KSC-06pd1283

NASA Image and Video Library

2006-06-28

KENNEDY SPACE CENTER, FLA. - A Rawinsonde weather balloon sails into the sky after release from the Cape Canaveral forecast facility in Florida. The release was planned as part of a media tour prior to the launch of Space Shuttle Discovery on mission STS-121 July 1. Rawinsonde balloons are GPS-tracked and can collect such data as atmospheric pressure, temperature, humidity and wind speed and direction up to 100,000 feet. At the facility, which is operated by the U.S. Air Force 45th Weather Squadron, media saw the tools used by the weather team to create the forecast for launch day. They received a briefing on how the launch weather forecast is developed by Shuttle Weather Officer Kathy Winters and met the forecasters for the space shuttle and the expendable launch vehicles. Also participating were members of the Applied Meteorology Unit who provide special expertise to the forecasters by analyzing and interpreting unusual or inconsistent weather data. The media were able to see the release of the Rawinsonde weather balloon carrying instruments aloft to be used as part of developing the forecast. Photo credit: NASA/George Shelton

KSC-06pd1281

NASA Image and Video Library

2006-06-28

KENNEDY SPACE CENTER, FLA. - At the Cape Canaveral forecast facility in Florida, a worker carries a Rawinsonde weather balloon outside for release. Rawinsonde balloons are GPS-tracked and can collect such data as atmospheric pressure, temperature, humidity and wind speed and direction up to 100,000 feet. The release was planned as part of a media tour prior to the launch of Space Shuttle Discovery on mission STS-121 July 1. At the facility, which is operated by the U.S. Air Force 45th Weather Squadron, media saw the tools used by the weather team to create the forecast for launch day. They received a briefing on how the launch weather forecast is developed by Shuttle Weather Officer Kathy Winters and met the forecasters for the space shuttle and the expendable launch vehicles. Also participating were members of the Applied Meteorology Unit who provide special expertise to the forecasters by analyzing and interpreting unusual or inconsistent weather data. The media were able to see the release of the Rawinsonde weather balloon carrying instruments aloft to be used as part of developing the forecast. Photo credit: NASA/George Shelton

KSC-06pd1282

NASA Image and Video Library

2006-06-28

KENNEDY SPACE CENTER, FLA. - At the Cape Canaveral forecast facility in Florida, a worker releases a Rawinsonde weather balloon outside for release. Rawinsonde balloons are GPS-tracked and can collect such data as atmospheric pressure, temperature, humidity and wind speed and direction up to 100,000 feet. The release was planned as part of a media tour prior to the launch of Space Shuttle Discovery on mission STS-121 July 1. At the facility, which is operated by the U.S. Air Force 45th Weather Squadron, media saw the tools used by the weather team to create the forecast for launch day. They received a briefing on how the launch weather forecast is developed by Shuttle Weather Officer Kathy Winters and met the forecasters for the space shuttle and the expendable launch vehicles. Also participating were members of the Applied Meteorology Unit who provide special expertise to the forecasters by analyzing and interpreting unusual or inconsistent weather data. The media were able to see the release of the Rawinsonde weather balloon carrying instruments aloft to be used as part of developing the forecast. Photo credit: NASA/George Shelton

Understanding causality and uncertainty in volcanic observations: An example of forecasting eruptive activity on Soufrière Hills Volcano, Montserrat

NASA Astrophysics Data System (ADS)

Sheldrake, T. E.; Aspinall, W. P.; Odbert, H. M.; Wadge, G.; Sparks, R. S. J.

2017-07-01

Following a cessation in eruptive activity it is important to understand how a volcano will behave in the future and when it may next erupt. Such an assessment can be based on the volcano's long-term pattern of behaviour and insights into its current state via monitoring observations. We present a Bayesian network that integrates these two strands of evidence to forecast future eruptive scenarios using expert elicitation. The Bayesian approach provides a framework to quantify the magmatic causes in terms of volcanic effects (i.e., eruption and unrest). In October 2013, an expert elicitation was performed to populate a Bayesian network designed to help forecast future eruptive (in-)activity at Soufrière Hills Volcano. The Bayesian network was devised to assess the state of the shallow magmatic system, as a means to forecast the future eruptive activity in the context of the long-term behaviour at similar dome-building volcanoes. The findings highlight coherence amongst experts when interpreting the current behaviour of the volcano, but reveal considerable ambiguity when relating this to longer patterns of volcanism at dome-building volcanoes, as a class. By asking questions in terms of magmatic causes, the Bayesian approach highlights the importance of using short-term unrest indicators from monitoring data as evidence in long-term forecasts at volcanoes. Furthermore, it highlights potential biases in the judgements of volcanologists and identifies sources of uncertainty in terms of magmatic causes rather than scenario-based outcomes.

Time Series Forecasting of the Number of Malaysia Airlines and AirAsia Passengers

NASA Astrophysics Data System (ADS)

Asrah, N. M.; Nor, M. E.; Rahim, S. N. A.; Leng, W. K.

2018-04-01

The standard practice in forecasting process involved by fitting a model and further analysis on the residuals. If we know the distributional behaviour of the time series data, it can help us to directly analyse the model identification, parameter estimation, and model checking. In this paper, we want to compare the distributional behaviour data from the number of Malaysia Airlines (MAS) and AirAsia passenger’s. From the previous research, the AirAsia passengers are govern by geometric Brownian motion (GBM). The data were normally distributed, stationary and independent. Then, GBM was used to forecast the number of AirAsia passenger’s. The same methods were applied to MAS data and the results then were compared. Unfortunately, the MAS data were not govern by GBM. Then, the standard approach in time series forecasting will be applied to MAS data. From this comparison, we can conclude that the number of AirAsia passengers are always in peak season rather than MAS passengers.

Diagnostic studies of ensemble forecast "jumps"

NASA Astrophysics Data System (ADS)

Magnusson, Linus; Hewson, Tim; Ferranti, Laura; Rodwell, Mark

2016-04-01

During 2015 we saw exceptional consistency in successive seasonal forecasts produced at ECMWF, for the winter period 2015/16, right across the globe. This winter was characterised by a well-predicted and unusually strong El Nino, and some have ascribed the consistency to that. For most of December this consistency was mirrored in the (separate) ECMWF monthly forecast system, which correctly predicted anomalously strong (mild) zonal flow, over the North Atlantic and western Eurasia, even in forecasts for weeks 3 and 4. In monthly forecasts in general these weeks are often devoid of strong signals. However in late December and early January strong signals, even in week 2, proved to be incorrect, most notably over the North Atlantic and Eurasian sectors. Indeed on at least two occasions the outcome was beyond the ensemble forecast range over Scandinavia. In one of these conditions flipped from extreme mild to extreme cold as a high latitude block developed. Temperature prediction is very important to many customers, notably those dealing with renewable energy, because cold weather causes increased demand but also tends to coincide with reduced wind power production. So understandably jumps can cause consternation amongst some customer groups, and are very difficult to handle operationally. This presentation will discuss the results of initial diagnostic investigations into what caused the "ensemble jumps", particularly at the week two lead, though reference will also be made to a related shorter range (day 3) jump that was important for flooding over the UK. Initial results suggest that an inability of the ECMWF model to correctly represent convective outbreaks over North America (that for winter-time were quite extreme) played an important role. Significantly, during this period, an unusually large amount of upper air data over North America was rejected or ascribed low weight. These results bear similarities to previous diagnostic studies at ECMWF, wherein major convective outbreaks in spring and early summer over North America were shown to have a detrimental impact on forecast quality. The possible contributions of other factors will also be discussed; for example we know that the ECMWF model exhibits different skill levels for different regime transitions. It will also be shown that the new higher resolution ECMWF forecast system, then running in trial mode, performed somewhat better, at least for some of these cases.

Mitigating randomness of consumer preferences under certain conditional choices

NASA Astrophysics Data System (ADS)

Bothos, John M. A.; Thanos, Konstantinos-Georgios; Papadopoulou, Eirini; Daveas, Stelios; Thomopoulos, Stelios C. A.

2017-05-01

Agent-based crowd behaviour consists a significant field of research that has drawn a lot of attention in recent years. Agent-based crowd simulation techniques have been used excessively to forecast the behaviour of larger or smaller crowds in terms of certain given conditions influenced by specific cognition models and behavioural rules and norms, imposed from the beginning. Our research employs conditional event algebra, statistical methodology and agent-based crowd simulation techniques in developing a behavioural econometric model about the selection of certain economic behaviour by a consumer that faces a spectre of potential choices when moving and acting in a multiplex mall. More specifically we try to analyse the influence of demographic, economic, social and cultural factors on the economic behaviour of a certain individual and then we try to link its behaviour with the general behaviour of the crowds of consumers in multiplex malls using agent-based crowd simulation techniques. We then run our model using Generalized Least Squares and Maximum Likelihood methods to come up with the most probable forecast estimations, regarding the agent's behaviour. Our model is indicative about the formation of consumers' spectre of choices in multiplex malls under the condition of predefined preferences and can be used as a guide for further research in this area.

Using Haines Index coupled with fire weather model predicted from high resolution LAM forecasts to asses wildfire extreme behaviour in Southern Europe.

NASA Astrophysics Data System (ADS)

Gaetani, Francesco; Baptiste Filippi, Jean; Simeoni, Albert; D'Andrea, Mirko

2010-05-01

Haines Index (HI) was developed by USDA Forest Service to measure the atmosphere's contribution to the growth potential of a wildfire. The Haines Index combines two atmospheric factors that are known to have an effect on wildfires: Stability and Dryness. As operational tools, HI proved its ability to predict plume dominated high intensity wildfires. However, since HI does not take into account the fuel continuity, composition and moisture conditions and the effects of wind and topography on fire behaviour, its use as forecasting tool should be carefully considered. In this work we propose the use of HI, predicted from HR Limited Area Model forecasts, coupled with a Fire Weather model (i.e., RISICO system) fully operational in Italy since 2003. RISICO is based on dynamic models able to represent in space and in time the effects that environment and vegetal physiology have on fuels and, in turn, on the potential behaviour of wildfires. The system automatically acquires from remote databases a thorough data-set of input information both of in situ and spatial nature. Meteorological observations, radar data, Limited Area Model weather forecasts, EO data, and fuel data are managed by a Unified Interface able to process a wide set of different data. Specific semi-physical models are used in the system to simulate the dynamics of the fuels (load and moisture contents of dead and live fuel) and the potential fire behaviour (rate of spread and linear intensity). A preliminary validation of this approach will be provided with reference to Sardinia and Corsica Islands, two major islands of the Mediterranean See frequently affected by extreme plume dominated wildfires. A time series of about 3000 wildfires burnt in Sardinia and Corsica in 2007 and 2008 will be used to evaluate the capability of HI coupled with the outputs of the Fire Weather model to forecast the actual risk in time and in space.

KSC-06pd1279

NASA Image and Video Library

2006-06-28

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

Behavioural Phenotype in Borjeson-Forssman-Lehmann Syndrome

ERIC Educational Resources Information Center

de Winter, C. F.; van Dijk, F.; Stolker, J. J.; Hennekam, R. C. M.

2009-01-01

Background: Borjeson-Forssman-Lehmann syndrome (BFLs) is an X-linked inherited disorder characterised by unusual facial features, abnormal fat distribution and intellectual disability. As many genetically determined disorders are characterised not only by physical features but also by specific behaviour, we studied whether a specific behavioural…

Using modified fruit fly optimisation algorithm to perform the function test and case studies

NASA Astrophysics Data System (ADS)

Pan, Wen-Tsao

2013-06-01

Evolutionary computation is a computing mode established by practically simulating natural evolutionary processes based on the concept of Darwinian Theory, and it is a common research method. The main contribution of this paper was to reinforce the function of searching for the optimised solution using the fruit fly optimization algorithm (FOA), in order to avoid the acquisition of local extremum solutions. The evolutionary computation has grown to include the concepts of animal foraging behaviour and group behaviour. This study discussed three common evolutionary computation methods and compared them with the modified fruit fly optimization algorithm (MFOA). It further investigated the ability of the three mathematical functions in computing extreme values, as well as the algorithm execution speed and the forecast ability of the forecasting model built using the optimised general regression neural network (GRNN) parameters. The findings indicated that there was no obvious difference between particle swarm optimization and the MFOA in regards to the ability to compute extreme values; however, they were both better than the artificial fish swarm algorithm and FOA. In addition, the MFOA performed better than the particle swarm optimization in regards to the algorithm execution speed, and the forecast ability of the forecasting model built using the MFOA's GRNN parameters was better than that of the other three forecasting models.

Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

NASA Astrophysics Data System (ADS)

MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

2015-04-01

The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

Beyond Behaviour: Is Social Anxiety Low in Williams Syndrome?

ERIC Educational Resources Information Center

Dodd, Helen F.; Schniering, Carolyn A.; Porter, Melanie A.

2009-01-01

Individuals with Williams syndrome (WS) exhibit striking social behaviour that may be indicative of abnormally low social anxiety. The present research aimed to determine whether social anxiety is unusually low in WS and to replicate previous findings of increased generalised anxiety in WS using both parent and self report. Fifteen individuals…

Water intake and risk of hyponatraemia in Prader-Willi syndrome.

