological Society 2011.

Sensitivity of extreme precipitation to temperature: the variability of scaling factors from a regional to local perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Kirchengast, G.

2018-06-01

Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.

Sea Buckthorn (Hippophaë rhamnoides ssp. rhamnoides) Berries in Nordic Environment: Compositional Response to Latitude and Weather Conditions.

PubMed

Zheng, Jie; Kallio, Heikki; Yang, Baoru

2016-06-22

Flavonol glycosides (FGs) in sea buckthorn (Hippophaë rhamnoides ssp. rhamnoides) berries of varieties 'Tytti' and 'Terhi', cultivated in northern Finland (68°02' N) for six years and southern Finland (60°23' N) for seven years, were investigated and compared by HPLC-DAD-ESI-MS/MS. The average total content of 23 identified glycosides of isorhamnetin and quercetin was 103 ± 23 and 110 ± 21 mg/100 g fresh berries in 'Terhi' and 'Tytti', respectively. The total contents of FGs, flavonol diglycosides, and triglycosides in both varieties were higher in the north than in the south, whereas total flavonol monoglycoside content behaved vice versa (p < 0.05). Among the 89 weather variables studied, the sum of the daily mean temperatures that are 5 °C or higher from the start of growth season until the day of harvest was the most important variable which associated negatively with the accumulation of FGs in berries. Such influence was much stronger in berries from the north than from the south.

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

76 FR 78141 - Pilot, Flight Instructor, and Pilot School Certification; Technical Amendment

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-16

... command under IFR or in weather conditions less than the minimums prescribed for VFR. Finally, this... pilot in command under IFR or in weather conditions less than the minimums prescribed for VFR. Under... command under IFR or in weather conditions less than the minimums prescribed for VFR. In the 2009 final...

How climate and weather affect the erosion risk in the northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Wahl, T.; Plant, N. G.

2015-12-01

Oceanographic variables such as mean sea level, tides, storm surges, and waves are drivers of erosion, and they act on different time scales ranging from hours (associated with weather) to seasonal and decadal variations and trends (associated with climate). Here we explore how the related sea-state conditions affect the erosion risk in the northern Gulf of Mexico for past and future climate scenarios. From the climate perspective we find that long-term trends in the relevant variables have caused an increase of ~30% in the erosion risk since the 1980s; at least half of this increase was due to changes in the wave climate. In the next decades, sea level rise will likely become the dominating driver and may, in combination with ongoing changes in the wave climate (and depending on the emission scenario), escalate the erosion risk by up to 300% over the next 30 years. We also find significant changes in the seasonal cycles of sea level and significant wave height, which have in combination caused a considerable increase of the erosion risk in summer and decrease in winter (superimposed onto the long-term trends). The influence of weather is assessed with a copula-based multivariate sea storm model in a Monte-Carlo framework; i.e. we simulate hundreds of thousands of artificial but physically consistent sea-state conditions to quantify how different our understanding of the present day erosion risk would be if we had seen more or less extreme combinations of the different sea-state parameters over the last three decades. We find, for example, that total water levels (tide + surge + wave run-up) associated with 100-year return periods may be underestimated by up to 30% and that the average number of impact hours - when total water levels exceeded the height of the dune toe (collision) or dune crest (overwash) - could have been up to 50% higher than what we inferred based on the actually observed oceanographic conditions. Assessing erosion risk in such a probabilistic way while accounting for non-stationarity due to climate variability and change can help decision makers and planners to implement improved monitoring and adaptation strategies for long-term sustainability of the coastline and barrier islands.

Erosion risk in the northern Gulf of Mexico - the effects of climate and weather

NASA Astrophysics Data System (ADS)

Wahl, Thomas; Plant, Nathaniel G.; Long, Joseph W.

2016-04-01

Oceanographic variables such as mean sea level, tides, storm surges, and waves are drivers of erosion, and they act on different time scales ranging from hours (associated with weather) to seasonal and decadal variations and trends (associated with climate). Here we explore how the related sea-state conditions affect the erosion risk in the northern Gulf of Mexico for past and future climate scenarios. From the climate perspective we find that long-term trends in the relevant variables have caused an increase of ~30% in the erosion risk since the 1980s; at least half of this increase was due to changes in the wave climate. In the next decades, sea level rise will likely become the dominating driver and may, in combination with ongoing changes in the wave climate (and depending on the emission scenario), escalate the erosion risk by up to 300% over the next 30 years. We also find significant changes in the seasonal cycles of sea level and significant wave height, which have in combination caused a considerable increase of the erosion risk in summer and decrease in winter (superimposed onto the long-term trends). The influence of weather is assessed with a copula-based multivariate sea storm model in a Monte-Carlo framework; i.e. we simulate hundreds of thousands of artificial but physically consistent sea-state conditions to quantify how different our understanding of the present day erosion risk would be if we had seen more or less extreme combinations of the different sea-state parameters over the last three decades. We find, for example, that total water levels (tide + surge + wave run-up) associated with 100-year return periods may be underestimated by up to 30% and that the average number of impact hours - when total water levels exceeded the height of the dune toe (collision) or dune crest (overwash) - could have been up to 50% higher than what we inferred based on the actually observed oceanographic conditions. Assessing erosion risk in such a probabilistic way while accounting for non-stationarity due to climate variability and change can help decision makers and planners to implement improved monitoring and adaptation strategies for long-term sustainability of the coastline and barrier islands.

PID temperature controller in pig nursery: spatial characterization of thermal environment

NASA Astrophysics Data System (ADS)

de Souza Granja Barros, Juliana; Rossi, Luiz Antonio; Menezes de Souza, Zigomar

2018-05-01

The use of enhanced technologies of temperature control can improve the thermal conditions in environments of livestock facilities. The objective of this study was to evaluate the spatial distribution of the thermal environment variables in a pig nursery with a heating system with two temperature control technologies based on the geostatistical analysis. The following systems were evaluated: overhead electrical resistance with Proportional, Integral, and Derivative (PID) controller and overhead electrical resistance with a thermostat. We evaluated the climatic variables: dry bulb temperature (Tbs), air relative humidity (RH), temperature and humidity index (THI), and enthalpy in the winter, at 7:00, 12:00, and 18:00 h. The spatial distribution of these variables was mapped by kriging. The results showed that the resistance heating system with PID controllers improved the thermal comfort conditions in the pig nursery in the coldest hours, maintaining the spatial distribution of the air temperature more homogeneous in the pen. During the hottest weather, neither system provided comfort.

PID temperature controller in pig nursery: spatial characterization of thermal environment

NASA Astrophysics Data System (ADS)

de Souza Granja Barros, Juliana; Rossi, Luiz Antonio; Menezes de Souza, Zigomar

2017-11-01

The use of enhanced technologies of temperature control can improve the thermal conditions in environments of livestock facilities. The objective of this study was to evaluate the spatial distribution of the thermal environment variables in a pig nursery with a heating system with two temperature control technologies based on the geostatistical analysis. The following systems were evaluated: overhead electrical resistance with Proportional, Integral, and Derivative (PID) controller and overhead electrical resistance with a thermostat. We evaluated the climatic variables: dry bulb temperature (Tbs), air relative humidity (RH), temperature and humidity index (THI), and enthalpy in the winter, at 7:00, 12:00, and 18:00 h. The spatial distribution of these variables was mapped by kriging. The results showed that the resistance heating system with PID controllers improved the thermal comfort conditions in the pig nursery in the coldest hours, maintaining the spatial distribution of the air temperature more homogeneous in the pen. During the hottest weather, neither system provided comfort.

Does Life Seem Better on a Sunny Day? Examining the Association between Daily Weather Conditions and Life Satisfaction Judgments

PubMed Central

Lucas, Richard E.; Lawless, Nicole M.

2013-01-01

Weather conditions have been shown to affect a broad range of thoughts, feelings, and behaviors. The current study examines whether these effects extend to life satisfaction judgments. We examine the association between daily weather conditions and life satisfaction in a representative sample of over 1 million Americans from all 50 states who were assessed (in a cross-sectional design) over a 5-year period. Most daily weather conditions were unrelated to life satisfaction judgments, and those effects that were significant reflect very small effects that were only detectable because of the extremely high power of these analyses. These results show that weather does not reliably affect judgments of life satisfaction. PMID:23607534

Solar variability, weather, and climate

NASA Technical Reports Server (NTRS)

1982-01-01

Advances in the understanding of possible effects of solar variations on weather and climate are most likely to emerge by addressing the subject in terms of fundamental physical principles of atmospheric sciences and solar-terrestrial physis. The limits of variability of solar inputs to the atmosphere and the depth in the atmosphere to which these variations have significant effects are determined.

Influence of weather and climate variables on the basal area growth of individual shortleaf pine trees

Treesearch

Pradip Saud; Thomas B. Lynch; Duncan S. Wilson; John Stewart; James M. Guldin; Bob Heinemann; Randy Holeman; Dennis Wilson; Keith Anderson

2015-01-01

An individual-tree basal area growth model previously developed for even-aged naturally occurring shortleaf pine trees (Pinus echinata Mill.) in western Arkansas and southeastern Oklahoma did not include weather variables. Individual-tree growth and yield modeling of shortleaf pine has been carried out using the remeasurements of over 200 plots...

