Weather based warning systems for bean angular-leaf-spot and anthracnose

Data available in the literature were used to develop a warning system for bean angular leaf spot and anthracnose, caused by Phaeoisariopsis griseola and Colletotrichum lindemuthianum, respectively. The model is based on favorable environmental conditions for the infectious process such as continuous leaf wetness duration and mean air temperature during this subphase of the pathogen-host relationship cycle. Equations published by DALLA PRIA (1977) showing the interactions of those two factors on the disease severity were used. Excell spreadsheet was used to calculate the leaf wetness period needed to cause different infection probabilities at different temperature ranges. These data were employed to elaborate critical period tables used to program a computerized electronic device that records leaf wetness duration and mean temperature and automatically shows the daily disease severity value (DDSV) for each disease. The model should be validated in field experiments under natural infection for which the daily disease severity sum (DDSS) should be identified as a criterion to indicate the beginning and the interval of fungicide applications to control both diseases.

Weather requirements and rain forecast to time fungicide application for Fusarium head blight control in wheat

The aim of this study was to determine the minimum conditions of wetness duration and mean temperature required for Fusarium head blight infection in wheat. The weather model developed by Zoldan (2008) was tested in field experiments for two wheat cultivars grown in 2005 (five sowing dates) and 2006 (six sowing dates) in 10 m² plots with three replicates. The disease was assessed according to head incidence (HI), spikelet incidence (SI), and the interaction between these two methods was called head blight severity (HBS). Starting at the beginning of anthesis, air temperature and head wetness duration were daily recorded with an automatic weather station. With the combination of these two factors, a weather favorability table was built for the disease occurrence. Starting on the day of flowering beginning (1 - 5% fully exserted anthers), the sum of daily values for infection favorability (SDVIF) was calculated by means of a computer program, according to Zoldan (2008) table. The initial symptoms of the disease were observed at 3.7% spikelet incidence, corresponding to 2.6 SVDFI. The infection occurs in wheat due to rainfall which results in spike wetting of > 61.4 h duration. Rainfall events forecast can help time fungicide application to control FHB. The name of this alert system is proposed as UPF-scab alert.

Forecasting financial weather - can we foresee market sentiment? Spectrum of stock price behavior - NYSE case study

The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.

A time series analysis of meteorological factors and hospital outpatient admissions for cardiovascular disease in the Northern district of Guizhou Province, China

Findings on the effects of weather on health, especially the effects of ambient temperature on overall morbidity, remain inconsistent. We conducted a time series study to examine the acute effects of meteorological factors (mainly air temperature) on daily hospital outpatient admissions for cardiovascular disease (CVD) in Zunyi City, China, from January 1, 2007 to November 30, 2009. We used the generalized additive model with penalized splines to analyze hospital outpatient admissions, climatic parameters, and covariate data. Results show that, in Zunyi, air temperature was associated with hospital outpatient admission for CVD. When air temperature was less than 10°C, hospital outpatient admissions for CVD increased 1.07-fold with each increase of 1°C, and when air temperature was more than 10°C, an increase in air temperature by 1°C was associated with a 0.99-fold decrease in hospital outpatient admissions for CVD over the previous year. Our analyses provided statistically significant evidence that in China meteorological factors have adverse effects on the health of the general population. Further research with consistent methodology is needed to clarify the magnitude of these effects and to show which populations and individuals are vulnerable.

Simulation of crop yields using ERA-40: Limits to skill and nonstationarity in weather-yield relationships

Reanalysis data provide an excellent test bed for impacts prediction systems. because they represent an upper limit on the skill of climate models. Indian groundnut (Arachis hypogaea L.) yields have been simulated using the General Large-Area Model (GLAM) for annual crops and the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40). The ability of ERA-40 to represent the Indian summer monsoon has been examined. The ability of GLAM. when driven with daily ERA-40 data, to model both observed yields and observed relationships between subseasonal weather and yield has been assessed. Mean yields "were simulated well across much of India. Correlations between observed and modeled yields, where these are significant. are comparable to correlations between observed yields and ERA-40 rainfall. Uncertainties due to the input planting window, crop duration, and weather data have been examined. A reduction in the root-mean-square error of simulated yields was achieved by applying bias correction techniques to the precipitation. The stability of the relationship between weather and yield over time has been examined. Weather-yield correlations vary on decadal time scales. and this has direct implications for the accuracy of yield simulations. Analysis of the skewness of both detrended yields and precipitation suggest that nonclimatic factors are partly responsible for this nonstationarity. Evidence from other studies, including data on cereal and pulse yields, indicates that this result is not particular to groundnut yield. The detection and modeling of nonstationary weather-yield relationships emerges from this study as an important part of the process of understanding and predicting the impacts of climate variability and change on crop yields.