PubMed

Akefeldt, A

2009-06-01

Unusual water intake and drinking behaviour has occasionally been observed in individuals with Prader-Willi syndrome (PWS). The aim of this study is to explore whether this observation is a part of the PWS phenotype and what the consequences may be. The parents of 51 individuals with PWS (age range 2-40 years) were asked by questionnaire to answer on past and present water intake, drinking behaviour, fluid preferences and medical treatment in their PWS-affected and unaffected children. Questionnaires with information on 47 PWS individuals and 17 without PWS were returned for analysis. The questionnaire information was complemented with information from the individual's medical records. Siblings to PWS individuals made up the control group. The study was approved by the regional medical research ethics committee. During infancy, 36 (76%) individuals with PWS disliked water without any flavouring and had an extremely small daily intake of water. Seven individuals (15%) increased the daily water intake to unusually high amounts. In 45 the clinical PWS diagnosis was confirmed by molecular (genetic) testing: nine of them with a confirmed PWS diagnosis had a deletion of chromosome 15q11-13, in nine individuals no deletion was identified. The majority of individuals who increased their water consumption to extreme values belonged to the non-deletion group. Two in the non-deletion group developed hyponatraemia while receiving psychiatric medication. Infants with PWS seem to be predisposed to unusual drinking behaviour. They dislike and have an unusually small intake of pure water without flavouring, and most of them continue this even after infancy. Some individuals, especially those without deletion, increase their fluid intake and also accept pure water. They have an increased risk of developing water retention and severe hyponatraemia if exposed to medication known to cause side effects like the syndrome of inappropriate antidiuretic hormone secretion. Perhaps this behaviour is just secondary to overeating; perhaps it is a result of a dysfunction of the hypothalamic nuclei engaged in antidiuretic hormone production.

Understanding the Unusual 2017 Monsoon and Floods in South Asia

NASA Astrophysics Data System (ADS)

Akanda, A. S.; Palash, W.; Hasan, M. A.; Nusrat, F.

2017-12-01

Driven primarily by the South Asian Monsoon, the Ganges-Brahmaputra-Meghna (GBM) river basin system collectively drains intense precipitation for an area of more than 1.5 million square kilometers during the wet summer season. Bangladesh, being the lowest riparian country in the system, experiences recurrent floods and immense suffering to its population. The 2017 monsoon season was quite unusual in terms of the characteristics of the precipitation received in the basin. The monsoon was spread out over a much larger time span (April-October) compared to the average monsoon season (June-September). Although the monsoon does not typically start until June in Bangladesh, the 2017 season started much earlier in April with unusually heavy precipitation in the Meghna basin region and caused major damage to agriculture in northeastern Bangladesh. The rainfall continued in several record-breaking pulses, compared to the typical one or two large waves. One of the largest pulses occurred in early August with very high in intensity and volume, causing ECMWF to issue a major warning about widespread flooding in Bangladesh, Northern India, and Eastern Nepal. This record flood event impacted over 40 million people in the above regions, causing major damage to life and infrastructure. Although the Brahmaputra rose above the danger level several times this season, the Ganges was unusually low, thus sparing downstream areas from disastrous floods. However, heavy precipitation continued until October, causing urban flooding in Dhaka and Chittagong - and worsening sanitation and public health conditions in southern Bangladesh - currently undergoing a terrible humanitarian crisis involving Rohingya refugees from the Myanmar. Despite marked improvement in flood forecasting systems in recent years, the 2017 floods identified critical gaps in our understanding of the flooding phenomena and limitations of dissemination in these regions. In this study, we investigate 1) the unusual characteristics of the 2017 season, 2) the nature of the floods in northern areas and the Teesta basin region, 3) the performance of rainfall and flood forecasts, 4) the stark difference in Ganges and Brahmaputra basin rainfall, and 5) corresponding relations to known teleconnections such as ENSO and other climate phenomena.

Extreme precipitation event over North China in August 2010: observations, monthly forecasting, and link to intra-seasonal variability of the Silk-Road wave-train across Eurasia

NASA Astrophysics Data System (ADS)

Orsolini, Yvan; Zhang, Ling; Peters, Dieter; Fraedrich, Klaus

2014-05-01

Forecast of regional precipitation events at the sub-seasonal timescale remains a big challenge for operational global prediction systems. Over the Far East in summer, climate and precipitation are strongly influenced by the fluctuating western Pacific subtropical high (WPSH) and strong precipitation is often associated with southeasterly low-level wind that brings moist-laden air from the southern China seas. The WPSH variability is partly influenced by quasi-stationary wave-trains propagating eastwards from Europe across Asia along the two westerly jets: the Silk-Road wave-train along the Asian jet at mid-latitudes and, on a more northern route, the polar wave-train along the sub-polar jet. While the Silk-Road wave-train appears as a robust, internal mode of variability in seasonal predictions models, its predictability is very low on the sub-seasonal to seasonal time scale. A case in point is the unusual summer of 2010, when China experienced its worst seasonal flooding for a decade, triggered by unusually prolonged and severe monsoonal rains. In addition that summer was also characterized by record-breaking heat wave over Eastern Europe and Russia as well as catastrophic monsoonal floods in Pakistan 2010. The impact of the latter circulation anomalies on the precipitation further east over China, has been little explored. Here, we examine the role and the actual predictability of the Silk-Road wave-train, and its impact on precipitation over Northeastern China throughout August 2010, using the high-resolution IFS forecast model of ECMWF, realistic initialized and run in an ensemble mode. We demonstrate that the forecast failure with regard to flooding and extreme precipitation over Northeastern China in August 2010 is linked to the failure to represent intra-seasonal variations of the Silk-Road wave-train and the associated intensification of the WPSH.

Challenging official health cost estimates: an alternative view that incorporates the behavioural and economic effects of policy changes.

PubMed

Robbins, A; Robbins, G

1992-01-01

Cost estimates of health care policy changes are extremely important. Historically, however, the US government has done a poor job in projecting the actual cost of new health care programmes. These projections have been inaccurate primarily because government forecasters use 'static' methods that fail to incorporate the change in people's behaviour as a direct result of a new policy. In contrast, 'dynamic' forecasts incorporate the behavioural effects of policy changes on individuals and the economy. Static and dynamic estimates can lead to different results for 4 areas of US health policy: (a) the Medicare Catastrophic Coverage Act; (b) mandated health benefits; (c) health insurance tax subsidies; and (d) national health insurance. Improving health care policy requires the adoption of dynamic estimation practices, periodic appraisals evaluating the accuracy of official estimates in relation to actual experience, and clear presentation of proposed policy changes and estimates to policymakers and the general public.

Multi-body coalescence in Pickering emulsions

NASA Astrophysics Data System (ADS)

Wu, Tong; Wang, Haitao; Jing, Benxin; Liu, Fang; Burns, Peter C.; Na, Chongzheng

2015-01-01

Particle-stabilized Pickering emulsions have shown unusual behaviours such as the formation of non-spherical droplets and the sudden halt of coalescence between individual droplets. Here we report another unusual behaviour of Pickering emulsions—the simultaneous coalescence of multiple droplets in a single event. Using latex particles, silica particles and carbon nanotubes as model stabilizers, we show that multi-body coalescence can occur in both water-in-oil and oil-in-water emulsions. The number of droplets involved in the nth coalscence event equals four times the corresponding number of the tetrahedral sequence in close packing. Furthermore, coalescence is promoted by repulsive latex and silica particles but inhibited by attractive carbon nanotubes. The revelation of multi-body coalescence is expected to help better understand Pickering emulsions in natural systems and improve their designs in engineering applications.

Validation of the Ford Score as a Measure for Predicting the Level of Emotional and Behavioural Problems in Mainstream Schools

ERIC Educational Resources Information Center

Goodman, Anna; Ford, Tamsin

2008-01-01

Emotional and behavioural difficulties (EBD) are common in children, and forecasting their prevalence in schools is of interest to both academic researchers and local authorities. Percentage of pupils eligible for free school meals is one measure often used for this purpose. The article presents the first independent validation of a simple…

Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

NASA Astrophysics Data System (ADS)

Turner, Sean W. D.; Bennett, James C.; Robertson, David E.; Galelli, Stefano

2017-09-01

Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made - namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

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

Turner, Sean W. D.; Bennett, James C.; Robertson, David E.

Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strongmore » relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.« less

Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

DOE PAGES

Turner, Sean W. D.; Bennett, James C.; Robertson, David E.; ...

2017-09-28

Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strongmore » relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.« less

Using time series structural characteristics to analyze grain prices in food insecure countries

USGS Publications Warehouse

Davenport, Frank; Funk, Chris

2015-01-01

Two components of food security monitoring are accurate forecasts of local grain prices and the ability to identify unusual price behavior. We evaluated a method that can both facilitate forecasts of cross-country grain price data and identify dissimilarities in price behavior across multiple markets. This method, characteristic based clustering (CBC), identifies similarities in multiple time series based on structural characteristics in the data. Here, we conducted a simulation experiment to determine if CBC can be used to improve the accuracy of maize price forecasts. We then compared forecast accuracies among clustered and non-clustered price series over a rolling time horizon. We found that the accuracy of forecasts on clusters of time series were equal to or worse than forecasts based on individual time series. However, in the following experiment we found that CBC was still useful for price analysis. We used the clusters to explore the similarity of price behavior among Kenyan maize markets. We found that price behavior in the isolated markets of Mandera and Marsabit has become increasingly dissimilar from markets in other Kenyan cities, and that these dissimilarities could not be explained solely by geographic distance. The structural isolation of Mandera and Marsabit that we find in this paper is supported by field studies on food security and market integration in Kenya. Our results suggest that a market with a unique price series (as measured by structural characteristics that differ from neighboring markets) may lack market integration and food security.

Curiosity and exploratory behaviour towards possible and impossible events in children and adults.

PubMed

Subbotsky, Eugene

2010-08-01

In four experiments with 4-, 6-, and 9-year-old children and adults, the hypothesis was tested that, all other conditions being equal, a novel and unusual event elicits stronger curiosity and exploratory behaviour if its suggested explanation involves an element of the supernatural than if it does not (the impossible over possible effect - the I/P effect). Participants were shown an unusual phenomenon (a spontaneous disintegration of a physical object in an apparently empty box) framed in the context of either a magical (the impossible event) or scientific (the possible event) explanation. In the verbal trial, participants showed a clear understanding of the difference between the effect of genuine magic and the effect of a trick. In the behavioural trial, both children and adults showed the I/P effect. They were more likely to run the risk of losing their valuable objects in order to explore the impossible event than the possible event. Follow-up experiments showed that the I/P effect couldn't be explained as an artifact of the different degrees of cost of exploratory behaviour in the possible and impossible conditions or as a result of misinterpreting magic as tricks. The I/P effect emerged when the cost of exploratory behaviour was moderate and disappeared when the cost was perceived as too high or too low.

Experimental observation and simulation of unusual microwave response for the superconducting microstrip resonator at small dc magnetic field

NASA Astrophysics Data System (ADS)

Ong, C. K.; Rao, X. S.; Jin, B. B.

1999-11-01

An unusual microwave response of the surface impedance Zs of high-Tc thin films at an applied small dc magnetic field (Bdc) at 77 K, namely a decrease of Zs, is observed with the microstrip resonator technique. The resonant frequency is 1.107 GHz. The direction of Bdc is parallel or perpendicular to the a-b plane. Bdc ranges from 0 to 200 G. It is found that the surface resistance (Rs) at Bdc parallel to the a-b plane first decreases with Bdc and then increases above a crossover field. The Rs behaviour for Bdc perpendicular to the a-b plane is the same but with a different crossover field. The two behaviours can be collapsed to one curve by scaling the crossover fields. The changes of surface reactance Xs correlated linearly with the changes of Rs in the ranges of Bdc. The ratios rH of changes of Rs and Xs (rH = icons/Journals/Common/Delta" ALT="Delta" ALIGN="TOP"/> Rs/icons/Journals/Common/Delta" ALT="Delta" ALIGN="TOP"/> Xs) are 0.5 at Bdc less than the crossover field and 0.1 at Bdc greater than the crossover field. The measurements also show that the crossover field is independent of rf input power. A phenomenological model is also proposed to explain this unusual behaviour. By adjusting fitting parameters the computed results agree with the experimental results qualitatively.

New product forecasting with limited or no data

NASA Astrophysics Data System (ADS)

Ismai, Zuhaimy; Abu, Noratikah; Sufahani, Suliadi

2016-10-01

In the real world, forecasts would always be based on historical data with the assumption that the behaviour be the same for the future. But how do we forecast when there is no such data available? New product or new technologies normally has limited amount of data available. Knowing that forecasting is valuable for decision making, this paper presents forecasting of new product or new technologies using aggregate diffusion models and modified Bass Model. A newly launched Proton car and its penetration was chosen to demonstrate the possibility of forecasting sales demand where there is limited or no data available. The model was developed to forecast diffusion of new vehicle or an innovation in the Malaysian society. It is to represent the level of spread on the new vehicle among a given set of the society in terms of a simple mathematical function that elapsed since the introduction of the new product. This model will forecast the car sales volume. A procedure of the proposed diffusion model was designed and the parameters were estimated. Results obtained by applying the proposed diffusion model and numerical calculation shows that the model is robust and effective for forecasting demand of the new vehicle. The results reveal that newly developed modified Bass diffusion of demand function has significantly contributed for forecasting the diffusion of new Proton car or new product.

How often should general practitioners provide nutrition care to patients? A forecasting activity to determine the target frequency for chronic-disease management in Australia.

PubMed

Ball, Lauren; Lee, Patricia; Ambrosini, Gina L; Hamilton, Kyra; Tuffaha, Haitham

2016-11-01

Supporting patients to have healthy dietary behaviours contributes significantly to preventing and managing lifestyle-related chronic diseases. 'Nutrition care' refers to any practice provided by a health professional to support a patient to improve their dietary behaviours and subsequent health outcomes. Approximately 3% of consultations by Australian general practitioners (GPs) involve the provision of nutrition care. The aim of the present paper was to forecast the potential implications of a higher frequency of nutrition care by GPs. Evidence on the effect of improved dietary behaviours on chronic disease outcomes, number of Australian adults estimated to have poor dietary behaviours and effectiveness of GPs providing nutrition care were taken into consideration. Using hypertension as a case example, for GPs to provide nutrition care to all hypertensive adults who would benefit from improved dietary behaviours, GPs would need to provide nutrition care in a target rate of 4.85% of consultations or 4.5 million different patients each year. The target aligns with the existing priorities for supporting chronic-disease prevention and management in Australia by increasing the rate that brief lifestyle interventions are provided by primary health professionals. This conservative target presents a considerable challenge for GPs, support staff, researchers and policy makers, but can be used to inform future interventions to support nutrition care by GPs.