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

PubMed

Brandon, Caitlin A; Gill, Dawn P; Speechley, Mark; Gilliland, Jason; Jones, Gareth R

2009-04-01

Adequate daily physical activity (PA) is important for maintaining functional capacity and independence in older adults. However, most older adults in Canada do not engage in enough PA to sustain fitness and functional independence. Environmental influences, such as warmer daytime temperatures, may influence PA participation; however, few studies have examined the effect of summertime temperatures on PA levels in older adults. This investigation measured the influence of summertime weather variables on PA in 48 community-dwelling older adults who were randomly recruited from a local seniors' community centre. Each participant wore an accelerometer for a single 7-consecutive-day period (between 30 May and 9 August 2006) during waking hours, and completed a PA logbook to remark on major daily PA events. Local weather variables were collected from a national weather service and compared with PA counts per minute. Regression analysis revealed a curvilinear relationship between log-transformed PA and mean daily temperature (r2 = 0.025; p < 0.05). Linear mixed effects models that accounted for repeated measures nested within individuals were performed for monthly periods, meteorological variables, sex, age, and estimated maximal oxygen consumption, with PA as the dependent variable. Age and Air Quality Index remained significant variables within the model. Higher fitness levels had no effect on allowing individuals to perform more vigorous PA in warmer temperatures.

Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor

NASA Technical Reports Server (NTRS)

Rouse, J. W., Jr. (Principal Investigator); Haas, R. H.; Deering, D. W.; Schell, J. A.; Harlan, J. C.

1974-01-01

The author has identified the following significant results. The Great Plains Corridor rangeland project successfully utilized natural vegetation systems as phenological indicators of seasonal development and climatic effects upon regional growth conditions. An effective method was developed for quantitative measurement of vegetation conditions, including green biomass estimates, recorded in bands 5 and 6, corrected for sun angle, were used to compute a ratio parameter (TV16) which is shown to be highly correlated with green biomass and vegatation moisture content. Analyses results of ERTS-1 digital data and correlated ground data are summarized. Attention was given to analyzing weather influences and test site variables on vegetation condition measurements with ERTS-1 data.

Climate Modulation of Pb Isotopes in the Deep Indian Ocean Linked to the Himalayan Chemical Weathering

NASA Astrophysics Data System (ADS)

Galy, A.; Wilson, D. J.; Piotrowski, A. M.; Gattacceca, J. C.

2015-12-01

Leaching of sediments from the Eastern flank of the Chagos-Laccadive ridge, the 90°E ridge and the distal part of the Bengal Fan have extracted authigenic lead (Pb). This allowed the reconstruction of the Pb isotope evolution of the deep central Indian Ocean over the past 250 thousand years at ˜3 kyr resolution and over the past 20 Ma at 2-3Myr resolution. High frequency temporal variations recorded close to the ridges define a binary mixing line that records the variable admixture of radiogenic Pb with a signature characteristic of the composition of Ganges-Brahmaputra river sediments to the stable unradiogenic widely-distributed Pb source, from mid-ocean ridges or possibly volcanic aerosols. The temporal variations suggest an enhancement of Himalayan contributions by two to three times during interglacial periods, indicating that climate modulates the supply of dissolved elements to the ocean. While these changes could accurately record variations in the continental chemical weathering flux in response to warmer and wetter conditions during interglacials, the relative proportions of Pb derived from the Ganges and Brahmaputra appear to have been constant through time. This observation may point towards particulate-dissolved interactions in the estuary or pro-delta as a buffer of short timescale variability of the fluvial inputs. The changes recorded directly in the turbiditic fan during the Neogene are more difficult to interpret and will be discussed in lengh. If the last Ma data points are consistent with the 2 records from either side of the sedimentary basin, the input from the weathering of the Himalaya could have been impacted by 1) the uplift of more radiogenic terrane consistent with the onset of the Main Boundary Thrust around 10 Ma, and 2) changes in the weathering style pointing toward a more uncongruent weathering between 7 and 1 Ma.

POPULATION SYNCHRONY WITHIN AND AMONG LEPIDOPTERA SPECIES IN RELATION TO WEATHER, PHYLOGENY, AND LARVEL PHENOLOGY

EPA Science Inventory

1. The population dynamics of native herbivore species in central Appalachian deciduous forests were studied by analysing patterns of synchrony among intra- and interspecific populations and weather. 2. Spatial synchrony of 10 Lepidoptera species and three weather variables (min...

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

NASA Astrophysics Data System (ADS)

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.

Atmospheric circulation classification comparison based on wildfires in Portugal

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

Linking the M&Rfi Weather Generator with Agrometeorological Models

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Trnka, Miroslav

2015-04-01

Realistic meteorological inputs (representing the present and/or future climates) for the agrometeorological model simulations are often produced by stochastic weather generators (WGs). This contribution presents some methodological issues and results obtained in our recent experiments. We also address selected questions raised in the synopsis of this session. The input meteorological time series for our experiments are produced by the parametric single site weather generator (WG) Marfi, which is calibrated from the available observational data (or interpolated from surrounding stations). To produce meteorological series representing the future climate, the WG parameters are modified by climate change scenarios, which are prepared by the pattern scaling method: the standardised scenarios derived from Global or Regional Climate Models are multiplied by the change in global mean temperature (ΔTG) determined by the simple climate model MAGICC. The presentation will address following questions: (i) The dependence of the quality of the synthetic weather series and impact results on the WG settings. An emphasis will be put on an effect of conditioning the daily WG on monthly WG (presently being one of our hot topics), which aims at improvement of the reproduction of the low-frequency weather variability. Comparison of results obtained with various WG settings is made in terms of climatic and agroclimatic indices (including extreme temperature and precipitation characteristics and drought indices). (ii) Our methodology accounts for the uncertainties coming from various sources. We will show how the climate change impact results are affected by 1. uncertainty in climate modelling, 2. uncertainty in ΔTG, and 3. uncertainty related to the complexity of the climate change scenario (focusing on an effect of inclusion of changes in variability into the climate change scenarios). Acknowledgements: This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248. The weather generator is being developed within the frame of WG4VALUE project (LD12029), which is supported by Ministry of Education, Youth and Sports and linked to the COST action ES1102 VALUE.

Probabilistic forecasting of extreme weather events based on extreme value theory

NASA Astrophysics Data System (ADS)

Van De Vyver, Hans; Van Schaeybroeck, Bert

2016-04-01

Extreme events in weather and climate such as high wind gusts, heavy precipitation or extreme temperatures are commonly associated with high impacts on both environment and society. Forecasting extreme weather events is difficult, and very high-resolution models are needed to describe explicitly extreme weather phenomena. A prediction system for such events should therefore preferably be probabilistic in nature. Probabilistic forecasts and state estimations are nowadays common in the numerical weather prediction community. In this work, we develop a new probabilistic framework based on extreme value theory that aims to provide early warnings up to several days in advance. We consider the combined events when an observation variable Y (for instance wind speed) exceeds a high threshold y and its corresponding deterministic forecasts X also exceeds a high forecast threshold y. More specifically two problems are addressed:} We consider pairs (X,Y) of extreme events where X represents a deterministic forecast, and Y the observation variable (for instance wind speed). More specifically two problems are addressed: Given a high forecast X=x_0, what is the probability that Y>y? In other words: provide inference on the conditional probability: [ Pr{Y>y|X=x_0}. ] Given a probabilistic model for Problem 1, what is the impact on the verification analysis of extreme events. These problems can be solved with bivariate extremes (Coles, 2001), and the verification analysis in (Ferro, 2007). We apply the Ramos and Ledford (2009) parametric model for bivariate tail estimation of the pair (X,Y). The model accommodates different types of extremal dependence and asymmetry within a parsimonious representation. Results are presented using the ensemble reforecast system of the European Centre of Weather Forecasts (Hagedorn, 2008). Coles, S. (2001) An Introduction to Statistical modelling of Extreme Values. Springer-Verlag.Ferro, C.A.T. (2007) A probability model for verifying deterministic forecasts of extreme events. Wea. Forecasting {22}, 1089-1100.Hagedorn, R. (2008) Using the ECMWF reforecast dataset to calibrate EPS forecasts. ECMWF Newsletter, {117}, 8-13.Ramos, A., Ledford, A. (2009) A new class of models for bivariate joint tails. J.R. Statist. Soc. B {71}, 219-241.

Linking Surface and Subsurface Processes: Implications for Seismic Hazards in Southern California

NASA Astrophysics Data System (ADS)

Lin, J. C.; Moon, S.; Yong, A.; Meng, L.; Martin, A. J.; Davis, P. M.

2017-12-01

Earth's surface and subsurface processes such as bedrock weathering, soil production, and river incision can influence and be influenced by spatial variations in the mechanical strength of surface material. Mechanically weakened rocks tend to have reduced seismic velocity, which can result in larger ground-motion amplification and greater potential for earthquake-induced damages. However, the influence and extent of surface and subsurface processes on the mechanical strength of surface material and seismic site conditions in southern California remain unclear. In this study, we examine whether physics-based models of surface and subsurface processes can explain the spatial variability and non-linearity of near-surface seismic velocity in southern California. We use geophysical measurements (Yong et al., 2013; Ancheta et al., 2014), consisting of shear-wave velocity (Vs) tomography data, Vs profiles, and the time-averaged Vs in the upper 30 m of the crust (Vs30) to infer lateral and vertical variations of surface material properties. Then, we compare Vs30 values with geologic and topographic attributes such as rock type, slope, elevation, and local relief, as well as metrics for surface processes such as soil production and bedrock weathering from topographic stress, frost cracking, chemical reactions, and vegetation presence. Results from this study will improve our understanding of physical processes that control subsurface material properties and their influences on local variability in seismic site conditions.