From short-range barotropic modelling to extended-range global weather prediction: a 40-year perspective

At the end of the 20th century, we can look back on a spectacular development of numerical weather prediction, which has, practically uninterrupted, been going on since the middle of the century. High-resolution predictions for more than a week ahead for any part of the globe are now routinely produced and anyone with an Internet connection can access many of these forecasts for anywhere in the world. Extended predictions for several seasons ahead are also being done — the latest El Niño event in 1997/1998 is an example of such a successful prediction. The great achievement is due to a number of factors including the progress in computational technology and the establishment of global observing systems, combined with a systematic research program with an overall strategy towards building comprehensive prediction systems for climate and weather. In this article, I will discuss the different evolutionary steps in this development and the way new scientific ideas have contributed to efficiently explore the computing power and in using observations from new types of observing systems. Weather prediction is not an exact science due to unavoidable errors in initial data and in the models. To quantify the reliability of a forecast is therefore essential and probably more so the longer the forecasts are. Ensemble prediction is thus a new and important concept in weather and climate prediction, which I believe will become a routine aspect of weather prediction in the future. The limit between weather and climate prediction is becoming more and more diffuse and in the final part of this article I will outline the way I think development may proceed in the future.

Synoptic-scale controls of persistent low temperature and icy weather over southern China in January 2008

In January 2008, central and southern China experienced persistent low temperatures, freezing rain, and snow. The large-scale conditions associated with the occurrence and development of these snowstorms are examined in order to identify the key synoptic controls leading to this event. Three main factors are identified: 1) the persistent blocking high over Siberia, which remained quasi-stationary around 65°E for 3 weeks, led to advection of dry and cold Siberian air down to central and southern China; 2) a strong persistent southwesterly flow associated with the western Pacific subtropical high led to enhanced moisture advection from the Bay of Bengal into central and southern China; and 3) the deep inversion layer in the lower troposphere associated with the extended snow cover over most of central and southern China. The combination of these three factors is likely responsible for the unusual severity of the event, and hence a long return period

Are there risk factors in alpine skiing? A controlled multicentre survey of 1278 skiers

OBJECTIVE: To analyse risk factors in alpine skiing. DESIGN: A controlled multicentre survey of injured and non-injured alpine skiers. SETTING: One tertiary and two secondary trauma centres in Bern, Switzerland. PATIENTS AND METHODS: All injured skiers admitted from November 2007 to April 2008 were analysed using a completed questionnaire incorporating 15 parameters. The same questionnaire was distributed to non-injured controls. Multiple logistic regression was performed. Patterns of combined risk factors were calculated by inference trees. A total of 782 patients and 496 controls were interviewed. RESULTS: Parameters that were significant for the patients were: high readiness for risk (p = 0.0365, OR 1.84, 95% CI 1.04 to 3.27); low readiness for speed (p = 0.0008, OR 0.29, 95% CI 0.14 to 0.60); no aggressive behaviour on slopes (p<0.0001, OR 0.19, 95% CI 0.09 to 0.37); new skiing equipment (p = 0.0228, OR 59, 95% CI 0.37 to 0.93); warm-up performed (p = 0.0015, OR 1.79, 95% CI 1.25 to 2.57); old snow compared with fresh snow (p = 0.0155, OR 0.31, 95% CI 0.12 to 0.80); old snow compared with artificial snow (p = 0.0037, OR 0.21, 95% CI 0.07 to 0.60); powder snow compared with slushy snow (p = 0.0035, OR 0.25, 95% CI 0.10 to 0.63); drug consumption (p = 0.0044, OR 5.92, 95% CI 1.74 to 20.11); and alcohol abstinence (p<0.0001, OR 0.14, 95% CI 0.05 to 0.34). Three groups at risk were detected: (1) warm-up 3-12 min, visual analogue scale (VAS)(speed) >4 and bad weather/visibility; (2) VAS(speed) 4-7, icy slopes and not wearing a helmet; (3) warm-up >12 min and new skiing equipment. CONCLUSIONS: Low speed, high readiness for risk, new skiing equipment, old and powder snow, and drug consumption are significant risk factors when skiing. Future work should aim to identify more precisely specific groups at risk and develop recommendations--for example, a snow weather index at valley stations.