Forecasting giant, catastrophic slope collapse: lessons from Vajont, Northern Italy

NASA Astrophysics Data System (ADS)

Kilburn, Christopher R. J.; Petley, David N.

2003-08-01

Rapid, giant landslides, or sturzstroms, are among the most powerful natural hazards on Earth. They have minimum volumes of ˜10 6-10 7 m 3 and, normally preceded by prolonged intervals of accelerating creep, are produced by catastrophic and deep-seated slope collapse (loads ˜1-10 MPa). Conventional analyses attribute rapid collapse to unusual mechanisms, such as the vaporization of ground water during sliding. Here, catastrophic collapse is related to self-accelerating rock fracture, common in crustal rocks at loads ˜1-10 MPa and readily catalysed by circulating fluids. Fracturing produces an abrupt drop in resisting stress. Measured stress drops in crustal rock account for minimum sturzstrom volumes and rapid collapse accelerations. Fracturing also provides a physical basis for quantitatively forecasting catastrophic slope failure.

Satellite altimetry and the intensification of Hurricane Katrina

NASA Astrophysics Data System (ADS)

Scharroo, Remko; Smith, Walter H. F.; Lillibridge, John L.

Remotely sensed infrared images of Hurricane Katrina taken on 26, 27, and 28 August 2005 (Figure 1, left panels) show the aerial extent of the cloud cover and the central “eye” increasing as the storm that swamped areas of the U.S. Gulf Coast intensified. Computer animations of such image sequences show forecasters the tracks of storms and are a familiar staple of weather news. Less well known is the role that satellite altimetry plays both in forecasting conditions that can intensify a tropical storm and in observing the storm conditions at the sea surface.Satellite altimeter data indicate that Katrina intensified over areas of anomalously high dynamic topography rather than areas of unusually warm surface waters. Altimeter data from Katrina also for the first time observed the building of a storm surge.

Deliberate exotic magnetism via frustration and topology

NASA Astrophysics Data System (ADS)

Nisoli, Cristiano; Kapaklis, Vassilios; Schiffer, Peter

2017-03-01

Introduced originally to mimic the unusual, frustrated behaviour of spin ice pyrochlores, artificial spin ice can be realized in odd, dedicated geometries that open the door to new manifestations of a higher level of frustration.

Massive Solar Storms Inflict Little Damage on Earth

NASA Astrophysics Data System (ADS)

Simpson, Sarah

2003-11-01

The face of the Sun had been peaceful and blemish-free for much of 2003. But space weather forecasters knew trouble was brewing on 24 October when Jupiter-sized sunspot 486 rotated into full view. Combined with two other unusually large spots, number 486 would kick up the most intense solar activity in 30 years according to several NOAA and NASA officials who were interviewed during the accompanying flurry of media coverage.

Wind power forecasting for a real onshore wind farm on complex terrain using WRF high resolution simulations.

NASA Astrophysics Data System (ADS)

Ángel Prósper Fernández, Miguel; Casal, Carlos Otero; Canoura Fernández, Felipe; Miguez-Macho, Gonzalo

2017-04-01

Regional meteorological models are becoming a generalized tool for forecasting wind resource, due to their capacity to simulate local flow dynamics impacting wind farm production. This study focuses on the production forecast and validation of a real onshore wind farm using high horizontal and vertical resolution WRF (Weather Research and Forecasting) model simulations. The wind farm is located in Galicia, in the northwest of Spain, in a complex terrain region with high wind resource. Utilizing the Fitch scheme, specific for wind farms, a period of one year is simulated with a daily operational forecasting set-up. Power and wind predictions are obtained and compared with real data provided by the management company. Results show that WRF is able to yield good wind power operational predictions for this kind of wind farms, due to a good representation of the planetary boundary layer behaviour of the region and the good performance of the Fitch scheme under these conditions.

Observation of unusual topological surface states in half-Heusler compounds LnPtBi (Ln=Lu, Y)

DOE PAGES

Liu, Z. K.; Yang, L. X.; Wu, S. -C.; ...

2016-09-27

Topological quantum materials represent a new class of matter with both exotic physical phenomena and novel application potentials. Many Heusler compounds, which exhibit rich emergent properties such as unusual magnetism, superconductivity and heavy fermion behaviour, have been predicted to host non-trivial topological electronic structures. The coexistence of topological order and other unusual properties makes Heusler materials ideal platform to search for new topological quantum phases (such as quantum anomalous Hall insulator and topological superconductor). By carrying out angle-resolved photoemission spectroscopy and ab initio calculations on rare-earth half-Heusler compounds LnPtBi (Ln=Lu, Y), we directly observe the unusual topological surface states onmore » these materials, establishing them as first members with non-trivial topological electronic structure in this class of materials. Moreover, as LnPtBi compounds are non-centrosymmetric superconductors, our discovery further highlights them as promising candidates of topological superconductors.« less

Observation of unusual topological surface states in half-Heusler compounds LnPtBi (Ln=Lu, Y)

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

Liu, Z. K.; Yang, L. X.; Wu, S. -C.

Topological quantum materials represent a new class of matter with both exotic physical phenomena and novel application potentials. Many Heusler compounds, which exhibit rich emergent properties such as unusual magnetism, superconductivity and heavy fermion behaviour, have been predicted to host non-trivial topological electronic structures. The coexistence of topological order and other unusual properties makes Heusler materials ideal platform to search for new topological quantum phases (such as quantum anomalous Hall insulator and topological superconductor). By carrying out angle-resolved photoemission spectroscopy and ab initio calculations on rare-earth half-Heusler compounds LnPtBi (Ln=Lu, Y), we directly observe the unusual topological surface states onmore » these materials, establishing them as first members with non-trivial topological electronic structure in this class of materials. Moreover, as LnPtBi compounds are non-centrosymmetric superconductors, our discovery further highlights them as promising candidates of topological superconductors.« less

Spatial forecasting of disease risk and uncertainty

USGS Publications Warehouse

De Cola, L.

2002-01-01

Because maps typically represent the value of a single variable over 2-dimensional space, cartographers must simplify the display of multiscale complexity, temporal dynamics, and underlying uncertainty. A choropleth disease risk map based on data for polygonal regions might depict incidence (cases per 100,000 people) within each polygon for a year but ignore the uncertainty that results from finer-scale variation, generalization, misreporting, small numbers, and future unknowns. In response to such limitations, this paper reports on the bivariate mapping of data "quantity" and "quality" of Lyme disease forecasts for states of the United States. Historical state data for 1990-2000 are used in an autoregressive model to forecast 2001-2010 disease incidence and a probability index of confidence, each of which is then kriged to provide two spatial grids representing continuous values over the nation. A single bivariate map is produced from the combination of the incidence grid (using a blue-to-red hue spectrum), and a probabilistic confidence grid (used to control the saturation of the hue at each grid cell). The resultant maps are easily interpretable, and the approach may be applied to such problems as detecting unusual disease occurences, visualizing past and future incidence, and assembling a consistent regional disease atlas showing patterns of forecasted risks in light of probabilistic confidence.

Low-frequency seismic events in a wider volcanological context

NASA Astrophysics Data System (ADS)

Neuberg, J. W.; Collombet, M.

2006-12-01

Low-frequency seismic events have been in the centre of attention for several years, particularly on volcanoes with highly viscous magmas. The ultimate aim is to detect changes in volcanic activity by identifying changes in the seismic behaviour in order to forecast an eruption, or in case of an ongoing eruption, forecast the short and longterm behaviour of the volcanic system. A major boost in recent years arose through several attempts of multi-parameter volcanic monitoring and modelling programs, which allowed multi-disciplinary groups of volcanologists to interpret seismic signals together with, e.g. ground deformation, stress field analysis and petrological information. This talk will give several examples of such multi-disciplinary projects, focussing on the joint modelling of seismic source processes for low-frequency events together with advanced magma flow models, and the signs of magma movement in the deformation and stress field at the surface.

Seasonal forecasting for water resource management: the example of CNR Genissiat dam on the Rhone River in France

NASA Astrophysics Data System (ADS)

Dommanget, Etienne; Bellier, Joseph; Ben Daoud, Aurélien; Graff, Benjamin

2014-05-01

Compagnie Nationale du Rhône (CNR) has been granted the concession to operate the Rhone River from the Swiss border to the Mediterranean Sea since 1933 and carries out three interdependent missions: navigation, irrigation and hydropower production. Nowadays, CNR generates one quarter of France's hydropower electricity. The convergence of public and private interests around optimizing the management of water resources throughout the French Rhone valley led CNR to develop hydrological models dedicated to discharge seasonal forecasting. Indeed, seasonal forecasting is a major issue for CNR and water resource management, in order to optimize long-term investments of the produced electricity, plan dam maintenance operations and anticipate low water period. Seasonal forecasting models have been developed on the Genissiat dam. With an installed capacity of 420MW, Genissiat dam is the first of the 19 CNR's hydropower plants. Discharge forecasting at Genissiat dam is strategic since its inflows contributes to 20% of the total Rhone average discharge and consequently to 40% of the total Rhone hydropower production. Forecasts are based on hydrological statistical models. Discharge on the main Rhone River tributaries upstream Genissiat dam are forecasted from 1 to 6 months ahead thanks to multiple linear regressions. Inputs data of these regressions are identified depending on river hydrological regimes and periods of the year. For the melting season, from spring to summer, snow water equivalent (SWE) data are of major importance. SWE data are calculated from Crocus model (Météo France) and SLF's model (Switzerland). CNR hydro-meteorological forecasters assessed meteorological trends regarding precipitations for the next coming months. These trends are used to generate stochastically precipitation scenarios in order to complement regression data set. This probabilistic approach build a decision-making supports for CNR's water resource management team and provides them with seasonal forecasts and their confidence interval. After a presentation of CNR methodology, results for the years 2011 and 2013 will illustrate CNR's seasonal forecasting models ability. These years are of particular interest regarding water resource management seeing that they are, respectively, unusually dry and snowy. Model performances will be assessed in comparison with historical climatology thanks to CRPS skill score.

Spatio-temporal behaviour of medium-range ensemble forecasts

NASA Astrophysics Data System (ADS)

Kipling, Zak; Primo, Cristina; Charlton-Perez, Andrew

2010-05-01

Using the recently-developed mean-variance of logarithms (MVL) diagram, together with the TIGGE archive of medium-range ensemble forecasts from nine different centres, we present an analysis of the spatio-temporal dynamics of their perturbations, and show how the differences between models and perturbation techniques can explain the shape of their characteristic MVL curves. We also consider the use of the MVL diagram to compare the growth of perturbations within the ensemble with the growth of the forecast error, showing that there is a much closer correspondence for some models than others. We conclude by looking at how the MVL technique might assist in selecting models for inclusion in a multi-model ensemble, and suggest an experiment to test its potential in this context.

Modelling and measuring the irrational behaviour of agents in financial markets: Discovering the psychological soliton

NASA Astrophysics Data System (ADS)

Dhesi, Gurjeet; Ausloos, Marcel

2016-07-01

Following a Geometrical Brownian Motion extension into an Irrational Fractional Brownian Motion model, we re-examine agent behaviour reacting to time dependent news on the log-returns thereby modifying a financial market evolution. We specifically discuss the role of financial news or economic information positive or negative feedback of such irrational (or contrarian) agents upon the price evolution. We observe a kink-like effect reminiscent of soliton behaviour, suggesting how analysts' forecasts errors induce stock prices to adjust accordingly, thereby proposing a measure of the irrational force in a market.

Applications systems verification and transfer project. Volume 3: Operational applications of satellite snow cover observations in California

NASA Technical Reports Server (NTRS)

Brown, A. J.; Hannaford, J. F.

1981-01-01

Five southern Sierra snowmelt basins and two northern Sierra-Southern Cascade snowmelt basins were used to evaluate the effect on operational water supply forecasting from satellite imagery. Manual photointerpretation techniques were used to obtain SCA and equivalent snow line for the years 1973 to 1979 for the seven test basins using LANDSAT imagery and GOES imagery. The use of SCA was tested operationally in 1977-79. Results indicate the addition of SCA improve the water supply forecasts during the snowmelt phase for these basins where there may be an unusual distribution of snowpack throughout the basin, or where there is a limited amount of real time data available. A high correlation to runoff was obtained when SCA was combined with snow water content data obtained from reporting snow sensors.

Multiple "buy buttons" in the brain: Forecasting chocolate sales at point-of-sale based on functional brain activation using fMRI.

PubMed

Kühn, Simone; Strelow, Enrique; Gallinat, Jürgen

2016-08-01

We set out to forecast consumer behaviour in a supermarket based on functional magnetic resonance imaging (fMRI). Data was collected while participants viewed six chocolate bar communications and product pictures before and after each communication. Then self-reports liking judgement were collected. fMRI data was extracted from a priori selected brain regions: nucleus accumbens, medial orbitofrontal cortex, amygdala, hippocampus, inferior frontal gyrus, dorsomedial prefrontal cortex assumed to contribute positively and dorsolateral prefrontal cortex and insula were hypothesized to contribute negatively to sales. The resulting values were rank ordered. After our fMRI-based forecast an instore test was conducted in a supermarket on n=63.617 shoppers. Changes in sales were best forecasted by fMRI signal during communication viewing, second best by a comparison of brain signal during product viewing before and after communication and least by explicit liking judgements. The results demonstrate the feasibility of applying neuroimaging methods in a relatively small sample to correctly forecast sales changes at point-of-sale. Copyright © 2016. Published by Elsevier Inc.