Global Weather States and Their Properties from Passive and Active Satellite Cloud Retrievals

NASA Technical Reports Server (NTRS)

Tselioudis, George; Rossow, William; Zhang, Yuanchong; Konsta, Dimitra

2013-01-01

In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness-cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s.

The influence of weather on health-related help-seeking behavior of senior citizens in Hong Kong.

PubMed

Wong, Ho Ting; Chiu, Marcus Yu Lung; Wu, Cynthia Sau Ting; Lee, Tsz Cheung

2015-03-01

It is believed that extreme hot and cold weather has a negative impact on general health conditions. Much research focuses on mortality, but there is relatively little community health research. This study is aimed at identifying high-risk groups who are sensitive to extreme weather conditions, in particular, very hot and cold days, through an analysis of the health-related help-seeking patterns of over 60,000 Personal Emergency Link (PE-link) users in Hong Kong relative to weather conditions. In the study, 1,659,716 PE-link calls to the help center were analyzed. Results showed that females, older elderly, people who did not live alone, non-subsidized (relatively high-income) users, and those without medical histories of heart disease, hypertension, stroke, and diabetes were more sensitive to extreme weather condition. The results suggest that using official government weather forecast reports to predict health-related help-seeking behavior is feasible. An evidence-based strategic plan could be formulated by using a method similar to that used in this study to identify high-risk groups. Preventive measures could be established for protecting the target groups when extreme weather conditions are forecasted.

The influence of weather on health-related help-seeking behavior of senior citizens in Hong Kong

NASA Astrophysics Data System (ADS)

Wong, Ho Ting; Chiu, Marcus Yu Lung; Wu, Cynthia Sau Ting; Lee, Tsz Cheung

2015-03-01

It is believed that extreme hot and cold weather has a negative impact on general health conditions. Much research focuses on mortality, but there is relatively little community health research. This study is aimed at identifying high-risk groups who are sensitive to extreme weather conditions, in particular, very hot and cold days, through an analysis of the health-related help-seeking patterns of over 60,000 Personal Emergency Link (PE-link) users in Hong Kong relative to weather conditions. In the study, 1,659,716 PE-link calls to the help center were analyzed. Results showed that females, older elderly, people who did not live alone, non-subsidized (relatively high-income) users, and those without medical histories of heart disease, hypertension, stroke, and diabetes were more sensitive to extreme weather condition. The results suggest that using official government weather forecast reports to predict health-related help-seeking behavior is feasible. An evidence-based strategic plan could be formulated by using a method similar to that used in this study to identify high-risk groups. Preventive measures could be established for protecting the target groups when extreme weather conditions are forecasted.

The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States.

PubMed

McGeehin, M A; Mirabelli, M

2001-05-01

Heat and heat waves are projected to increase in severity and frequency with increasing global mean temperatures. Studies in urban areas show an association between increases in mortality and increases in heat, measured by maximum or minimum temperature, heat index, and sometimes, other weather conditions. Health effects associated with exposure to extreme and prolonged heat appear to be related to environmental temperatures above those to which the population is accustomed. Models of weather-mortality relationships indicate that populations in northeastern and midwestern U.S. cities are likely to experience the greatest number of illnesses and deaths in response to changes in summer temperature. Physiologic and behavioral adaptations may reduce morbidity and mortality. Within heat-sensitive regions, urban populations are the most vulnerable to adverse heat-related health outcomes. The elderly, young children, the poor, and people who are bedridden or are on certain medications are at particular risk. Heat-related illnesses and deaths are largely preventable through behavioral adaptations, including the use of air conditioning and increased fluid intake. Overall death rates are higher in winter than in summer, and it is possible that milder winters could reduce deaths in winter months. However, the relationship between winter weather and mortality is difficult to interpret. Other adaptation measures include heat emergency plans, warning systems, and illness management plans. Research is needed to identify critical weather parameters, the associations between heat and nonfatal illnesses, the evaluation of implemented heat response plans, and the effectiveness of urban design in reducing heat retention.

Development of a New Data Tool for Computing Launch and Landing Availability with Respect to Surface Weather

NASA Technical Reports Server (NTRS)

Burns, K. Lee; Altino, Karen

2008-01-01

The Marshall Space Flight Center Natural Environments Branch has a long history of expertise in the modeling and computation of statistical launch availabilities with respect to weather conditions. Their existing data analysis product, the Atmospheric Parametric Risk Assessment (APRA) tool, computes launch availability given an input set of vehicle hardware and/or operational weather constraints by calculating the climatological probability of exceeding the specified constraint limits, APRA has been used extensively to provide the Space Shuttle program the ability to estimate impacts that various proposed design modifications would have to overall launch availability. The model accounts for both seasonal and diurnal variability at a single geographic location and provides output probabilities for a single arbitrary launch attempt. Recently, the Shuttle program has shown interest in having additional capabilities added to the APRA model, including analysis of humidity parameters, inclusion of landing site weather to produce landing availability, and concurrent analysis of multiple sites, to assist in operational landing site selection. In addition, the Constellation program has also expressed interest in the APRA tool, and has requested several additional capabilities to address some Constellation-specific issues, both in the specification and verification of design requirements and in the development of operations concepts. The combined scope of the requested capability enhancements suggests an evolution of the model beyond a simple revision process. Development has begun for a new data analysis tool that will satisfy the requests of both programs. This new tool, Probabilities of Atmospheric Conditions and Environmental Risk (PACER), will provide greater flexibility and significantly enhanced functionality compared to the currently existing tool.

Adverse weather impacts on arable cropping systems

NASA Astrophysics Data System (ADS)

Gobin, Anne

2016-04-01

Damages due to extreme or adverse weather strongly depend on crop type, crop stage, soil conditions and management. The impact is largest during the sensitive periods of the farming calendar, and requires a modelling approach to capture the interactions between the crop, its environment and the occurrence of the meteorological event. The hypothesis is that extreme and adverse weather events can be quantified and subsequently incorporated in current crop models. Since crop development is driven by thermal time and photoperiod, a regional crop model was used to examine the likely frequency, magnitude and impacts of frost, drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages. Risk profiles and associated return levels were obtained by fitting generalized extreme value distributions to block maxima for air humidity, water balance and temperature variables. The risk profiles were subsequently confronted with yields and yield losses for the major arable crops in Belgium, notably winter wheat, winter barley, winter oilseed rape, sugar beet, potato and maize at the field (farm records) to regional scale (statistics). The average daily vapour pressure deficit (VPD) and reference evapotranspiration (ET0) during the growing season is significantly lower (p < 0.001) and has a higher variability before 1988 than after 1988. Distribution patterns of VPD and ET0 have relevant impacts on crop yields. The response to rising temperatures depends on the crop's capability to condition its microenvironment. Crops short of water close their stomata, lose their evaporative cooling potential and ultimately become susceptible to heat stress. Effects of heat stress therefore have to be combined with moisture availability such as the precipitation deficit or the soil water balance. Risks of combined heat and moisture deficit stress appear during the summer. These risks are subsequently related to crop damage. The methodology of defining meteorological risks and subsequently relating the risk to the cropping calendar will be demonstrated for major arable crops in Belgium. Physically based crop models assist in understanding the links between adverse weather events, sensitive crop stages and crop damage. Financial support was obtained from Belspo under research contract SD/RI/03A.

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

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

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE PAGES

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.; ...

2018-03-01

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less

Long-term change of the atmospheric energy cycles and weather disturbances

NASA Astrophysics Data System (ADS)

Kim, WonMoo; Choi, Yong-Sang

2017-11-01

Weather disturbances are the manifestation of mean atmospheric energy cascading into eddies, thus identifying atmospheric energy structure is of fundamental importance to understand the weather variability in a changing climate. The question is whether our observational data can lead to a consistent diagnosis on the energy conversion characteristics. Here we investigate the atmospheric energy cascades by a simple framework of Lorenz energy cycle, and analyze the energy distribution in mean and eddy fields as forms of potential and kinetic energy. It is found that even the widely utilized independent reanalysis datasets, NCEP-DOE AMIP-II Reanalysis (NCEP2) and ERA-Interim (ERA-INT), draw different conclusions on the change of weather variability measured by eddy-related kinetic energy. NCEP2 shows an increased mean-to-eddy energy conversion and enhanced eddy activity due to efficient baroclinic energy cascade, but ERA-INT shows relatively constant energy cascading structure between the 1980s and the 2000s. The source of discrepancy mainly originates from the uncertainties in hydrological variables in the mid-troposphere. Therefore, much efforts should be made to improve mid-tropospheric observations for more reliable diagnosis of the weather disturbances as a consequence of man-made greenhouse effect.

Characterization of freezing precipitation events through other meteorological variables and their recent changes over Northern Extratropics

NASA Astrophysics Data System (ADS)

Groisman, P. Y.; Yin, X.; Bulygina, O.