Weather and War – Economic and social vulnerability in Switzerland at the end of the First World War

Neutral Switzerland – not embedded in the fighting forces – yet was involved in the Great War mainly in economical terms. Since Switzerland is a landlocked country especially agriculture became an important topic of war economy in regard to food security. Until 1916 national food supply was limited but could be maintained through barter trade. In 1916 a crisis on both supply and production level occurred and led to a decline in food availability and to immense price risings causing social turmoil. This paper aims to outline the factors of vulnerability in respect of food in Switzerland during the First World War and further it will show different coping strategies that were undertaken during that time. The paper takes the work of Mario Aeby and Christian Pfister (University of Bern) into consideration that pointed out to weather anomalies during the years 1916 and 1917 aggravating the already tense food situation. Arguing for an overlap of supply and production crisis the paper focuses on agricultural and economic history including environmental impacts. Further the paper addresses the question of what makes a food system resilient to such unforeseen impacts.

Environmental and behavioral risk factors for moderate or severe rotavirus diarrhea in children less than 24 months

On a global basis rotaviruses are the most important agents involved in childhood diarrhea. In developing countries they account for 6% of all diarrheas and 20% of all diarrhea related deaths of children under 5 years of age, with over 1 billion episodes and over 4 million deaths annually. Given the disease burden, there is a need for better understanding the risk factors involved in rotavirus disease, to identify areas of intervention. In order to provide this information, two areas were developed: a review of the literature, examining the causal evidence for rotavirus diarrhea and a case comparison study. The case comparison study analyzed two areas: identifying climate factors and, identifying environmental and behavioral risk factors. The literature review showed that few analytical studies have identified specific risk factors such as home environment, and a winter seasonal trend for temperate areas, but in key areas evidence is contradictory. The case comparison study for climate factors demonstrated that seasonality occurs in a tropical country like Venezuela and that a complex interplay between weather conditions contribute to the seasonal pattern. A positive association between rain fall (OR 4.1); dew point (OR 2.3) and temperature differential during the day (OR 1.4) and, an inverse association with temperature (OR 0.5) and relative humidity (OR 0.8) was found. This information is useful in understanding the seasonal pattern of rotavirus and for planning health care needs. The second analysis demonstrated that environmental variables such as crowding (OR 14.3), contact with someone with an infectious disease (OR 4.9) and animal ownership (OR 2.3) were important. Restricting the analysis to animal owners demonstrated that living In a rural settling (OR 13.8), defecating in inappropriate places (OR 7.2), crowding(4.2) and indoor animals (4.0) are of importance. Behavioral variables identified were: lack of breast feeding (OR 4.0) and visiting when someone was sick (OR 3.4). Biological and demographic variables of importance were: age, with a dose response relationship; undernurishment (OR 11.3) and household per capita monthly income less than US $ 16.30 (OR 8.5). Using a diarrhea compeer group we found that, although some of the previous variables were of importance, no major differences were found. These findings are important in identifying paths for prevention and further research. ^

The interurban DRAG-Spain model: the main factors of influence on road accidents in Spain

This paper presents the results of applying DRAG methodology to the identification of the main factors of influence on the number of injury and fatal accidents occurring on Spain’s interurban network. Nineteen independent variables have been included in the model grouped together under ten categories: exposure, infrastructure, weather, drivers, economic variables, vehicle stock, surveillance, speed and legislative measures. Highly interesting conclusions can be reached from the results on the basis of the different effects of a single variable on each of the accident types according to severity. The greatest influence revealed by the results is exposure, which together with inexperienced drivers, speed and an ageing vehicle stock, have a negative effect, while the increased surveillance on roads, the improvement in the technological features of vehicles and the proportion of high capacity networks have a positive effect, since the results obtained show a significant drop in accidents.

The Relationship of Built Environment and Weather with Bike Share –Evidence from the Pronto Bike Share System in Seattle

Thesis (Master's)--University of Washington, 2016-06