Multifractality and value-at-risk forecasting of exchange rates

NASA Astrophysics Data System (ADS)

Batten, Jonathan A.; Kinateder, Harald; Wagner, Niklas

2014-05-01

This paper addresses market risk prediction for high frequency foreign exchange rates under nonlinear risk scaling behaviour. We use a modified version of the multifractal model of asset returns (MMAR) where trading time is represented by the series of volume ticks. Our dataset consists of 138,418 5-min round-the-clock observations of EUR/USD spot quotes and trading ticks during the period January 5, 2006 to December 31, 2007. Considering fat-tails, long-range dependence as well as scale inconsistency with the MMAR, we derive out-of-sample value-at-risk (VaR) forecasts and compare our approach to historical simulation as well as a benchmark GARCH(1,1) location-scale VaR model. Our findings underline that the multifractal properties in EUR/USD returns in fact have notable risk management implications. The MMAR approach is a parsimonious model which produces admissible VaR forecasts at the 12-h forecast horizon. For the daily horizon, the MMAR outperforms both alternatives based on conditional as well as unconditional coverage statistics.

Volcano Deformation and Eruption Forecasting using Data Assimilation: Building the Strategy

NASA Astrophysics Data System (ADS)

Bato, M. G.; Pinel, V.; Yan, Y.

2016-12-01

In monitoring active volcanoes, the magma overpressure is one of the key parameters used in forecasting volcanic eruptions. This can be inferred from the ground displacements measured on the Earth's surface by applying inversion techniques. However, during the inversion, we lose the temporal characteristic along with huge amount of information about the behaviour of the volcano. Our work focuses on developing a strategy in order to better forecast the magma overpressure using data assimilation. Data assimilation is a sequential time-forward process that best combines models and observations, sometimes a priori information based on error statistics, to predict the state of a dynamical system. It has gained popularity in various fields of geoscience (e.g. ocean-weather forecasting, geomagnetism and natural resources exploration), but remains a new and emerging technique in the field of volcanology. With the increasing amount of geodetic data (i.e. InSAR and GPS) recorded on volcanoes nowadays, and the wide-range availability of dynamical models that can provide better understanding about the volcano plumbing system; developing a forecasting framework that can efficiently combine them is crucial. Here, we particularly built our strategy on the basis of the Ensemble Kalman Filter (EnKF) [1]. We predict the temporal behaviours of the magma overpressures and surface deformations by adopting the two-magma chamber model proposed by Reverso et. al., 2014 [2] and by using synthetic GPS and/or InSAR data. Several tests are performed in order to answer the following: 1) know the efficiency of EnKF in forecasting volcanic unrests, 2) constrain unknown parameters of the model, 3) properly use GPS and/or InSAR during assimilation and 4) compare EnKF with classic inversion while using the same dynamical model. Results show that EnKF works well with the synthetic cases and there is a great potential in utilising the method for real-time monitoring of volcanic unrests. [1] Evensen, G., The Ensemble Kalman Filter: theoretical formulation and practical implementation. Ocean Dyn.,53, 343-367, 2003 [2] T. Reverso, J. Vandemeulebrouck, F. Jouanne, V. Pinel, T. Villemin, E. Sturkell, A two-magma chamber as a source of deformation at Grimsvötn volcano, Iceland, JGR, 2014

Developing a Simulated-Person Methodology Workshop: An Experiential Education Initiative for Educators and Simulators

ERIC Educational Resources Information Center

Peisachovich, Eva Hava; Nelles, L. J.; Johnson, Samantha; Nicholson, Laura; Gal, Raya; Kerr, Barbara; Celia, Popovic; Epstein, Iris; Da Silva, Celina

2017-01-01

Numerous forecasts suggest that professional-competence development depends on human encounters. Interaction between organizations, tasks, and individual providers influence human behaviour, affect organizations' or systems' performance, and are a key component of professional-competence development. Further, insufficient or ineffective…

Quantitative approaches to energy and glucose homeostasis: machine learning and modelling for precision understanding and prediction

PubMed Central

Murphy, Kevin G.; Jones, Nick S.

2018-01-01

Obesity is a major global public health problem. Understanding how energy homeostasis is regulated, and can become dysregulated, is crucial for developing new treatments for obesity. Detailed recording of individual behaviour and new imaging modalities offer the prospect of medically relevant models of energy homeostasis that are both understandable and individually predictive. The profusion of data from these sources has led to an interest in applying machine learning techniques to gain insight from these large, relatively unstructured datasets. We review both physiological models and machine learning results across a diverse range of applications in energy homeostasis, and highlight how modelling and machine learning can work together to improve predictive ability. We collect quantitative details in a comprehensive mathematical supplement. We also discuss the prospects of forecasting homeostatic behaviour and stress the importance of characterizing stochasticity within and between individuals in order to provide practical, tailored forecasts and guidance to combat the spread of obesity. PMID:29367240

A new transiently chaotic flow with ellipsoid equilibria

NASA Astrophysics Data System (ADS)

Panahi, Shirin; Aram, Zainab; Jafari, Sajad; Pham, Viet-Thanh; Volos, Christos; Rajagopal, Karthikeyan

2018-03-01

In this article, a simple autonomous transiently chaotic flow with cubic nonlinearities is proposed. This system represents some unusual features such as having a surface of equilibria. We shall describe some dynamical properties and behaviours of this system in terms of eigenvalue structures, bifurcation diagrams, time series, and phase portraits. Various behaviours of this system such as periodic and transiently chaotic dynamics can be shown by setting special parameters in proper values. Our system belongs to a newly introduced category of transiently chaotic systems: systems with hidden attractors. Transiently chaotic behaviour of our proposed system has been implemented and tested by the OrCAD-PSpise software. We have found a proper qualitative similarity between circuit and simulation results.

The Virtual Quake earthquake simulator: a simulation-based forecast of the El Mayor-Cucapah region and evidence of predictability in simulated earthquake sequences

NASA Astrophysics Data System (ADS)

Yoder, Mark R.; Schultz, Kasey W.; Heien, Eric M.; Rundle, John B.; Turcotte, Donald L.; Parker, Jay W.; Donnellan, Andrea

2015-12-01

In this manuscript, we introduce a framework for developing earthquake forecasts using Virtual Quake (VQ), the generalized successor to the perhaps better known Virtual California (VC) earthquake simulator. We discuss the basic merits and mechanics of the simulator, and we present several statistics of interest for earthquake forecasting. We also show that, though the system as a whole (in aggregate) behaves quite randomly, (simulated) earthquake sequences limited to specific fault sections exhibit measurable predictability in the form of increasing seismicity precursory to large m > 7 earthquakes. In order to quantify this, we develop an alert-based forecasting metric, and show that it exhibits significant information gain compared to random forecasts. We also discuss the long-standing question of activation versus quiescent type earthquake triggering. We show that VQ exhibits both behaviours separately for independent fault sections; some fault sections exhibit activation type triggering, while others are better characterized by quiescent type triggering. We discuss these aspects of VQ specifically with respect to faults in the Salton Basin and near the El Mayor-Cucapah region in southern California, USA and northern Baja California Norte, Mexico.

Avoidance responses of minke whales to 1-4kHz naval sonar.

PubMed

Kvadsheim, Petter H; DeRuiter, Stacy; Sivle, Lise D; Goldbogen, Jeremy; Roland-Hansen, Rune; Miller, Patrick J O; Lam, Frans-Peter A; Calambokidis, John; Friedlaender, Ari; Visser, Fleur; Tyack, Peter L; Kleivane, Lars; Southall, Brandon

2017-08-15

Minke whales are difficult to study and little information exists regarding their responses to anthropogenic sound. This study pools data from behavioural response studies off California and Norway. Data are derived from four tagged animals, of which one from each location was exposed to naval sonar signals. Statistical analyses were conducted using Mahalanobis distance to compare overall changes in parameters summarising dive behaviour, avoidance behaviour, and potential energetic costs of disturbance. Our quantitative analysis showed that both animals initiated avoidance behaviour, but responses were not associated with unusual dive behaviour. In one exposed animal the avoidance of the sonar source included a 5-fold increase in horizontal speed away from the source, implying a significant increase in metabolic rate. Despite the different environmental settings and exposure contexts, clear changes in behaviour were observed providing the first insights into the nature of responses to human noise for this wide-ranging species. Copyright © 2017. Published by Elsevier Ltd.

Detection of Ionospheric Alfven Resonator Signatures in the Equatorial Ionosphere

NASA Technical Reports Server (NTRS)

Simoes, Fernando; Klenzing, Jeffrey; Ivanov, Stoyan; Pfaff, Robert; Freudenreich, Henry; Bilitza, Dieter; Rowland, Douglas; Bromund, Kenneth; Liebrecht, Maria Carmen; Martin, Steven;

Climate, not conflict, explains extreme Middle East dust storm

DOE PAGES

Parolari, Anthony J.; Li, Dan; Bou-Zeid, Elie; ...

2016-11-08

The recent dust storm in the Middle East (Sepember 2015) was publicized in the media as a sign of an impending 'Dust Bowl.' Its severity, demonstrated by extreme aerosol optical depth in the atmosphere in the 99th percentile compared to historical data, was attributed to the ongoing regional conflict. However, surface meteorological and remote sensing data, as well as regional climate model simulations, support an alternative hypothesis: the historically unprecedented aridity played a more prominent role, as evidenced by unusual climatic and meteorological conditions prior to and during the storm. Remotely sensed normalized difference vegetation index demonstrates that vegetation covermore » was high in 2015 relative to the prior drought and conflict periods, suggesting that agricultural activity was not diminished during that year, thus negating the media narrative. Instead, meteorological simulations using the Weather Research and Forecasting (WRF) model show that the storm was associated with a cyclone and 'Shamal' winds, typical for dust storm generation in this region, that were immediately followed by an unusual wind reversal at low levels that spread dust west to the Mediterranean Coast. These unusual meteorological conditions were aided by a significant reduction in the critical shear stress due to extreme dry and hot conditions, thereby enhancing dust availability for erosion during this storm. Concluding, unusual aridity, combined with unique synoptic weather patterns, enhanced dust emission and westward long-range transport across the region, thus generating the extreme storm.« less

Climate, not conflict, explains extreme Middle East dust storm

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

Parolari, Anthony J.; Li, Dan; Bou-Zeid, Elie

The recent dust storm in the Middle East (Sepember 2015) was publicized in the media as a sign of an impending 'Dust Bowl.' Its severity, demonstrated by extreme aerosol optical depth in the atmosphere in the 99th percentile compared to historical data, was attributed to the ongoing regional conflict. However, surface meteorological and remote sensing data, as well as regional climate model simulations, support an alternative hypothesis: the historically unprecedented aridity played a more prominent role, as evidenced by unusual climatic and meteorological conditions prior to and during the storm. Remotely sensed normalized difference vegetation index demonstrates that vegetation covermore » was high in 2015 relative to the prior drought and conflict periods, suggesting that agricultural activity was not diminished during that year, thus negating the media narrative. Instead, meteorological simulations using the Weather Research and Forecasting (WRF) model show that the storm was associated with a cyclone and 'Shamal' winds, typical for dust storm generation in this region, that were immediately followed by an unusual wind reversal at low levels that spread dust west to the Mediterranean Coast. These unusual meteorological conditions were aided by a significant reduction in the critical shear stress due to extreme dry and hot conditions, thereby enhancing dust availability for erosion during this storm. Concluding, unusual aridity, combined with unique synoptic weather patterns, enhanced dust emission and westward long-range transport across the region, thus generating the extreme storm.« less

Impact of the quasi-biennial oscillation on predictability of the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Marshall, Andrew G.; Hendon, Harry H.; Son, Seok-Woo; Lim, Yuna

2017-08-01

The Madden-Julian oscillation (MJO) during boreal winter is observed to be stronger during the easterly phase of the quasi-biennial oscillation (QBO) than during the westerly phase, with the QBO zonal wind at 50 hPa leading enhanced MJO activity by about 1 month. Using 30 years of retrospective forecasts from the POAMA coupled model forecast system, we show that this strengthened MJO activity during the easterly QBO phase translates to improved prediction of the MJO and its convective anomalies across the tropical Indo-Pacific region by about 8 days lead time relative to that during westerly QBO phases. These improvements in forecast skill result not just from the fact that forecasts initialized with stronger MJO events, such as occurs during QBO easterly phases, have greater skill, but also from the more persistent behaviour of the MJO for a similar initial amplitude during QBO easterly phases as compared to QBO westerly phases. The QBO is thus an untapped source of subseasonal predictability that can provide a window of opportunity for improved prediction of global climate.

Unusual solvatochromic absorbance probe behaviour within mixtures of poly(ethylene glycol)-400 + ionic liquid, [bmim][Tf2N

NASA Astrophysics Data System (ADS)

Ali, Anwar; Ali, Maroof; Malik, Nisar Ahmad; Uzair, Sahar

2014-03-01

The potentially green solvents made up of ionic liquids (ILs) and poly(ethylene glycols) may have wide range of the applications in many chemical and biochemical fields. In the present work, solvatochromic absorbance probe behaviour is used to assess the physicochemical properties of the mixtures composed of PEG-400 + IL, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, [bmim][Tf2N]. Lowest energy intramolecular charge-transfer absorbance maxima of a betaine dye, i.e., ETN , indicates the dipolarity/polarizability and/or hydrogen-bond donating (HBD) acidity of the [bmim][Tf2N] + PEG-400 mixtures to be even higher than that of neat [bmim][Tf2N], the solution component with higher dipolarity/polarizability and/or HBD acidity. Dipolarity/polarizability (π∗) obtained separately from the electronic absorbance response of probe N,N-diethyl-4-nitroaniline, and the HBD acidity (α) of PEG-400 + [bmim][Tf2N] mixtures are also observed to be anomalously high. A comparative study of the PEG + IL mixtures has also been done with PEG-400 + molecular organic solvents (protic polar [methanol], aprotic polar [N,N-dimethylformamide], and non polar, [benzene]) mixtures, but these mixtures do not show this type of unusual behaviour. A four-parameter simplified combined nearly ideal binary solvent/Redlich-Kister (CNIBS/R-K) equation is shown to satisfactorily predict the solvatochromic parameters within PEG-400 + different solvent mixtures.