2017-12-01

Freezing precipitation events intertwine with agriculture, recreation, energy consumption, and seasonal transportation cycles of human activities. Using supplementary synoptic reports at 1,500 long-term stations of North America and Northern Eurasia, we created climatology of freezing precipitation near the surface and found significant changes (increases) in these occurrences in the past decade at high latitudes/elevations (Groisman et al. 2016; updated). Firstly, we document narrow boundaries of near surface temperature and humidity fields when freezing precipitation events occur; these are necessary but insufficient conditions of their occurrence. Secondly, using the upper air data at the sites collocated with in situ observations of freezing events, we quantify the typical pattern of lower troposphere temperature anomalies during freezing events: At the same locations and Julian days, the presence of freezing event at the surface is associated with significantly warmer temperatures in the lower troposphere; comparison of temperatures at nearest days before and after the freezing events with days during these events also shows statistically significant positive temperature anomalies in the lower troposphere to 500 hPa (on average, +3 to 4 °C) In the days with freezing events, vertical air temperature gradients between surface and 850 hPa become less than usual with frequent inversions, when the tropospheric air is warmer than at the surface. The above features of the lower tropospheric temperature, near-surface temperature and humidity represent a combination of weather conditions conducive for precipitation, if it happens, falling in the freezing rain form. The in situ reports of freezing events at synoptic stations allow us to estimate temporary and spatial distributions of such "special weather conditions". Thus, a posteriori high probability of freezing events under these weather conditions invokes similar probabilities of freezing rain over the ungauged terrain, where we do not have special synoptic reports but can reproduce these "special weather conditions" from less sophisticated observational networks and/or reanalyses. Reference: Groisman et al. 2016: Recent changes in the frequency of freezing precipitation in North America and Northern Eurasia. Environ Res Lett 11 045007.

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

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-05

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

Reconstruction of Historical Weather by Assimilating Old Weather Diary Data

NASA Astrophysics Data System (ADS)

Neluwala, P.; Yoshimura, K.; Toride, K.; Hirano, J.; Ichino, M.; Okazaki, A.

2017-12-01

Climate can control not only human life style but also other living beings. It is important to investigate historical climate to understand the current and future climates. Information about daily weather can give a better understanding of past life on earth. Long-term weather influences crop calendar as well as the development of civilizations. Unfortunately, existing reconstructed daily weather data are limited to 1850s due to the availability of instrumental data. The climate data prior to that are derived from proxy materials (e.g., tree-ring width, ice core isotopes, etc.) which are either in annual or decadal scale. However, there are many historical documents which contain information about weather such as personal diaries. In Japan, around 20 diaries in average during the 16th - 19th centuries have been collected and converted into a digitized form. As such, diary data exist in many other countries. This study aims to reconstruct historical daily weather during the 18th and 19th centuries using personal daily diaries which have analogue weather descriptions such as `cloudy' or `sunny'. A recent study has shown the possibility of assimilating coarse weather data using idealized experiments. We further extend this study by assimilating modern weather descriptions similar to diary data in recent periods. The Global Spectral model (GSM) of National Centers for Environmental Prediction (NCEP) is used to reconstruct weather with the Local Ensemble Kalman filter (LETKF). Descriptive data are first converted to model variables such as total cloud cover (TCC), solar radiation and precipitation using empirical relationships. Those variables are then assimilated on a daily basis after adding random errors to consider the uncertainty of actual diary data. The assimilation of downward short wave solar radiation using weather descriptions improves RMSE from 64.3 w/m2 to 33.0 w/m2 and correlation coefficient (R) from 0.5 to 0.8 compared with the case without any assimilation. Non-assimilated fields are improved as well (e.g., RMSE from 40% to 29% and R 0.1 to 0.5 improved in TCC). Similarly, the assimilation of other variables shows improvements in atmospheric fields. These findings indicate the potential to reconstruct historical weather for the last five centuries by assimilating available weather descriptions.

An outline of the review on space weather in Latin America: space science, research networks and space weather center

NASA Astrophysics Data System (ADS)

De Nardin, C. M.; Dasso, S.; Gonzalez-Esparza, A.

2016-12-01

The present work is an outline of a three-part review on space weather in Latin America. The first paper (part 1) comprises the evolution of several Latin American institutions investing in space science since the 1960's, focusing on the solar-terrestrial interactions, which today is commonly called space weather. Despite recognizing advances in space research in all of Latin America, this part 1 is restricted to the development observed in three countries in particular (Argentina, Brazil and Mexico), due to the fact that these countries have recently developed operational centers for monitoring space weather. The review starts with a brief summary of the first groups to start working with space science in Latin America. This first part of the review closes with the current status and the research interests of these groups, which are described in relation to the most significant works and challenges of the next decade in order to aid in the solving of space weather open issues. The second paper (part 2) comprises a summary of scientific challenges in space weather research that are considered to be open scientific questions and how they are being addressed in terms of instrumentation by the international community, including the Latin American groups. We also provide an inventory of the networks and collaborations being constructed in Latin America, including details on the data processing, capabilities and a basic description of the resulting variables. These instrumental networks currently used for space science research are gradually being incorporated into the space weather monitoring data pipelines as their data provides key variables for monitoring and forecasting space weather, which allow these centers to monitor space weather and issue warnings and alerts. The third paper (part 3) presents the decision process for the spinning off of space weather prediction centers from space science groups with our interpretation of the reason/opportunities that leads to this. Lastly, the constraints for the progress in space weather monitoring, research, and forecast are listed with recommendations to overcome them, which we believe will lead to the access of key variables for the monitoring and forecasting space weather, which will allow these centers to better monitor space weather and issue warnings and alerts.

Synopsis of the Review on Space Weather in Latin America: Space Science, Research Networks and Space Weather Center

NASA Astrophysics Data System (ADS)

Denardini, Clezio Marcos; Dasso, Sergio; Gonzalez-Esparza, Americo

2016-07-01

The present work is a synopsis of a three-part review on space weather in Latin America. The first paper (part 1) comprises the evolution of several Latin American institutions investing in space science since the 1960's, focusing on the solar-terrestrial interactions, which today is commonly called space weather. Despite recognizing advances in space research in all of Latin America, this part 1 is restricted to the development observed in three countries in particular (Argentina, Brazil and Mexico), due to the fact that these countries have recently developed operational centers for monitoring space weather. The review starts with a brief summary of the first groups to start working with space science in Latin America. This first part of the review closes with the current status and the research interests of these groups, which are described in relation to the most significant works and challenges of the next decade in order to aid in the solving of space weather open issues. The second paper (part 2) comprises a summary of scientific challenges in space weather research that are considered to be open scientific questions and how they are being addressed in terms of instrumentation by the international community, including the Latin American groups. We also provide an inventory of the networks and collaborations being constructed in Latin America, including details on the data processing, capabilities and a basic description of the resulting variables. These instrumental networks currently used for space science research are gradually being incorporated into the space weather monitoring data pipelines as their data provides key variables for monitoring and forecasting space weather, which allow these centers to monitor space weather and issue warnings and alerts. The third paper (part 3) presents the decision process for the spinning off of space weather prediction centers from space science groups with our interpretation of the reason/opportunities that leads to this. Lastly, the constraints for the progress in space weather monitoring, research, and forecast are listed with recommendations to overcome them, which we believe will lead to the access of key variables for the monitoring and forecasting space weather, which will allow these centers to better monitor space weather and issue warnings and alerts.

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

USDA-ARS?s Scientific Manuscript database

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

Soil Moisture as an Estimator for Crop Yield in Germany

NASA Astrophysics Data System (ADS)

Peichl, Michael; Meyer, Volker; Samaniego, Luis; Thober, Stephan

2015-04-01

Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological, phenological, geological, agronomic, and socio-economic variables are also considered to extend the model in order to reveal the proper causal relation. First results show that dry as well as wet extremes of SMI have a negative impact on crop yield for winter wheat. This indicates that soil moisture has at least a limiting affect on crop production.

Evaluating the applicability of using daily forecasts from seasonal prediction systems (SPSs) for agriculture: a case study of Nepal's Terai with the NCEP CFSv2

NASA Astrophysics Data System (ADS)

Jha, Prakash K.; Athanasiadis, Panos; Gualdi, Silvio; Trabucco, Antonio; Mereu, Valentina; Shelia, Vakhtang; Hoogenboom, Gerrit

2018-03-01

Ensemble forecasts from dynamic seasonal prediction systems (SPSs) have the potential to improve decision-making for crop management to help cope with interannual weather variability. Because the reliability of crop yield predictions based on seasonal weather forecasts depends on the quality of the forecasts, it is essential to evaluate forecasts prior to agricultural applications. This study analyses the potential of Climate Forecast System version 2 (CFSv2) in predicting the Indian summer monsoon (ISM) for producing meteorological variables relevant to crop modeling. The focus area was Nepal's Terai region, and the local hindcasts were compared with weather station and reanalysis data. The results showed that the CFSv2 model accurately predicts monthly anomalies of daily maximum and minimum air temperature (Tmax and Tmin) as well as incoming total surface solar radiation (Srad). However, the daily climatologies of the respective CFSv2 hindcasts exhibit significant systematic biases compared to weather station data. The CFSv2 is less capable of predicting monthly precipitation anomalies and simulating the respective intra-seasonal variability over the growing season. Nevertheless, the observed daily climatologies of precipitation fall within the ensemble spread of the respective daily climatologies of CFSv2 hindcasts. These limitations in the CFSv2 seasonal forecasts, primarily in precipitation, restrict the potential application for predicting the interannual variability of crop yield associated with weather variability. Despite these limitations, ensemble averaging of the simulated yield using all CFSv2 members after applying bias correction may lead to satisfactory yield predictions.

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

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Clayson, Carol Anne

2013-01-01

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

Understanding the Influence of Climate Forecasts on Farmer Decisions as Planned Behavior

NASA Astrophysics Data System (ADS)

Artikov, Ikrom; Hoffman, Stacey J.; Lynne, Gary D.; Pytlik Zillig, Lisa M.; Hu, Qi; Tomkins, Alan J.; Hubbard, Kenneth G.; Hayes, Michael J.; Waltman, William

2006-09-01

Results of a set of four regression models applied to recent survey data of farmers in eastern Nebraska suggest the causes that drive farmer intentions of using weather and climate information and forecasts in farming decisions. The model results quantify the relative importance of attitude, social norm, perceived behavioral control, and financial capability in explaining the influence of climate-conditions information and short-term and long-term forecasts on agronomic, crop insurance, and crop marketing decisions. Attitude, serving as a proxy for the utility gained from the use of such information, had the most profound positive influence on the outcome of all the decisions, followed by norms. The norms in the community, as a proxy for the utility gained from allowing oneself to be influenced by others, played a larger role in agronomic decisions than in insurance or marketing decisions. In addition, the interaction of controllability (accuracy, availability, reliability, timeliness of weather and climate information), self-efficacy (farmer ability and understanding), and general preference for control was shown to be a substantive cause. Yet control variables also have an economic side: The farm-sales variable as a measure of financial ability and motivation intensified and clarified the role of control while also enhancing the statistical robustness of the attitude and norms variables in better clarifying how they drive the influence. Overall, the integrated model of planned behavior from social psychology and derived demand from economics, that is, the “planned demand model,” is more powerful than models based on either of these approaches alone. Taken together, these results suggest that the “human dimension” needs to be better recognized so as to improve effective use of climate and weather forecasts and information for farming decision making.

Wyoming Department of Transportation (WYDOT) road condition reporting application for weather responsive traffic management.

DOT National Transportation Integrated Search

2016-01-01

FHWAs Road Weather Management Program partnered with WYDOT to develop a new software application to improve the way maintenance personnel report road and weather conditions to their statewide Transportation Management Center (TMC), recommend varia...

Temporal Associations between Weather and Headache: Analysis by Empirical Mode Decomposition

PubMed Central

Yang, Albert C.; Fuh, Jong-Ling; Huang, Norden E.; Shia, Ben-Chang; Peng, Chung-Kang; Wang, Shuu-Jiun

2011-01-01

Background Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area. Methodology/Principal Findings The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3% of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts. Conclusions/Significance Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons. PMID:21297940

Climate services in the tourism sector - examples and market research

NASA Astrophysics Data System (ADS)

Damm, Andrea; Köberl, Judith; Prettenthaler, Franz; Kortschak, Dominik; Hofer, Marianne; Winkler, Claudia

2017-04-01

Tourism is one of the most weather-sensitive sectors. Hence, dealing with weather and climate risks is an important part of operational risk management. WEDDA® (WEather Driven Demand Analysis), developed by Joanneum Research, represents a comprehensive and flexible toolbox for managing weather and climate risks. Modelling the demand for products or services of a particular economic sector or company and its weather and climate sensitivity usually forms the starting and central point of WEDDA®. Coupling the calibrated demand models to either long-term climate scenarios or short-term weather forecasts enables the use of WEDDA® for the following areas of application: (i) implementing short-term forecasting systems for the prediction of the considered indicator; (ii) quantifying the weather risk of a particular economic sector or company using parameters from finance (e.g. Value-at-Risk); (iii) assessing the potential impacts of changing climatic conditions on a particular economic sector or company. WEDDA® for short-term forecasts on the demand for products or services is currently used by various tourism businesses, such as open-air swimming pools, ski areas, and restaurants. It supports tourism and recreation facilities to better cope with (increasing) weather variability by optimizing the disposability of staff, resources and merchandise according to expected demand. Since coping with increasing weather variability forms one of the challenges with respect to climate change, WEDDA® may become an important component within a whole pool of weather and climate services designed to support tourism and recreation facilities to adapt to climate change. Climate change impact assessments at European scale, as conducted in the EU-FP7 project IMPACT2C, provide basic information of climate change impacts on tourism demand not only for individual tourism businesses, but also for regional and national tourism planners and policy makers interested in benchmarks for the vulnerability of their tourism destination. In this project we analysed the impacts of +2 °C global warming on winter tourism demand in ski tourism related regions in Europe. In order to achieve the climate targets, tailored climate information services - for individual businesses as well as at the regional and national level - play an important role. The current market, however, is still in the early stages. In the ongoing H2020 projects EU-MACS (www.eu-macs.eu) and MARCO (www.marco-h2020.eu) (Nov 2016 - Oct 2018) Joanneum Research explores the climate services market in the tourism sector. The current use of climate services is reviewed in detail and in an interactive process key market barriers and enablers will be identified in close collaboration with stakeholders from the tourism industry. The analysis and co-development of new climate services concepts for the tourism sector aims to reduce the gaps between climate services supply and demand.

The Madden-Julian Oscillation and its Impact on Northern Hemisphere Weather Predictability during Wintertime

NASA Technical Reports Server (NTRS)

Jones, Charles; Waliser, Duane E.; Lau, K. M.; Stern, W.

2003-01-01

The Madden-Julian Oscillation (MJO) is known as the dominant mode of tropical intraseasonal variability and has an important role in the coupled-atmosphere system. This study used twin numerical model experiments to investigate the influence of the MJO activity on weather predictability in the midlatitudes of the Northern Hemisphere during boreal winter. The National Aeronautics and Space Administration (NASA) Goddard laboratory for the Atmospheres (GLA) general circulation model was first used in a 10-yr simulation with fixed climatological SSTs to generate a validation data set as well as to select initial conditions for active MJO periods and Null cases. Two perturbation numerical experiments were performed for the 75 cases selected [(4 MJO phases + Null phase) _ 15 initial conditions in each]. For each alternative initial condition, the model was integrated for 90 days. Mean anomaly correlations in the midlatitudes of the Northern Hemisphere (2O deg N_60 deg.N) and standardized root-mean-square errors were computed to validate forecasts and control run. The analyses of 500-hPa geopotential height, 200-hPa Streamfunction and 850-hPa zonal wind component systematically show larger predictability during periods of active MJO as opposed to quiescent episodes of the oscillation.

Space weather at Low Latitudes: Considerations to improve its forecasting

NASA Astrophysics Data System (ADS)

Chau, J. L.; Goncharenko, L.; Valladares, C. E.; Milla, M. A.

2013-05-01

In this work we present a summary of space weather events that are unique to low-latitude regions. Special emphasis will be devoted to events that occur during so-called quiet (magnetically) conditions. One of these events is the occurrence of nighttime F-region irregularities, also known Equatorial Spread F (ESF). When such irregularities occur navigation and communications systems get disrupted or perturbed. After more than 70 years of studies, many features of ESF irregularities (climatology, physical mechanisms, longitudinal dependence, time dependence, etc.) are well known, but so far they cannot be forecast on time scales of minutes to hours. We present a summary of some of these features and some of the efforts being conducted to contribute to their forecasting. In addition to ESF, we have recently identified a clear connection between lower atmospheric forcing and the low latitude variability, particularly during the so-called sudden stratospheric warming (SSW) events. During SSW events and magnetically quiet conditions, we have observed changes in total electron content (TEC) that are comparable to changes that occur during strong magnetically disturbed conditions. We present results from recent events as well as outline potential efforts to forecast the ionospheric effects during these events.

Climate, geography, and tree establishment in Subalpine Meadows of the Olympic Mountains, Washington, U.S.A.

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

Woodward, A.; Silsbee, D.G.; Schreiner, E.G.

1995-08-01

Noticeable changes in vegetation distribution have occurred in the Pacific Northwest during the last century as trees have established in some subalpine meadows. To study the relationship of this process to climate, recently established trees were aged in six subalpine meadows in the Olympic Mountains, Washington. The sites represent three points along a steep precipitation gradient. Subalpine fir (Abies lasiocarpa) has been establishing at the dry end of the gradient, mountain hemlock (Tsuga mertensiana) at the wet end, and both species in the center. Establishment patterns were compared with deviations from the century-long average for these weather variables: winter precipitation,more » Palmer Drought Severity Index, and winter, October and May temperatures. Results show that establishment occurred in dry areas when weather conditions were wetter than average, and in wet areas under drier than average conditions. Establishment at central sites did not show consistent relationships with climate. If future climatic conditions continue to warm, establishment of subalpine fir in subalpine meadows in dry areas may cease and mountain hemlock may resume in wet areas. 34 refs., 5 figs., 3 tabs.« less

Shifting patterns of mild weather in response to projected radiative forcing

NASA Astrophysics Data System (ADS)

van der Wiel, Karin; Kapnick, Sarah; Vecchi, Gabriel

2017-04-01

Traditionally, climate change research has focused on changes in mean climate (e.g. global mean temperature, sea level rise, glacier melt) or change in extreme events (e.g. hurricanes, extreme precipitation, droughts, heat waves, wild fires). Though extreme events have the potential to disrupt society, extreme conditions are rare by definition. In contrast, mild weather occurs frequently and many human activities are built around it. Examples of such activities include football games, dog walks, bike rides, and outdoor weddings, but also activities of direct economic impact, e.g. construction work, infrastructure projects, road or rail transportation, air travel, and landscaping projects. Absence of mild weather impacts society in various way, understanding current and future mild weather is therefore of high scientific interest. We present a global analysis of mild weather based on simple and relatable criteria and we explore changes in mild weather occurrence in response to radiative forcing. A high-resolution global climate model, GFDL HiFLOR, is used to allow for investigation of local features and changes. In response to RCP4.5, we find a slight global mean decrease in the annual number of mild days projected both in the near future (-4 d/yr, 2016-2035) and at the end of this century (-10 d/yr, 2081-2100). Projected regional and seasonal redistributions of mild days are substantially greater. Tropical regions are projected to see large decreases, in the mid-latitudes small increases in the number of mild days are projected. Mediterranean climates are projected to see a shift of mild weather away from the local summer to the shoulder seasons. These changes are larger than the interannual variability of mild weather caused by El Niño-Southern Oscillation. Finally, we use reanalysis data to show an observed global decrease in the recent past, and we verify that these observed regional changes in mild weather resemble the projections.