Behavioural phenotypes of the mucopolysaccharide disorders: a systematic literature review of cognitive, motor, social, linguistic and behavioural presentation in the MPS disorders.

PubMed

Cross, E M; Hare, D J

2013-03-01

The mucopolysaccharide disorders (MPS) are a group of recessively inherited metabolic disorders resulting in progressive physical and cognitive decline. MEDLINE, PsycINFO and Embase databases were searched, alongside manual screening, to identify relevant literature. Papers were included in the review if they were published in a peer reviewed journal and conducted empirical research into cognitive, motor, social or linguistic development or behaviour in one or more MPS disorders. Twenty-five papers were reviewed. Two papers used methodology of a sufficiently high standard to demonstrate a behavioural phenotype; both found sleep disturbance to be part of the phenotype of MPS III. Fearfulness and sleep disturbance were frequently observed in people with MPS I and II. Cognitive and motor impairment and decline, and challenging behaviour were highly prevalent in the severe form of MPS II. Cognitive decline and severe behavioural problems relating to aggression, hyperactivity, orality, unusual affect and temper tantrums were seen in MPS III. Sleep disturbance is part of the behavioural phenotype of MPS III, and challenging behaviour is highly prevalent in MPS II and MPS III, therefore the efficacy of behavioural interventions for these populations should be investigated. Further research into the behaviour and adaptive skills of children with MPS III and MPS IV is required.

On the Influence of North Pacific Sea Surface Temperature on the Arctic Winter Climate

NASA Technical Reports Server (NTRS)

Hurwitz, Margaret M.; Newman, P. A.; Garfinkel, C. I.

2012-01-01

Differences between two ensembles of Goddard Earth Observing System Chemistry-Climate Model simulations isolate the impact of North Pacific sea surface temperatures (SSTs) on the Arctic winter climate. One ensemble of extended winter season forecasts is forced by unusually high SSTs in the North Pacific, while in the second ensemble SSTs in the North Pacific are unusually low. High Low differences are consistent with a weakened Western Pacific atmospheric teleconnection pattern, and in particular, a weakening of the Aleutian low. This relative change in tropospheric circulation inhibits planetary wave propagation into the stratosphere, in turn reducing polar stratospheric temperature in mid- and late winter. The number of winters with sudden stratospheric warmings is approximately tripled in the Low ensemble as compared with the High ensemble. Enhanced North Pacific SSTs, and thus a more stable and persistent Arctic vortex, lead to a relative decrease in lower stratospheric ozone in late winter, affecting the April clear-sky UV index at Northern Hemisphere mid-latitudes.

Short-term volcano-tectonic earthquake forecasts based on a moving mean recurrence time algorithm: the El Hierro seismo-volcanic crisis experience

NASA Astrophysics Data System (ADS)

García, Alicia; De la Cruz-Reyna, Servando; Marrero, José M.; Ortiz, Ramón

2016-05-01

Under certain conditions, volcano-tectonic (VT) earthquakes may pose significant hazards to people living in or near active volcanic regions, especially on volcanic islands; however, hazard arising from VT activity caused by localized volcanic sources is rarely addressed in the literature. The evolution of VT earthquakes resulting from a magmatic intrusion shows some orderly behaviour that may allow the occurrence and magnitude of major events to be forecast. Thus governmental decision makers can be supplied with warnings of the increased probability of larger-magnitude earthquakes on the short-term timescale. We present here a methodology for forecasting the occurrence of large-magnitude VT events during volcanic crises; it is based on a mean recurrence time (MRT) algorithm that translates the Gutenberg-Richter distribution parameter fluctuations into time windows of increased probability of a major VT earthquake. The MRT forecasting algorithm was developed after observing a repetitive pattern in the seismic swarm episodes occurring between July and November 2011 at El Hierro (Canary Islands). From then on, this methodology has been applied to the consecutive seismic crises registered at El Hierro, achieving a high success rate in the real-time forecasting, within 10-day time windows, of volcano-tectonic earthquakes.

Effect of changes in milking routine on milking related behaviour and milk removal in Tunisian dairy dromedary camels.

PubMed

Atigui, Moufida; Marnet, Pierre-Guy; Ayeb, Naziha; Khorchani, Touhami; Hammadi, Mohamed

2014-11-01

We studied the effects of changes in the milking routine (lack or presence of 30-s prestimulation, 0 or 1, 2 or 4-min delay between preparation and cluster attachment) and environmental perturbation (unusual loud sounds capable of frightening animals just after stall entry or during the course of milking) on milk removal and milking-related behaviour in dairy dromedary camels. A 30-s prestimulation decreased incidence of bimodal milk flow curves and increased occurrence of the best milk ejection patterns with higher milk flow but had limited effect on milk production in our well-trained animals within a good machine milking setting. However, unusual sounds heard from the beginning of milking or even after milk ejection caused inhibition or disruption of milk removal and modification of camels' behaviour. Milk ejection was significantly delayed (1·58±0·17 min), residual milk increased over 40% of total milk yield and average and peak milk flow rates were significantly lowered when unusual noises were heard from the beginning of milking. These environmental perturbations increased signs of vigilance and the number of attempts to escape the milking parlour. Delaying cluster attachment for over 1 min after the end of udder preparation caused serious milk losses. Up to 62% of total milk was withheld in the udder when the delay reached 4 min. Average and peak milk flow rates also decreased significantly with delayed milking. Signs of vigilance and attempts to escape from the milking parlour appeared when camels waited for over 2 min. After a 4-min delay, camels showed signs of acute stress. Defaecation prior to milk ejection (solid faeces) and rumination during milking can be used to assess camels' milk ejection during milking. Animal welfare and milking efficiency can be ensured when camels are pre-stimulated, milked in calm conditions and with cluster attachment within a maximum of a 1-min delay after stimulation.

The Importance of Hurricane Research to Life, Property, the Economy, and National Security.

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2017-12-01

The devastating 2017 Atlantic hurricane season has brought into stark relief how much hurricane forecasts have improved - and how important it is to make them even better. Whereas the error in 48-hour track forecasts has been reduced by more than half, according to the National Hurricane Center, intensity forecasts remain challenging, especially with storms such as Harvey that strengthened from a tropical depression to a Category 4 hurricane in less than three days. The unusually active season, with Hurricane Irma sustaining 185-mph winds for a record 36 hours and two Atlantic hurricanes reaching 150-mph winds simultaneously for the first time, also highlighted what we do, and do not, know about how tropical cyclones will change as the climate warms. The extraordinary toll of Hurricanes Harvey, Irma, and Maria - which may ultimately be responsible for hundreds of deaths and an estimated $200 billion or more in damages - underscores why investments into improved forecasting must be a national priority. At NCAR and UCAR, scientists are working with their colleagues at federal agencies, the private sector, and the university community to advance our understanding of these deadly storms. Among their many projects, NCAR researchers are making experimental tropical cyclone forecasts using an innovative Earth system model that allows for variable resolution. We are working with NOAA to issue flooding, inundation, and streamflow forecasts for areas hit by hurricanes, and we have used extremely high-resolution regional models to simulate successfully the rapid hurricane intensification that has proved so difficult to predict. We are assessing ways to better predict the damage potential of tropical cyclones by looking beyond wind speed to consider such important factors as the size and forward motion of the storm. On the important question of climate change, scientists have experimented with running coupled climate models at a high enough resolution to spin up a hurricane, and we have used a convection-permitting regional model to examine how named storms of the past might look if they were to formed in a warmer, wetter future. Finally, research is also being performed to better communicate forecasts to help residents make informed choices when a damaging storm approaches.

Unrelated Helpers in a Primitively Eusocial Wasp: Is Helping Tailored Towards Direct Fitness?

PubMed Central

Leadbeater, Ellouise; Carruthers, Jonathan M.; Green, Jonathan P.; van Heusden, Jasper; Field, Jeremy

2010-01-01

The paper wasp Polistes dominulus is unique among the social insects in that nearly one-third of co-foundresses are completely unrelated to the dominant individual whose offspring they help to rear and yet reproductive skew is high. These unrelated subordinates stand to gain direct fitness through nest inheritance, raising the question of whether their behaviour is adaptively tailored towards maximizing inheritance prospects. Unusually, in this species, a wealth of theory and empirical data allows us to predict how unrelated subordinates should behave. Based on these predictions, here we compare helping in subordinates that are unrelated or related to the dominant wasp across an extensive range of field-based behavioural contexts. We find no differences in foraging effort, defense behaviour, aggression or inheritance rank between unrelated helpers and their related counterparts. Our study provides no evidence, across a number of behavioural scenarios, that the behaviour of unrelated subordinates is adaptively modified to promote direct fitness interests. PMID:20700463

Meta-heuristic ant colony optimization technique to forecast the amount of summer monsoon rainfall: skill comparison with Markov chain model

NASA Astrophysics Data System (ADS)

Chaudhuri, Sutapa; Goswami, Sayantika; Das, Debanjana; Middey, Anirban

2014-05-01

Forecasting summer monsoon rainfall with precision becomes crucial for the farmers to plan for harvesting in a country like India where the national economy is mostly based on regional agriculture. The forecast of monsoon rainfall based on artificial neural network is a well-researched problem. In the present study, the meta-heuristic ant colony optimization (ACO) technique is implemented to forecast the amount of summer monsoon rainfall for the next day over Kolkata (22.6°N, 88.4°E), India. The ACO technique belongs to swarm intelligence and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. ACO technique takes inspiration from the foraging behaviour of some ant species. The ants deposit pheromone on the ground in order to mark a favourable path that should be followed by other members of the colony. A range of rainfall amount replicating the pheromone concentration is evaluated during the summer monsoon season. The maximum amount of rainfall during summer monsoon season (June—September) is observed to be within the range of 7.5-35 mm during the period from 1998 to 2007, which is in the range 4 category set by the India Meteorological Department (IMD). The result reveals that the accuracy in forecasting the amount of rainfall for the next day during the summer monsoon season using ACO technique is 95 % where as the forecast accuracy is 83 % with Markov chain model (MCM). The forecast through ACO and MCM are compared with other existing models and validated with IMD observations from 2008 to 2012.

Inflexibility of Experts--Reality or Myth? Quantifying the Einstellung Effect in Chess Masters

ERIC Educational Resources Information Center

Bilalic, Merim; McLeod, Peter; Gobet, Fernand

2008-01-01

How does the knowledge of experts affect their behaviour in situations that require unusual methods of dealing? One possibility, loosely originating in research on creativity and skill acquisition, is that an increase in expertise can lead to inflexibility of thought due to automation of procedures. Yet another possibility, based on expertise…

Influence of Schizotypy on Responding and Contingency Awareness on Free-Operant Schedules of Reinforcement

ERIC Educational Resources Information Center

Randell, Jordan; Searle, Rob; Reed, Phil

2012-01-01

Schedules of reinforcement typically produce reliable patterns of behaviour, and one factor that can cause deviations from these normally reliable patterns is schizotypy. Low scorers on the unusual experiences subscale of the Oxford-Liverpool Inventory of Feelings and Experiences performed as expected on a yoked random-ratio (RR), random-interval…

What Do Studies of the Brain Tell Us about Learning?

ERIC Educational Resources Information Center

Harlen, Wynne

2010-01-01

Until the 1990s, the inside of the brain was a matter of mystery to all except the few, the brain surgeons, revered for their specialist knowledge. Early work was focused on explaining and attempting to treat unusual behaviours and conditions, but interest now extends to the implications of neuroscience for regular education. Non-intrusive imaging…

An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index

NASA Astrophysics Data System (ADS)

Ali, Mumtaz; Deo, Ravinesh C.; Downs, Nathan J.; Maraseni, Tek

2018-07-01

Forecasting drought by means of the World Meteorological Organization-approved Standardized Precipitation Index (SPI) is considered to be a fundamental task to support socio-economic initiatives and effectively mitigating the climate-risk. This study aims to develop a robust drought modelling strategy to forecast multi-scalar SPI in drought-rich regions of Pakistan where statistically significant lagged combinations of antecedent SPI are used to forecast future SPI. With ensemble-Adaptive Neuro Fuzzy Inference System ('ensemble-ANFIS') executed via a 10-fold cross-validation procedure, a model is constructed by randomly partitioned input-target data. Resulting in 10-member ensemble-ANFIS outputs, judged by mean square error and correlation coefficient in the training period, the optimal forecasts are attained by the averaged simulations, and the model is benchmarked with M5 Model Tree and Minimax Probability Machine Regression (MPMR). The results show the proposed ensemble-ANFIS model's preciseness was notably better (in terms of the root mean square and mean absolute error including the Willmott's, Nash-Sutcliffe and Legates McCabe's index) for the 6- and 12- month compared to the 3-month forecasts as verified by the largest error proportions that registered in smallest error band. Applying 10-member simulations, ensemble-ANFIS model was validated for its ability to forecast severity (S), duration (D) and intensity (I) of drought (including the error bound). This enabled uncertainty between multi-models to be rationalized more efficiently, leading to a reduction in forecast error caused by stochasticity in drought behaviours. Through cross-validations at diverse sites, a geographic signature in modelled uncertainties was also calculated. Considering the superiority of ensemble-ANFIS approach and its ability to generate uncertainty-based information, the study advocates the versatility of a multi-model approach for drought-risk forecasting and its prime importance for estimating drought properties over confidence intervals to generate better information for strategic decision-making.

Electrochemically induced actuation of liquid metal marbles

NASA Astrophysics Data System (ADS)

Tang, Shi-Yang; Sivan, Vijay; Khoshmanesh, Khashayar; O'Mullane, Anthony P.; Tang, Xinke; Gol, Berrak; Eshtiaghi, Nicky; Lieder, Felix; Petersen, Phred; Mitchell, Arnan; Kalantar-Zadeh, Kourosh

2013-06-01

Controlled actuation of soft objects with functional surfaces in aqueous environments presents opportunities for liquid phase electronics, novel assembled super-structures and unusual mechanical properties. We show the extraordinary electrochemically induced actuation of liquid metal droplets coated with nanoparticles, so-called ``liquid metal marbles''. We demonstrate that nanoparticle coatings of these marbles offer an extra dimension for affecting the bipolar electrochemically induced actuation. The nanoparticles can readily migrate along the surface of liquid metals, upon the application of electric fields, altering the capacitive behaviour and surface tension in a highly asymmetric fashion. Surprising actuation behaviours are observed illustrating that nanoparticle coatings can have a strong effect on the movement of these marbles. This significant novel phenomenon, combined with unique properties of liquid metal marbles, represents an exciting platform for enabling diverse applications that cannot be achieved using rigid metal beads.Controlled actuation of soft objects with functional surfaces in aqueous environments presents opportunities for liquid phase electronics, novel assembled super-structures and unusual mechanical properties. We show the extraordinary electrochemically induced actuation of liquid metal droplets coated with nanoparticles, so-called ``liquid metal marbles''. We demonstrate that nanoparticle coatings of these marbles offer an extra dimension for affecting the bipolar electrochemically induced actuation. The nanoparticles can readily migrate along the surface of liquid metals, upon the application of electric fields, altering the capacitive behaviour and surface tension in a highly asymmetric fashion. Surprising actuation behaviours are observed illustrating that nanoparticle coatings can have a strong effect on the movement of these marbles. This significant novel phenomenon, combined with unique properties of liquid metal marbles, represents an exciting platform for enabling diverse applications that cannot be achieved using rigid metal beads. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr00185g

Anaphylaxis and intimate behaviour.

PubMed

Liccardi, Gennaro; Caminati, Marco; Senna, Gianenrico; Calzetta, Luigino; Rogliani, Paola

2017-10-01

Intimate behaviours may represent an unusual way of exposure to a culprit allergen, or the frame for sex-related allergies due to triggers typically linked to that situation. The present review aims at summarizing the state of the art about the topic, in order to spread the awareness and the basic know-how in the field of sexual-related allergies. Kiss-related IgE-mediated reactions are caused in sensitized partners mainly by the passive transport of allergenic molecules through saliva, skin or oral mucosa. It has also been recently suggested that kissing may act as an epicutaneous way for induction of allergic sensitization. Among food and drugs, not only but mostly, peanuts and beta-lactams, respectively, are the usual trigger. Although controversial, 1-hour wait before kissing and a proper mouth cleaning have been suggested as prevention strategies. Sexual intercourse related local or systemic symptoms can be caused by seminal plasma hypersensitivity, an IgE-mediated/type IV reaction due to prostate-specific antigen, which carries high homology to the canine prostatic kallikrein (Can f 5). Although applied to few patients, successful desensitization and immunotherapy protocols have been proposed. Intimate behaviours are possible modalities of contact with the allergen. The exact prevalence of such hypersensitivity reactions is not known, but for its implications on Quality of Life and reproductive wishes, the possible link between sex and allergy should become part of the personal culture of clinical allergists and every clinician, in order to extend and improve the diagnosis of unusual or unexplained conditions.

Forecasting short-term data center network traffic load with convolutional neural networks.

PubMed

Mozo, Alberto; Ordozgoiti, Bruno; Gómez-Canaval, Sandra

2018-01-01

Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution.

Forecasting short-term data center network traffic load with convolutional neural networks

PubMed Central

Ordozgoiti, Bruno; Gómez-Canaval, Sandra

2018-01-01

Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution. PMID:29408936

Revisiting the cognitive buffer hypothesis for the evolution of large brains

PubMed Central

Sol, Daniel

2008-01-01

Why have some animals evolved large brains despite substantial energetic and developmental costs? A classic answer is that a large brain facilitates the construction of behavioural responses to unusual, novel or complex socioecological challenges. This buffer effect should increase survival rates and favour a longer reproductive life, thereby compensating for the costs of delayed reproduction. Although still limited, evidence in birds and mammals is accumulating that a large brain facilitates the construction of novel and altered behavioural patterns and that this ability helps dealing with new ecological challenges more successfully, supporting the cognitive-buffer interpretation of the evolution of large brains. PMID:19049952

Free Fall Misconceptions: Results of a Graph Based Pre-Test of Sophomore Civil Engineering Students

ERIC Educational Resources Information Center

Montecinos, Alicia M.

2014-01-01

A partially unusual behaviour was found among 14 sophomore students of civil engineering who took a pre test for a free fall laboratory session, in the context of a general mechanics course. An analysis contemplating mathematics models and physics models consistency was made. In all cases, the students presented evidence favoring a correct free…

Water Intake and Risk of Hyponatraemia in Prader-Willi Syndrome

ERIC Educational Resources Information Center

Akefeldt, A.

2009-01-01

Background and Methods: Unusual water intake and drinking behaviour has occasionally been observed in individuals with Prader-Willi syndrome (PWS). The aim of this study is to explore whether this observation is a part of the PWS phenotype and what the consequences may be. The parents of 51 individuals with PWS (age range 2-40 years) were asked by…

Wilson loops in warped resolved deformed conifolds

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

Bennett, Stephen, E-mail: pystephen@swansea.ac.uk

We calculate quark-antiquark potentials using the relationship between the expectation value of the Wilson loop and the action of a probe string in the string dual. We review and categorise the possible forms of the dependence of the energy on the separation between the quarks. In particular, we examine the possibility of there being a minimum separation for probe strings which do not penetrate close to the origin of the bulk space, and derive a condition which determines whether this is the case. We then apply these considerations to the flavoured resolved deformed conifold background of Gaillard et al. (2010)more » . We suggest that the unusual behaviour that we observe in this solution is likely to be related to the IR singularity which is not present in the unflavoured case. - Highlights: > We calculate quark-antiquark potentials using the Wilson loop and the action of a probe string in the string dual. > We review and categorise the possible forms of the dependence of the energy on the separation between the quarks. > We look in particular at the flavoured resolved deformed conifold. > There appears to be unusual behaviour which seems likely to be related to the IR singularity introduced by flavours.« less

The life-history basis of behavioural innovations

PubMed Central

Sol, Daniel; Sayol, Ferran; Ducatez, Simon; Lefebvre, Louis

2016-01-01

The evolutionary origin of innovativeness remains puzzling because innovating means responding to novel or unusual problems and hence is unlikely to be selected by itself. A plausible alternative is considering innovativeness as a co-opted product of traits that have evolved for other functions yet together predispose individuals to solve problems by adopting novel behaviours. However, this raises the question of why these adaptations should evolve together in an animal. Here, we develop the argument that the adaptations enabling animals to innovate evolve together because they are jointly part of a life-history strategy for coping with environmental changes. In support of this claim, we present comparative evidence showing that in birds, (i) innovative propensity is linked to life histories that prioritize future over current reproduction, (ii) the link is in part explained by differences in brain size, and (iii) innovative propensity and life-history traits may evolve together in generalist species that frequently expose themselves to novel or unusual conditions. Combined with previous evidence, these findings suggest that innovativeness is not a specialized adaptation but more likely part of a broader general adaptive system to cope with changes in the environment. PMID:26926277

Unusual behaviour of phototrophic picoplankton in turbid waters.

PubMed

Somogyi, Boglárka; Pálffy, Károly; V-Balogh, Katalin; Botta-Dukát, Zoltán; Vörös, Lajos

2017-01-01

Autotrophic picoplankton (APP) abundance and contribution to phytoplankton biomass was studied in Hungarian shallow lakes to test the effect of inorganic turbidity determining the size distribution of the phytoplankton. The studied lakes displayed wide turbidity (TSS: 4-2250 mg l-1) and phytoplankton biomass (chlorophyll a: 1-460 μg l-1) range, as well as APP abundance (0 and 100 million cells ml-1) and contribution (0-100%) to total phytoplankton biomass. Inorganic turbidity had a significant effect on the abundance and contribution of APP, resulting in higher values compared to other freshwater lakes with the same phytoplankton biomass. Our analysis has provided empirical evidence for a switching point (50 mg l-1 inorganic turbidity), above which turbidity is the key factor causing APP predominance regardless of phytoplankton biomass in shallow turbid lakes. Our results have shown that turbid shallow lakes are unique waters, where the formerly and widely accepted model (decreasing APP contribution with increasing phytoplankton biomass) is not applicable. We hypothesize that this unusual behaviour of APP in turbid waters is a result of either diminished underwater light intensity or a reduced grazing pressure due to high inorganic turbidity.

Unusual behaviour of phototrophic picoplankton in turbid waters

PubMed Central

Pálffy, Károly; V. -Balogh, Katalin; Botta-Dukát, Zoltán; Vörös, Lajos

2017-01-01

Autotrophic picoplankton (APP) abundance and contribution to phytoplankton biomass was studied in Hungarian shallow lakes to test the effect of inorganic turbidity determining the size distribution of the phytoplankton. The studied lakes displayed wide turbidity (TSS: 4–2250 mg l-1) and phytoplankton biomass (chlorophyll a: 1–460 μg l-1) range, as well as APP abundance (0 and 100 million cells ml-1) and contribution (0–100%) to total phytoplankton biomass. Inorganic turbidity had a significant effect on the abundance and contribution of APP, resulting in higher values compared to other freshwater lakes with the same phytoplankton biomass. Our analysis has provided empirical evidence for a switching point (50 mg l-1 inorganic turbidity), above which turbidity is the key factor causing APP predominance regardless of phytoplankton biomass in shallow turbid lakes. Our results have shown that turbid shallow lakes are unique waters, where the formerly and widely accepted model (decreasing APP contribution with increasing phytoplankton biomass) is not applicable. We hypothesize that this unusual behaviour of APP in turbid waters is a result of either diminished underwater light intensity or a reduced grazing pressure due to high inorganic turbidity. PMID:28346542

Deterministic decomposition and seasonal ARIMA time series models applied to airport noise forecasting

NASA Astrophysics Data System (ADS)

Guarnaccia, Claudio; Quartieri, Joseph; Tepedino, Carmine

2017-06-01

One of the most hazardous physical polluting agents, considering their effects on human health, is acoustical noise. Airports are a strong source of acoustical noise, due to the airplanes turbines, to the aero-dynamical noise of transits, to the acceleration or the breaking during the take-off and landing phases of aircrafts, to the road traffic around the airport, etc.. The monitoring and the prediction of the acoustical level emitted by airports can be very useful to assess the impact on human health and activities. In the airports noise scenario, thanks to flights scheduling, the predominant sources may have a periodic behaviour. Thus, a Time Series Analysis approach can be adopted, considering that a general trend and a seasonal behaviour can be highlighted and used to build a predictive model. In this paper, two different approaches are adopted, thus two predictive models are constructed and tested. The first model is based on deterministic decomposition and is built composing the trend, that is the long term behaviour, the seasonality, that is the periodic component, and the random variations. The second model is based on seasonal autoregressive moving average, and it belongs to the stochastic class of models. The two different models are fitted on an acoustical level dataset collected close to the Nice (France) international airport. Results will be encouraging and will show good prediction performances of both the adopted strategies. A residual analysis is performed, in order to quantify the forecasting error features.

Short- and Long-Term Earthquake Forecasts Based on Statistical Models

NASA Astrophysics Data System (ADS)

Console, Rodolfo; Taroni, Matteo; Murru, Maura; Falcone, Giuseppe; Marzocchi, Warner

2017-04-01

The epidemic-type aftershock sequences (ETAS) models have been experimentally used to forecast the space-time earthquake occurrence rate during the sequence that followed the 2009 L'Aquila earthquake and for the 2012 Emilia earthquake sequence. These forecasts represented the two first pioneering attempts to check the feasibility of providing operational earthquake forecasting (OEF) in Italy. After the 2009 L'Aquila earthquake the Italian Department of Civil Protection nominated an International Commission on Earthquake Forecasting (ICEF) for the development of the first official OEF in Italy that was implemented for testing purposes by the newly established "Centro di Pericolosità Sismica" (CPS, the seismic Hazard Center) at the Istituto Nazionale di Geofisica e Vulcanologia (INGV). According to the ICEF guidelines, the system is open, transparent, reproducible and testable. The scientific information delivered by OEF-Italy is shaped in different formats according to the interested stakeholders, such as scientists, national and regional authorities, and the general public. The communication to people is certainly the most challenging issue, and careful pilot tests are necessary to check the effectiveness of the communication strategy, before opening the information to the public. With regard to long-term time-dependent earthquake forecast, the application of a newly developed simulation algorithm to Calabria region provided typical features in time, space and magnitude behaviour of the seismicity, which can be compared with those of the real observations. These features include long-term pseudo-periodicity and clustering of strong earthquakes, and a realistic earthquake magnitude distribution departing from the Gutenberg-Richter distribution in the moderate and higher magnitude range.

Using Scaling to Understand, Model and Predict Global Scale Anthropogenic and Natural Climate Change

NASA Astrophysics Data System (ADS)

Lovejoy, S.; del Rio Amador, L.