Estimating the fuel moisture content of indicator sticks from selected weather variables

Treesearch

Theodore G. Storey

1965-01-01

Equations were developed to predict the fuel moisture content of indicator sticks from the controlling weather variables. Moisture content of ⅛-inch thick basswood slats used in the South and East could be determined with about equal precision by equation in the critical low moisture range or by weighing at fire danger stations. The most useful equation...

Evaluating climate models: Should we use weather or climate observations?

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

Oglesby, Robert J; Erickson III, David J

2009-12-01

Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

Does vehicle color influence the risk of being passively involved in a collision?

PubMed

Lardelli-Claret, Pablo; De Dios Luna-Del-Castillo, Juan; Juan Jiménez-Moleón, José; Femia-Marzo, Pedro; Moreno-Abril, Obdulia; Bueno-Cavanillas, Aurora

2002-11-01

Bright- or light-colored vehicles are sometimes regarded as safer because they are presumably more visible. We examined the effect of vehicle color on the risk of being passively involved in a collision. This paired case-control study used data from the Spanish database of traffic crashes. We selected those collisions from 1993 to 1999 in which only one of the drivers committed an infraction. The violators constituted the control group; the other drivers formed the case group. Information about the color of the vehicle and other confounding variables was also collected. When white was compared with the remaining colors, a protective estimate was obtained (adjusted odds ratio [aOR] = 0.97; 95% confidence interval = 0.94-1.00). The results were similar for light colors (white plus yellow) compared with all remaining colors (aOR = 0.96; 0.94-0.99). The protective effect of light colors was specifically observed for open roads and under daylight conditions. It was stronger in conditions other than good weather (aOR = 0.91; 0.86-0.99) than in good weather conditions. Light colors (white and yellow) were associated with a slightly lower risk of being passively involved in a collision, although only under certain environmental conditions.

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions.

PubMed

Mosedale, Jonathan R; Wilson, Robert J; Maclean, Ilya M D

2015-01-01

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions

PubMed Central

Mosedale, Jonathan R.; Wilson, Robert J.; Maclean, Ilya M. D.

2015-01-01

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions. PMID:26496127

En Route Air Traffic Control Input Devices for the Next Generation

NASA Technical Reports Server (NTRS)

Mainini, Matthew J.

2010-01-01

The purpose of this study was to investigate the usefulness of different input device configurations when trial planning new routes for aircraft in an advanced simulation of the en route workstation. The task of trial planning is one of the futuristic tools that is performed by the graphical manipulation of an aircraft's trajectory to reroute the aircraft without voice communication. In this study with two input devices, the FAA's current trackball and a basic optical computer mouse were evaluated with "pick" button in a click-and-hold state and a click-and-release state while the participant dragged the trial plan line. The trial plan was used for three different conflict types: Aircraft Conflicts, Weather Conflicts, and Aircraft + Weather Conflicts. Speed and accuracy were the primary dependent variables. Results indicate that the mouse conditions were significantly faster than the trackball conditions overall with no significant loss of accuracy. Several performance ratings and preference ratings were analyzed from post-run and post-simulation questionnaires. The release conditions were significantly more useful and likable than the hold conditions. The results suggest that the mouse in the release button state was the fastest and most well liked device configuration for trial planning in the en route workstation. Keywords-input devices, en route, controller, workstation, mouse, trackball, NextGen

Air Quality and Meteorological Boundary Conditions during the MCMA-2003 Field Campaign

NASA Astrophysics Data System (ADS)

Sosa, G.; Arriaga, J.; Vega, E.; Magaña, V.; Caetano, E.; de Foy, B.; Molina, L. T.; Molina, M. J.; Ramos, R.; Retama, A.; Zaragoza, J.; Martínez, A. P.; Márquez, C.; Cárdenas, B.; Lamb, B.; Velasco, E.; Allwine, E.; Pressley, S.; Westberg, H.; Reyes, R.

2004-12-01

A comprehensive field campaign to characterize photochemical smog in the Mexico City Metropolitan Area (MCMA) was conducted during April 2003. An important number of equipment was deployed all around the urban core and its surroundings to measure gas and particles composition from the various sources and receptor sites. In addition to air quality measurements, meteorology variables were also taken by regular weather meteorological stations, tethered balloons, radiosondes, sodars and lidars. One important issue with regard to the field campaign was the characterization of the boundary conditions in order to feed meteorological and air quality models. Four boundary sites were selected to measure continuously criteria pollutants, VOC and meteorological variables at surface level. Vertical meteorological profiles were measured at three other sites : radiosondes in Tacubaya site were launched every six hours daily; tethered balloons were launched at CENICA and FES-Cuautitlan sites according to the weather conditions, and one sodar was deployed at UNAM site in the south of the city. Additionally to these measurements, two fixed meteorological monitoring networks deployed along the city were available to complement these measurements. In general, we observed that transport of pollutants from the city to the boundary sites changes every day, according to the coupling between synoptic and local winds. This effect were less important at elevated sites such as Cerro de la Catedral and ININ, where synoptic wind were more dominant during the field campaign. Also, local sources nearby boundary sites hide the influence of pollution coming from the city some days, particularly at the La Reforma site.

Assessing the Impact of Climatic Variability and Change on Maize Production in the Midwestern USA

NASA Astrophysics Data System (ADS)

Andresen, J.; Jain, A. K.; Niyogi, D. S.; Alagarswamy, G.; Biehl, L.; Delamater, P.; Doering, O.; Elias, A.; Elmore, R.; Gramig, B.; Hart, C.; Kellner, O.; Liu, X.; Mohankumar, E.; Prokopy, L. S.; Song, C.; Todey, D.; Widhalm, M.

2013-12-01

Weather and climate remain among the most important uncontrollable factors in agricultural production systems. In this study, three process-based crop simulation models were used to identify the impacts of climate on the production of maize in the Midwestern U.S.A. during the past century. The 12-state region is a key global production area, responsible for more than 80% of U.S. domestic and 25% of total global production. The study is a part of the Useful to Useable (U2U) Project, a USDA NIFA-sponsored project seeking to improve the resilience and profitability of farming operations in the region amid climate variability and change. Three process-based crop simulation models were used in the study: CERES-Maize (DSSAT, Hoogenboom et al., 2012), the Hybrid-Maize model (Yang et al., 2004), and the Integrated Science Assessment Model (ISAM, Song et al., 2013). Model validation was carried out with individual plot and county observations. The models were run with 4 to 50 km spatial resolution gridded weather data for representative soils and cultivars, 1981-2012, to examine spatial and temporal yield variability within the region. We also examined the influence of different crop models and spatial scales on regional scale yield estimation, as well as a yield gap analysis between observed and attainable yields. An additional study was carried out with the CERES-Maize model at 18 individual site locations 1901-2012 to examine longer term historical trends. For all simulations, all input variables were held constant in order to isolate the impacts of climate. In general, the model estimates were in good agreement with observed yields, especially in central sections of the region. Regionally, low precipitation and soil moisture stress were chief limitations to simulated crop yields. The study suggests that at least part of the observed yield increases in the region during recent decades have occurred as the result of wetter, less stressful growing season weather conditions.