2014-12-01

The atmosphere is variable over twenty orders of magnitude in time (≈10-3 to 1017 s) and almost all of the variance is in the spectral "background" which we show can be divided into five scaling regimes: weather, macroweather, climate, macroclimate and megaclimate. We illustrate this with instrumental and paleo data. Based the signs of the fluctuation exponent H, we argue that while the weather is "what you get" (H>0: fluctuations increasing with scale), that it is macroweather (H<0: fluctuations decreasing with scale) - not climate - "that you expect". The conventional framework that treats the background as close to white noise and focuses on quasi-periodic variability assumes a spectrum that is in error by a factor of a quadrillion (≈ 1015). Using this scaling framework, we can quantify the natural variability, distinguish it from anthropogenic variability, test various statistical hypotheses and make stochastic climate forecasts. For example, we estimate the probability that the warming is simply a giant century long natural fluctuation is less than 1%, most likely less than 0.1% and estimate return periods for natural warming events of different strengths and durations, including the slow down ("pause") in the warming since 1998. The return period for the pause was found to be 20-50 years i.e. not very unusual; however it immediately follows a 6 year "pre-pause" warming event of almost the same magnitude with a similar return period (30 - 40 years). To improve on these unconditional estimates, we can use scaling models to exploit the long range memory of the climate process to make accurate stochastic forecasts of the climate including the pause. We illustrate stochastic forecasts on monthly and annual scale series of global and northern hemisphere surface temperatures. We obtain forecast skill nearly as high as the theoretical (scaling) predictability limits allow: for example, using hindcasts we find that at 10 year forecast horizons we can still explain ≈ 15% of the anomaly variance. These scaling hindcasts have comparable - or smaller - RMS errors than existing GCM's. We discuss how these be further improved by going beyond time series forecasts to space-time.

Effects of strong mining tremors, and assessment of the buildings' resistance to the dynamic impacts

NASA Astrophysics Data System (ADS)

Bryt-Nitarska, Izabela

2018-04-01

A particularly important element in the assessment of the actual state of the threats which is caused by conducting the mining exploitation of seams bumping under the urban areas is to diagnose the condition of the land development after hard shocks. In the buildings, for which the impact of the mining activities, including the tremors, is not taken into account at the stage of design and formulation of the strength and use conditions, conclusions from the structure behaviour under the tremor influence are an essential part of the assessment of the possibility for transferring the further dynamic impacts. The use of conclusions from the in situ research has its role in anticipating the behaviour of the buildings in case of the forecast of the mining tremors effects in the regions of their impacts. These conclusions should also provide ground for the assumptions to the scope of the building prevention necessary to be taken in case of forecasting the tremors with big intensity. Based on the analysis of effects which occurred in the land development after the highenergy mining tremors, the elements of the dynamic resistance assessment for the buildings with traditional structure were discussed.

Analysis of a Meteorological Database for London Heathrow in the Context of Wake Vortex Hazards

NASA Astrophysics Data System (ADS)

Agnew, P.; Ogden, D. J.; Hoad, D. J.

2003-04-01

A database of meteorological parameters collected by aircraft arriving at LHR has recently been compiled. We have used the recorded variation of temperature and wind with height to deduce the 'wake vortex behaviour class' (WVBC) along the glide slope, as experienced by each flight. The integrated state of the glide slope has been investigated, allowing us to estimate the proportion of time for which the wake vortex threat is reduced, due to either rapid decay or transport off the glide slope. A numerical weather prediction model was used to forecast the meteorological parameters for periods coinciding with the aircraft data. This allowed us to perform a comparison of forecast WVBC with those deduced from the aircraft measurements.

Attachment representations in mothers with abnormal illness behaviour by proxy.

PubMed

Adshead, Gwen; Bluglass, Kerry

2005-10-01

Abnormal illness behaviour by proxy (also known as factitious illness by proxy or Munchhausen syndrome by proxy) is a type of child maltreatment, the origins of which are poorly understood. To describe attachment representations in a cohort of mothers demonstrating abnormal illness behaviour by proxy. Sixty-seven mothers who had shown this behaviour took part in a semistructured interview assessing their attachment representations. Only 12 mothers (18%) were rated secure in terms of their own childhood attachments. There was evidence of unresolved trauma or loss reactions in 40 mothers (60%). Eighteen mothers (27%) gave unusually disorganised and incoherent accounts of attachment relationships in their own childhoods. The frequency of these attachment categories is higher than in normal non-clinical samples. Insecure attachment is a risk factor for this type of child maltreatment. Therapeutic interventions could be offered in relation to unresolved traumatic stress or bereavement responses. Further study of similar groups, such as mothers with sick children or mothers with histories of traumatic experience, would be a useful next step.

Coping with Unusual ExperienceS for 12-18 year olds (CUES+): a transdiagnostic randomised controlled trial of the effectiveness of cognitive therapy in reducing distress associated with unusual experiences in adolescent mental health services: study protocol for a randomised controlled trial.

PubMed

Jolley, Suzanne; Browning, Sophie; Corrigall, Richard; Laurens, Kristin R; Hirsch, Colette; Bracegirdle, Karen; Gin, Kimberley; Muccio, Francesca; Stewart, Catherine; Banerjea, Partha; Kuipers, Elizabeth; Garety, Philippa; Byrne, Majella; Onwumere, Juliana; Achilla, Evanthia; McCrone, Paul; Emsley, Richard

2017-12-04

Childhood 'unusual experiences' (such as hearing voices that others cannot, or suspicions of being followed) are common, but can become more distressing during adolescence, especially for young people in contact with Child and Adolescent Mental Health Services (CAMHS). Unusual experiences that are distressing or have adverse life impact (UEDs) are associated with a range of current and future emotional, behavioural and mental health difficulties. Recommendations for psychological intervention are based on evidence from adult studies, with some support from small, pilot, child-specific evaluations. Research is needed to ensure that the recommendations suit children as well as adults. The CUES+ study (Coping with Unusual ExperienceS for 12-18 year olds) aims to find out whether cognitive behaviour therapy for UEDs (CBT-UED) is a helpful and cost-effective addition to usual community care for 12-18 year olds presenting to United Kingdom National Health Service Child and Adolescent Mental Health Services in four London boroughs. The CUES+ study is a randomised controlled trial comparing CBT-UED plus routine care to routine care alone. CBT-UED comprises up to 16 sessions, including up to 12 individual and up to four family support meetings, each lasting around 45-60 min, delivered weekly. The primary outcome is emotional distress. Secondary outcomes are change in UEDs, risk events (self-harm, attendance at emergency services, other adverse events) and health economic outcomes. Participants will be randomised in a 1:1 ratio after baseline assessment. Randomisation will be stratified by borough and by severity of mental health presentation: 'severe' (an identified psychotic or bipolar disorder) or any 'other' condition. Outcomes will be assessed by a trained assessor blind to treatment condition at 0, 16 and 24 weeks. Recruitment began in February, 2015 and is ongoing until the end of March, 2017. The CUES+ study will contribute to the currently limited child-specific evidence base for psychological interventions for UEDs occurring in the context of psychosis or any other mental health presentation. International Standard Randomised Controlled Trials, ID: ISRCTN21802136 . Prospectively registered on 12 January 2015. Protocol V3 31 August 2015 with screening amended.

Using additional external inputs to forecast water quality with an artificial neural network for contamination event detection in source water

NASA Astrophysics Data System (ADS)

Schmidt, F.; Liu, S.

2016-12-01

Source water quality plays an important role for the safety of drinking water and early detection of its contamination is vital to taking appropriate countermeasures. However, compared to drinking water, it is more difficult to detect contamination events because its environment is less controlled and numerous natural causes contribute to a high variability of the background values. In this project, Artificial Neural Networks (ANNs) and a Contamination Event Detection Process (CED Process) were used to identify events in river water. The ANN models the response of basic water quality sensors obtained in laboratory experiments in an off-line learning stage and continuously forecasts future values of the time line in an on-line forecasting step. During this second stage, the CED Process compares the forecast to the measured value and classifies it as regular background or event value, which modifies the ANN's continuous learning and influences its forecasts. In addition to this basic setup, external information is fed to the CED Process: A so-called Operator Input (OI) is provided to inform about unusual water quality levels that are unrelated to the presence of contamination, for example due to cooling water discharge from a nearby power plant. This study's primary goal is to evaluate how well the OI fits into the design of the combined forecasting ANN and CED Process and to understand its effects on the online forecasting stage. To test this, data from laboratory experiments conducted previously at the School of Environment, Tsinghua University, have been used to perform simulations highlighting features and drawbacks of this method. Applying the OI has been shown to have a positive influence on the ANN's ability to handle a sudden change in background values, which is unrelated to contamination. However, it might also mask the presence of an event, an issue that underlines the necessity to have several instances of the algorithm run in parallel. Other difficulties addressed in this study include the source and the format of the OI. This project tries to add to the ongoing research into algorithms for CED. It provides ideas for how results from the binary classification of time series could be evaluated in a more realistic fashion and shows what the advantages and limitations of such a method would be.

Test operation of a real-time tsunami inundation forecast system using actual data observed by S-net

NASA Astrophysics Data System (ADS)

Suzuki, W.; Yamamoto, N.; Miyoshi, T.; Aoi, S.

2017-12-01

If the tsunami inundation information can be rapidly and stably forecast before the large tsunami attacks, the information would have effectively people realize the impeding danger and necessity of evacuation. Toward that goal, we have developed a prototype system to perform the real-time tsunami inundation forecast for Chiba prefecture, eastern Japan, using off-shore ocean bottom pressure data observed by the seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net) (Aoi et al., 2015, AGU). Because tsunami inundation simulation requires a large computation cost, we employ a database approach searching the pre-calculated tsunami scenarios that reasonably explain the observed S-net pressure data based on the multi-index method (Yamamoto et al., 2016, EPS). The scenario search is regularly repeated, not triggered by the occurrence of the tsunami event, and the forecast information is generated from the selected scenarios that meet the criterion. Test operation of the prototype system using the actual observation data started in April, 2017 and the performance and behavior of the system during non-tsunami event periods have been examined. It is found that the treatment of the noises affecting the observed data is the main issue to be solved toward the improvement of the system. Even if the observed pressure data are filtered to extract the tsunami signals, the noises in ordinary times or unusually large noises like high ocean waves due to storm affect the comparison between the observed and scenario data. Due to the noises, the tsunami scenarios are selected and the tsunami is forecast although any tsunami event does not actually occur. In most cases, the selected scenarios due to the noises have the fault models in the region along the Kurile or Izu-Bonin Trenches, far from the S-net region, or the fault models below the land. Based on the parallel operation of the forecast system with a different scenario search condition and examination of the fault models, we improve the stability and performance of the forecast system.This work was supported by Council for Science, Technology and Innovation(CSTI), Cross-ministerial Strategic Innovation Promotion Program (SIP), "Enhancement of societal resiliency against natural disasters"(Funding agency: JST).

Ionospheric behaviour during storm recovery phase

NASA Astrophysics Data System (ADS)

Buresova, D.; Lastovicka, J.; Boska, J.; Sindelarova, T.; Chum, J.

2012-04-01

Intensive ionospheric research, numerous multi-instrumental observations and large-scale numerical simulations of ionospheric F region response to magnetic storm-induced disturbances during the last several decades were primarily focused on the storm main phase, in most cases covering only a few hours of the recovery phase following after storm culmination. Ionospheric behaviour during entire recovery phase still belongs to not sufficiently explored and hardly predictable features. In general, the recovery phase is characterized by an abatement of perturbations and a gradual return to the "ground state" of ionosphere. However, observations of stormy ionosphere show significant departures from the climatology also within this phase. This paper deals with the quantitative and qualitative analysis of the ionospheric behaviour during the entire recovery phase of strong-to-severe magnetic storms at middle latitudes for nowadays and future modelling and forecasting purposes.

Avoiding the parametric roll

NASA Astrophysics Data System (ADS)

Acomi, Nicoleta; Ancuţa, Cristian; Andrei, Cristian; Boştinǎ, Alina; Boştinǎ, Aurel

2016-12-01

Ships are mainly built to sail and transport cargo at sea. Environmental conditions and state of the sea are communicated to vessels through periodic weather forecasts. Despite officers being aware of the sea state, their sea time experience is a decisive factor when the vessel encounters severe environmental conditions. Another important factor is the loading condition of the vessel, which triggers different behaviour in similar marine environmental conditions. This paper aims to analyse the behaviour of a port container vessel in severe environmental conditions and to estimate the potential conditions of parametric roll resonance. Octopus software simulation is employed to simulate vessel motions under certain conditions of the sea, with possibility to analyse the behaviour of ships and the impact of high waves on ships due to specific wave encounter situations. The study should be regarded as a supporting tool during the decision making process.

Interspecies sexual behaviour between a male Japanese macaque and female sika deer.

PubMed

Pelé, Marie; Bonnefoy, Alexandre; Shimada, Masaki; Sueur, Cédric

2017-04-01

Interspecies sexual behaviour or 'reproductive interference' has been reported across a wide range of animal taxa. However, most of these occurrences were observed in phylogenetically close species and were mainly discussed in terms of their effect on fitness, hybridization and species survival. The few cases of heterospecific mating in distant species occurred between animals that were bred and maintained in captivity. Only one scientific study has reported this phenomenon, describing sexual harassment of king penguins by an Antarctic fur seal. This is the first article to report mating behaviour between a male Japanese macaque (Macaca fuscata yakui) and female sika deer (Cervus nippon yakushimae) on Yakushima Island, Japan. Although Japanese macaques are known to ride deer, this individual showed clearly sexual behaviour towards several female deer, some of which tried to escape whilst others accepted the mount. This male seems to belong to a group of peripheral males. Although this phenomenon may be explained as copulation learning, this is highly unlikely. The most realistic hypothesis would be that of mate deprivation, which states that males with limited access to females are more likely to display this behaviour. Whatever the cause for this event may be, the observation of highly unusual animal behaviour may be a key to understanding the evolution of heterospecific mating behaviour in the animal kingdom.