Modeling the influence of preferential flow on the spatial variability and time-dependence of mineral weathering rates

DOE PAGES

Pandey, Sachin; Rajaram, Harihar

2016-12-05

Inferences of weathering rates from laboratory and field observations suggest significant scale and time-dependence. Preferential flow induced by heterogeneity (manifest as permeability variations or discrete fractures) has been suggested as one potential mechanism causing scale/time-dependence. In this paper, we present a quantitative evaluation of the influence of preferential flow on weathering rates using reactive transport modeling. Simulations were performed in discrete fracture networks (DFNs) and correlated random permeability fields (CRPFs), and compared to simulations in homogeneous permeability fields. The simulations reveal spatial variability in the weathering rate, multidimensional distribution of reactions zones, and the formation of rough weathering interfaces andmore » corestones due to preferential flow. In the homogeneous fields and CRPFs, the domain-averaged weathering rate is initially constant as long as the weathering front is contained within the domain, reflecting equilibrium-controlled behavior. The behavior in the CRPFs was influenced by macrodispersion, with more spread-out weathering profiles, an earlier departure from the initial constant rate and longer persistence of weathering. DFN simulations exhibited a sustained time-dependence resulting from the formation of diffusion-controlled weathering fronts in matrix blocks, which is consistent with the shrinking core mechanism. A significant decrease in the domain-averaged weathering rate is evident despite high remaining mineral volume fractions, but the decline does not follow a math formula dependence, characteristic of diffusion, due to network scale effects and advection-controlled behavior near the inflow boundary. Finally, the DFN simulations also reveal relatively constant horizontally averaged weathering rates over a significant depth range, challenging the very notion of a weathering front.« less

Modeling the influence of preferential flow on the spatial variability and time-dependence of mineral weathering rates

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

Pandey, Sachin; Rajaram, Harihar

Inferences of weathering rates from laboratory and field observations suggest significant scale and time-dependence. Preferential flow induced by heterogeneity (manifest as permeability variations or discrete fractures) has been suggested as one potential mechanism causing scale/time-dependence. In this paper, we present a quantitative evaluation of the influence of preferential flow on weathering rates using reactive transport modeling. Simulations were performed in discrete fracture networks (DFNs) and correlated random permeability fields (CRPFs), and compared to simulations in homogeneous permeability fields. The simulations reveal spatial variability in the weathering rate, multidimensional distribution of reactions zones, and the formation of rough weathering interfaces andmore » corestones due to preferential flow. In the homogeneous fields and CRPFs, the domain-averaged weathering rate is initially constant as long as the weathering front is contained within the domain, reflecting equilibrium-controlled behavior. The behavior in the CRPFs was influenced by macrodispersion, with more spread-out weathering profiles, an earlier departure from the initial constant rate and longer persistence of weathering. DFN simulations exhibited a sustained time-dependence resulting from the formation of diffusion-controlled weathering fronts in matrix blocks, which is consistent with the shrinking core mechanism. A significant decrease in the domain-averaged weathering rate is evident despite high remaining mineral volume fractions, but the decline does not follow a math formula dependence, characteristic of diffusion, due to network scale effects and advection-controlled behavior near the inflow boundary. Finally, the DFN simulations also reveal relatively constant horizontally averaged weathering rates over a significant depth range, challenging the very notion of a weathering front.« less

40 CFR 201.23 - Test site, weather conditions and background noise criteria for measurement at a 30 meter (100...

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 26 2013-07-01 2013-07-01 false Test site, weather conditions and background noise criteria for measurement at a 30 meter (100 feet) distance of the noise from locomotive and... TRANSPORTATION EQUIPMENT; INTERSTATE RAIL CARRIERS Measurement Criteria § 201.23 Test site, weather conditions...

40 CFR 201.23 - Test site, weather conditions and background noise criteria for measurement at a 30 meter (100...

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 25 2011-07-01 2011-07-01 false Test site, weather conditions and background noise criteria for measurement at a 30 meter (100 feet) distance of the noise from locomotive and... TRANSPORTATION EQUIPMENT; INTERSTATE RAIL CARRIERS Measurement Criteria § 201.23 Test site, weather conditions...

40 CFR 201.23 - Test site, weather conditions and background noise criteria for measurement at a 30 meter (100...

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 26 2012-07-01 2011-07-01 true Test site, weather conditions and background noise criteria for measurement at a 30 meter (100 feet) distance of the noise from locomotive and... TRANSPORTATION EQUIPMENT; INTERSTATE RAIL CARRIERS Measurement Criteria § 201.23 Test site, weather conditions...

40 CFR 201.23 - Test site, weather conditions and background noise criteria for measurement at a 30 meter (100...

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 25 2014-07-01 2014-07-01 false Test site, weather conditions and background noise criteria for measurement at a 30 meter (100 feet) distance of the noise from locomotive and... TRANSPORTATION EQUIPMENT; INTERSTATE RAIL CARRIERS Measurement Criteria § 201.23 Test site, weather conditions...

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

Treesearch

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

2015-01-01

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

Wildfire risk in the wildland-urban interface: A simulation study in northwestern Wisconsin

USGS Publications Warehouse

Bar-Massada, A.; Radeloff, V.C.; Stewart, S.I.; Hawbaker, T.J.

2009-01-01

The rapid growth of housing in and near the wildland-urban interface (WUI) increases wildfire risk to lives and structures. To reduce fire risk, it is necessary to identify WUI housing areas that are more susceptible to wildfire. This is challenging, because wildfire patterns depend on fire behavior and spread, which in turn depend on ignition locations, weather conditions, the spatial arrangement of fuels, and topography. The goal of our study was to assess wildfire risk to a 60,000 ha WUI area in northwestern Wisconsin while accounting for all of these factors. We conducted 6000 simulations with two dynamic fire models: Fire Area Simulator (FARSITE) and Minimum Travel Time (MTT) in order to map the spatial pattern of burn probabilities. Simulations were run under normal and extreme weather conditions to assess the effect of weather on fire spread, burn probability, and risk to structures. The resulting burn probability maps were intersected with maps of structure locations and land cover types. The simulations revealed clear hotspots of wildfire activity and a large range of wildfire risk to structures in the study area. As expected, the extreme weather conditions yielded higher burn probabilities over the entire landscape, as well as to different land cover classes and individual structures. Moreover, the spatial pattern of risk was significantly different between extreme and normal weather conditions. The results highlight the fact that extreme weather conditions not only produce higher fire risk than normal weather conditions, but also change the fine-scale locations of high risk areas in the landscape, which is of great importance for fire management in WUI areas. In addition, the choice of weather data may limit the potential for comparisons of risk maps for different areas and for extrapolating risk maps to future scenarios where weather conditions are unknown. Our approach to modeling wildfire risk to structures can aid fire risk reduction management activities by identifying areas with elevated wildfire risk and those most vulnerable under extreme weather conditions. ?? 2009 Elsevier B.V.

Examining the Pilot and Controller Performance Data When in a Free Flight with Weather Phenomenon

NASA Technical Reports Server (NTRS)

Nituen, Celestine A.; Lozito, Sandra C. (Technical Monitor)

2002-01-01

The present study investigated effects of weather related factors on the performance of pilots under free flight. A weather scenario was defined by a combination of precipitation factors (light rain, moderate rain, and heavy rain or snow), visibility (1,4,8 miles), wind conditions (light, medium, or heavy), cloud ceiling (800ft. below, 1800ft above, and 4000ft horizontal). The performance of the aircraft self-separation was evaluated in terms of detection accuracy and detection times for student- and commercial (expert) pilots. Overall, the results obtained from a behavioral analysis showed that in general, the ability to recognize intruder aircraft conflict incidents, followed by the ability to acquire the spatial location of the intruder aircraft relative to ownership aircraft were judged to be the major cognitive tasks as perceived by the participants during self-separation. Further, the participants rarely used cockpit display of traffic information (CDTI) during conflict management related to aircraft separation, but used CDTI highly during decision-making tasks. In all weather scenarios, there were remarkable differences between expert and student pilots in detection times. In summary, weather scenarios were observed to affect intruder aircraft detection performance accuracies. There was interaction effects between weather Scenario-1 and Scenario-2 for climbing task data generated by both expert- and student- pilots at high traffic density. Scenario-3 weather condition provided an opportunity for poor detection accuracy as well as detection time increase. This may be attributed to low visibility. The intruder aircraft detection times were not affected by the weather conditions during climbing and descending tasks. The decision of pilots to fly into certain weather condition was dependent in part on the warning distance to the location of the weather. When pilots were warned of the weather conditions, they were more likely to fly their aircraft into it, but mostly when the warning was not close to the weather location.

The Assessment of Climatological Impacts on Agricultural Production and Residential Energy Demand

NASA Astrophysics Data System (ADS)

Cooter, Ellen Jean

The assessment of climatological impacts on selected economic activities is presented as a multi-step, inter -disciplinary problem. The assessment process which is addressed explicitly in this report focuses on (1) user identification, (2) direct impact model selection, (3) methodological development, (4) product development and (5) product communication. Two user groups of major economic importance were selected for study; agriculture and gas utilities. The broad agricultural sector is further defined as U.S.A. corn production. The general category of utilities is narrowed to Oklahoma residential gas heating demand. The CERES physiological growth model was selected as the process model for corn production. The statistical analysis for corn production suggests that (1) although this is a statistically complex model, it can yield useful impact information, (2) as a result of output distributional biases, traditional statistical techniques are not adequate analytical tools, (3) the model yield distribution as a whole is probably non-Gausian, particularly in the tails and (4) there appears to be identifiable weekly patterns of forecasted yields throughout the growing season. Agricultural quantities developed include point yield impact estimates and distributional characteristics, geographic corn weather distributions, return period estimates, decision making criteria (confidence limits) and time series of indices. These products were communicated in economic terms through the use of a Bayesian decision example and an econometric model. The NBSLD energy load model was selected to represent residential gas heating consumption. A cursory statistical analysis suggests relationships among weather variables across the Oklahoma study sites. No linear trend in "technology -free" modeled energy demand or input weather variables which would correspond to that contained in observed state -level residential energy use was detected. It is suggested that this trend is largely the result of non-weather factors such as population and home usage patterns rather than regional climate change. Year-to-year changes in modeled residential heating demand on the order of 10('6) Btu's per household were determined and later related to state -level components of the Oklahoma economy. Products developed include the definition of regional forecast areas, likelihood estimates of extreme seasonal conditions and an energy/climate index. This information is communicated in economic terms through an input/output model which is used to estimate changes in Gross State Product and Household income attributable to weather variability.

Weather effects on the success of longleaf pine cone crops

Treesearch

Daniel J. Leduc; Shi-Jean Susana Sung; Dale G. Brockway; Mary Anne Sword Sayer

2016-01-01

We used National Oceanic and Atmospheric Administration weather data and historical records of cone crops from across the South to relate weather conditions to the yield of cones in 10 longleaf pine (Pinus palustris Mill.) stands. Seed development in this species occurs over a three-year time period and weather conditions during any part of this...

Exploring the future change space for fire weather in southeast Australia

NASA Astrophysics Data System (ADS)

Clarke, Hamish; Evans, Jason P.

2018-05-01

High-resolution projections of climate change impacts on fire weather conditions in southeast Australia out to 2080 are presented. Fire weather is represented by the McArthur Forest Fire Danger Index (FFDI), calculated from an objectively designed regional climate model ensemble. Changes in annual cumulative FFDI vary widely, from - 337 (- 21%) to + 657 (+ 24%) in coastal areas and - 237 (- 12%) to + 1143 (+ 26%) in inland areas. A similar spread is projected in extreme FFDI values. In coastal regions, the number of prescribed burning days is projected to change from - 11 to + 10 in autumn and - 10 to + 3 in spring. Across the ensemble, the most significant increases in fire weather and decreases in prescribed burn windows are projected to take place in spring. Partial bias correction of FFDI leads to similar projections but with a greater spread, particularly in extreme values. The partially bias-corrected FFDI performs similarly to uncorrected FFDI compared to the observed annual cumulative FFDI (ensemble root mean square error spans 540 to 1583 for uncorrected output and 695 to 1398 for corrected) but is generally worse for FFDI values above 50. This emphasizes the need to consider inter-variable relationships when bias-correcting for complex phenomena such as fire weather. There is considerable uncertainty in the future trajectory of fire weather in southeast Australia, including the potential for less prescribed burning days and substantially greater fire danger in spring. Selecting climate models on the basis of multiple criteria can lead to more informative projections and allow an explicit exploration of uncertainty.

Ground and surface water developmental toxicity at a municipal landfill--Description and weather-related variation

USGS Publications Warehouse

Bruner, M.A.; Rao, M.; Dumont, J.N.; Hull, M.; Jones, T.; Bantle, J.A.

1998-01-01

Contaminated groundwater poses a significant health hazard and may also impact wildlife such as amphibians when it surfaces. Using FETAX (Frog Embryo Teratogenesis Assay-Xenopus), the developmental toxicity of ground and surface water samples near a closed municipal landfill at Norman, OK, were evaluated. The groundwater samples were taken from a network of wells in a shallow, unconfined aquifer downgradient from the landfill. Surface water samples were obtained from a pond and small stream adjacent to the landfill. Surface water samples from a reference site in similar habitat were also analyzed. Groundwater samples were highly toxic in the area near the landfill, indicating a plume of toxicants. Surface water samples from the landfill site demonstrated elevated developmental toxicity. This toxicity was temporally variable and was significantly correlated with weather conditions during the 3 days prior to sampling. Mortality was negatively correlated with cumulative rain and relative humidity. Mortality was positively correlated with solar radiation and net radiation. No significant correlations were observed between mortality and weather parameters for days 4–7 preceding sampling.

Assimilation of Cloud Information in Numerical Weather Prediction Model in Southwest China

NASA Astrophysics Data System (ADS)

HENG, Z.

2016-12-01

Based on the ARPS Data Analysis System (ADAS), Weather Research and Forecasting (WRF) model, simulation experiments from July 1st 2015 to August 1st 2015 are conducted in the region of Southwest China. In the assimilation experiment (EXP), datasets from surface observations are assimilated, cloud information from weather Doppler radar, Fengyun-2E (FY-2E) geostationary satellite are retrieved by using the complex cloud analysis scheme in the ADAS, to insert microphysical variables and adjust the humility structure in the initial condition. As a control run (CTL), datasets from surface observations are assimilated, but no cloud information is used in the ADAS. The simulation result of a rainstorm caused by the Southwest Vortex during 14-15 July 2015 shows that, the EXP run has a better capability in representing the shape and intensity of precipitation, especially the center of rainstorm. The one-month inter-comparison of the initial and prediction results between the EXP and CTL runs reveled that, EXP runs can present a more reasonable phenomenon of rain and get a higher score in the rain prediction. Keywords: NWP, rainstorm, Data assimilation

Atmospheric Effects on Cosmic Ray Air Showers Observed with HAWC

NASA Astrophysics Data System (ADS)

Young, Steven

2014-01-01

The High Altitude Water Cherenkov Gamma Ray detector (HAWC), currently under construction on the Sierra Negra volcano near Puebla, Mexico, can be used to study solar physics with its scaler data acquisition system. Increases in the scaler rates are used to observe GeV cosmic rays from solar flares while decreases in the rates show the heliospheric disturbances associated with coronal mass ejections. However, weather conditions and height-dependent state variables such as pressure and temperature affect the production of extensive particle air showers that can be detected by the scaler system. To see if these atmospheric effects can be removed, we obtained local weather data from the Global Data Assimilation System (GDAS) and the local weather station at HAWC. The scaler pulse rates were then correlated to the pressure and temperature. We present data from a Forbush decrease observed by HAWC following a significant coronal mass ejection in April 2013, and describe our efforts to remove atmospheric variations from the scaler counts. This work was partially supported by the National Science Foundation’s REU program through NSF Award AST-1004881 to the University of Wisconsin-Madison.

Synoptic-scale fire weather conditions in Alaska

NASA Astrophysics Data System (ADS)

Hayasaka, Hiroshi; Tanaka, Hiroshi L.; Bieniek, Peter A.

2016-09-01

Recent concurrent widespread fires in Alaska are evaluated to assess their associated synoptic-scale weather conditions. Several periods of high fire activity from 2003 to 2015 were identified using Moderate Resolution Imaging Spectroradiometer (MODIS) hotspot data by considering the number of daily hotspots and their continuity. Fire weather conditions during the top six periods of high fire activity in the fire years of 2004, 2005, 2009, and 2015 were analyzed using upper level (500 hPa) and near surface level (1000 hPa) atmospheric reanalysis data. The top four fire-periods occurred under similar unique high-pressure fire weather conditions related to Rossby wave breaking (RWB). Following the ignition of wildfires, fire weather conditions related to RWB events typically result in two hotspot peaks occurring before and after high-pressure systems move from south to north across Alaska. A ridge in the Gulf of Alaska resulted in southwesterly wind during the first hotspot peak. After the high-pressure system moved north under RWB conditions, the Beaufort Sea High developed and resulted in relatively strong easterly wind in Interior Alaska and a second (largest) hotspot peak during each fire period. Low-pressure-related fire weather conditions occurring under cyclogenesis in the Arctic also resulted in high fire activity under southwesterly wind with a single large hot-spot peak.

Effects of climatic variables on weight loss: a global analysis.

PubMed

Ustulin, Morena; Keum, Changwon; Woo, Junghoon; Woo, Jeong-Taek; Rhee, Sang Youl

2017-01-20

Several studies have analyzed the effects of weather on factors associated with weight loss. In this study, we directly analyzed the effect of weather on intentional weight loss using global-scale data provided by smartphone applications. Through Weather Underground API and the Noom Coach application, we extracted information on weather and body weight for each user located in each of several geographic areas on all login days. We identified meteorological information (pressure, precipitation, wind speed, dew point, and temperature) and self-monitored body weight data simultaneously. A linear mixed-effects model was performed analyzing 3274 subjects. Subjects in North America had higher initial BMIs than those of subjects in Eastern Asia. During the study period, most subjects who used the smartphone application experienced weight loss in a significant way (80.39%, p-value < 0.001). Subjects who infrequently recorded information about dinner had smaller variations than those of other subjects (β freq.users dinner*time  = 0.007, p-value < 0.001). Colder temperature, lower dew point, and higher values for wind speed and precipitation were significantly associated with weight loss. In conclusion, we found a direct and independent impact of meteorological conditions on intentional weight loss efforts on a global scale (not only on a local level).

Weather and childbirth: a further search for relationships.

PubMed

Driscoll, D M

1995-03-01

Previous attempts to find relationships between weather and parturition (childbirth) and its onset (the beginning of labor pains) have revealed, firstly, limited but statistically significant relationships between weather conditions much colder than the day before, with high winds and low pressure, and increased onsets; and secondly, increased numbers of childbirths during periods of atmospheric pressure rise (highly statistically significant). To test these findings, this study examined weather data coincident childbirth data from a hospital at Bryan-College Station, Texas (for a period of 30 cool months from 1987 to 1992). Tests for (1) days of cold fronts, (2) a day before and a day after the cold front, (3) days with large temperature increases, and (4) decreases from the day before revealed no relationship with mean daily rate of onset. Cold days with high winds and low pressure had significantly fewer onsets, a result that is the opposite of previous findings. The postulated relationship between periods of pressure rise and increased birth frequency was negative, i.e., significantly fewer births occurred at those times--again, the opposite of the apparent occurrence in an earlier study. The coincidence of diurnal variations in both atmospheric pressure and frequency of childbirths, was shown to account for fairly strong negative associations between the two variables.(ABSTRACT TRUNCATED AT 250 WORDS)