The effect of domain length and parameter estimation on observation impact in data assimilation for flood inundation forecasting.

NASA Astrophysics Data System (ADS)

Cooper, Elizabeth; Dance, Sarah; Garcia-Pintado, Javier; Nichols, Nancy; Smith, Polly

2017-04-01

Timely and accurate inundation forecasting provides vital information about the behaviour of fluvial flood water, enabling mitigating actions to be taken by residents and emergency services. Data assimilation is a powerful mathematical technique for combining forecasts from hydrodynamic models with observations to produce a more accurate forecast. We discuss the effect of both domain size and channel friction parameter estimation on observation impact in data assimilation for inundation forecasting. Numerical shallow water simulations are carried out in a simple, idealized river channel topography. Data assimilation is performed using an Ensemble Transform Kalman Filter (ETKF) and synthetic observations of water depth in identical twin experiments. We show that reinitialising the numerical inundation model with corrected water levels after an assimilation can cause an initialisation shock if a hydrostatic assumption is made, leading to significant degradation of the forecast for several hours immediately following an assimilation. We demonstrate an effective and novel method for dealing with this. We find that using data assimilation to combine observations of water depth with forecasts from a hydrodynamic model corrects the forecast very effectively at time of the observations. In agreement with other authors we find that the corrected forecast then moves quickly back to the open loop forecast which does not take the observations into account. Our investigations show that the time taken for the forecast to decay back to the open loop case depends on the length of the domain of interest when only water levels are corrected. This is because the assimilation corrects water depths in all parts of the domain, even when observations are only available in one area. Error growth in the forecast step then starts at the upstream part of the domain and propagates downstream. The impact of the observations is therefore longer-lived in a longer domain. We have found that the upstream-downstream pattern of error growth can be due to incorrect friction parameter specification, rather than errors in inflow as shown elsewhere. Our results show that joint state-parameter estimation can recover accurate values for the parameter controlling channel friction processes in the model, even when observations of water level are only available on part of the flood plain. Correcting water levels and the channel friction parameter together leads to a large improvement in the forecast water levels at all simulation times. The impact of the observations is therefore much greater when the channel friction parameter is corrected along with water levels. We find that domain length effects disappear for joint state-parameter estimation.

Does a more skilful meteorological input lead to a more skilful flood forecast at seasonal timescales?

NASA Astrophysics Data System (ADS)

Neumann, Jessica; Arnal, Louise; Magnusson, Linus; Cloke, Hannah

2017-04-01

Seasonal river flow forecasts are important for many aspects of the water sector including flood forecasting, water supply, hydropower generation and navigation. In addition to short term predictions, seasonal forecasts have the potential to realise higher benefits through more optimal and consistent decisions. Their operational use however, remains a challenge due to uncertainties posed by the initial hydrologic conditions (e.g. soil moisture, groundwater levels) and seasonal climate forcings (mainly forecasts of precipitation and temperature), leading to a decrease in skill with increasing lead times. Here we present a stakeholder-led case study for the Thames catchment (UK), currently being undertaken as part of the H2020 IMPREX project. The winter of 2013-14 was the wettest on record in the UK; driven by 12 major Atlantic depressions, the Thames catchment was subject to compound (concurrent) flooding from fluvial and groundwater sources. Focusing on the 2013-14 floods, this study aims to see whether increased skill in meteorological input translates through to more accurate forecasting of compound flood events at seasonal timescales in the Thames catchment. An earlier analysis of the ECMWF System 4 (S4) seasonal meteorological forecasts revealed that it did not skilfully forecast the extreme event of winter 2013-14. This motivated the implementation of an atmospheric experiment by the ECMWF to force the S4 to more accurately represent the low-pressure weather conditions prevailing in winter 2013-14 [1]. Here, we used both the standard and the "improved" S4 seasonal meteorological forecasts to force the EFAS (European Flood Awareness System) LISFLOOD hydrological model. Both hydrological forecasts were started on the 1st of November 2013 and run for 4 months of lead time to capture the peak of the 2013-14 flood event. Comparing the seasonal hydrological forecasts produced with both meteorological forcing data will enable us to assess how the improved meteorology translates into skill in the hydrological forecast for this extreme compound event. As primary stakeholders involved in the study, the Environment Agency and Flood Forecasting Centre are responsible for managing flood risk in the UK. For them, the detection of a potential flood signal weeks or months in advance could be of great value in terms of operational practice, decision-making and early warning. [1] Rodwell, M.J., Ferranti, L., Magnusson, L., Weisheimer, A., Rabier, F. & Richardson, D. (2015) Diagnosis of northern hemispheric regime behaviour during winter 2013/14. ECMWF Technical Memoranda 769.

State-space based analysis and forecasting of macroscopic road safety trends in Greece.

PubMed

Antoniou, Constantinos; Yannis, George

2013-11-01

In this paper, macroscopic road safety trends in Greece are analyzed using state-space models and data for 52 years (1960-2011). Seemingly unrelated time series equations (SUTSE) models are developed first, followed by richer latent risk time-series (LRT) models. As reliable estimates of vehicle-kilometers are not available for Greece, the number of vehicles in circulation is used as a proxy to the exposure. Alternative considered models are presented and discussed, including diagnostics for the assessment of their model quality and recommendations for further enrichment of this model. Important interventions were incorporated in the models developed (1986 financial crisis, 1991 old-car exchange scheme, 1996 new road fatality definition) and found statistically significant. Furthermore, the forecasting results using data up to 2008 were compared with final actual data (2009-2011) indicating that the models perform properly, even in unusual situations, like the current strong financial crisis in Greece. Forecasting results up to 2020 are also presented and compared with the forecasts of a model that explicitly considers the currently on-going recession. Modeling the recession, and assuming that it will end by 2013, results in more reasonable estimates of risk and vehicle-kilometers for the 2020 horizon. This research demonstrates the benefits of using advanced state-space modeling techniques for modeling macroscopic road safety trends, such as allowing the explicit modeling of interventions. The challenges associated with the application of such state-of-the-art models for macroscopic phenomena, such as traffic fatalities in a region or country, are also highlighted. Furthermore, it is demonstrated that it is possible to apply such complex models using the relatively short time-series that are available in macroscopic road safety analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Tracking employment shocks using mobile phone data

PubMed Central

Toole, Jameson L.; Lin, Yu-Ru; Muehlegger, Erich; Shoag, Daniel; González, Marta C.; Lazer, David

2015-01-01

Can data from mobile phones be used to observe economic shocks and their consequences at multiple scales? Here we present novel methods to detect mass layoffs, identify individuals affected by them and predict changes in aggregate unemployment rates using call detail records (CDRs) from mobile phones. Using the closure of a large manufacturing plant as a case study, we first describe a structural break model to correctly detect the date of a mass layoff and estimate its size. We then use a Bayesian classification model to identify affected individuals by observing changes in calling behaviour following the plant's closure. For these affected individuals, we observe significant declines in social behaviour and mobility following job loss. Using the features identified at the micro level, we show that the same changes in these calling behaviours, aggregated at the regional level, can improve forecasts of macro unemployment rates. These methods and results highlight promise of new data resources to measure microeconomic behaviour and improve estimates of critical economic indicators. PMID:26018965

Assessing the value of post-processed state-of-the-art long-term weather forecast ensembles for agricultural water management mediated by farmers' behaviours

NASA Astrophysics Data System (ADS)

Li, Yu; Giuliani, Matteo; Castelletti, Andrea

2016-04-01

Recent advances in modelling of coupled ocean-atmosphere dynamics significantly improved skills of long-term climate forecast from global circulation models (GCMs). These more accurate weather predictions are supposed to be a valuable support to farmers in optimizing farming operations (e.g. crop choice, cropping and watering time) and for more effectively coping with the adverse impacts of climate variability. Yet, assessing how actually valuable this information can be to a farmer is not straightforward and farmers' response must be taken into consideration. Indeed, in the context of agricultural systems potentially useful forecast information should alter stakeholders' expectation, modify their decisions, and ultimately produce an impact on their performance. Nevertheless, long-term forecast are mostly evaluated in terms of accuracy (i.e., forecast quality) by comparing hindcast and observed values and only few studies investigated the operational value of forecast looking at the gain of utility within the decision-making context, e.g. by considering the derivative of forecast information, such as simulated crop yields or simulated soil moisture, which are essential to farmers' decision-making process. In this study, we contribute a step further in the assessment of the operational value of long-term weather forecasts products by embedding these latter into farmers' behavioral models. This allows a more critical assessment of the forecast value mediated by the end-users' perspective, including farmers' risk attitudes and behavioral patterns. Specifically, we evaluate the operational value of thirteen state-of-the-art long-range forecast products against climatology forecast and empirical prediction (i.e. past year climate and historical average) within an integrated agronomic modeling framework embedding an implicit model of the farmers' decision-making process. Raw ensemble datasets are bias-corrected and downscaled using a stochastic weather generator, in order to address the mismatch of the spatio-temporal scale between forecast data from GCMs and our model. For each product, the experiment is composed by two cascade simulations: 1) an ex-ante simulation using forecast data, and 2) an ex-post simulation with observations. Multi-year simulations are performed to account for climate variability, and the operational value of the different forecast products is evaluated against the perfect foresight on the basis of expected crop productivity as well as the final decisions under different decision-making criterions. Our results show that not all products generate beneficial effects to farmers' performance, and the forecast errors might be amplified due to farmers' decision-making process and risk attitudes, yielding little or even worse performance compared with the empirical approaches.

New smoke predictions for Alaska in NOAA’s National Air Quality Forecast Capability

NASA Astrophysics Data System (ADS)

Davidson, P. M.; Ruminski, M.; Draxler, R.; Kondragunta, S.; Zeng, J.; Rolph, G.; Stajner, I.; Manikin, G.

2009-12-01

Smoke from wildfire is an important component of fine particle pollution, which is responsible for tens of thousands of premature deaths each year in the US. In Alaska, wildfire smoke is the leading cause of poor air quality in summer. Smoke forecast guidance helps air quality forecasters and the public take steps to limit exposure to airborne particulate matter. A new smoke forecast guidance tool, built by a cross-NOAA team, leverages efforts of NOAA’s partners at the USFS on wildfire emissions information, and with EPA, in coordinating with state/local air quality forecasters. Required operational deployment criteria, in categories of objective verification, subjective feedback, and production readiness, have been demonstrated in experimental testing during 2008-2009, for addition to the operational products in NOAA's National Air Quality Forecast Capability. The Alaska smoke forecast tool is an adaptation of NOAA’s smoke predictions implemented operationally for the lower 48 states (CONUS) in 2007. The tool integrates satellite information on location of wildfires with weather (North American mesoscale model) and smoke dispersion (HYSPLIT) models to produce daily predictions of smoke transport for Alaska, in binary and graphical formats. Hour-by hour predictions at 12km grid resolution of smoke at the surface and in the column are provided each day by 13 UTC, extending through midnight next day. Forecast accuracy and reliability are monitored against benchmark criteria for accuracy and reliability. While wildfire activity in the CONUS is year-round, the intense wildfire activity in AK is limited to the summer. Initial experimental testing during summer 2008 was hindered by unusually limited wildfire activity and very cloudy conditions. In contrast, heavier than average wildfire activity during summer 2009 provided a representative basis (more than 60 days of wildfire smoke) for demonstrating required prediction accuracy. A new satellite observation product was developed for routine near-real time verification of these predictions. The footprint of the predicted smoke from identified fires is verified with satellite observations of the spatial extent of smoke aerosols (5km resolution). Based on geostationary aerosol optical depth measurements that provide good time resolution of the horizontal spatial extent of the plumes, these observations do not yield quantitative concentrations of smoke particles at the surface. Predicted surface smoke concentrations are consistent with the limited number of in situ observations of total fine particle mass from all sources; however they are much higher than predicted for most CONUS fires. To assess uncertainty associated with fire emissions estimates, sensitivity analyses are in progress.

Informing policy makers about future health spending: a comparative analysis of forecasting methods in OECD countries.

PubMed

Astolfi, Roberto; Lorenzoni, Luca; Oderkirk, Jillian

2012-09-01

Concerns about health care expenditure growth and its long-term sustainability have risen to the top of the policy agenda in many OECD countries. As continued growth in spending places pressure on government budgets, health services provision and patients' personal finances, policy makers have launched forecasting projects to support policy planning. This comparative analysis reviewed 25 models that were developed for policy analysis in OECD countries by governments, research agencies, academics and international organisations. We observed that the policy questions that need to be addressed drive the choice of forecasting model and the model's specification. By considering both the level of aggregation of the units analysed and the level of detail of health expenditure to be projected, we identified three classes of models: micro, component-based, and macro. Virtually all models account for demographic shifts in the population, while two important influences on health expenditure growth that are the least understood include technological innovation and health-seeking behaviour. The landscape for health forecasting models is dynamic and evolving. Advances in computing technology and increases in data granularity are opening up new possibilities for the generation of system of models which become an on-going decision support tool capable of adapting to new questions as they arise. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Evidence of dilute ferromagnetism in rare-earth doped yttrium aluminium garnet

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

Farr, Warrick G.; Goryachev, Maxim; Le Floch, Jean-Michel

This work demonstrates strong coupling regime between an erbium ion spin ensemble and microwave hybrid cavity-whispering gallery modes in a yttrium aluminium garnet dielectric crystal. Coupling strengths of 220 MHz and mode quality factors in excess of 10{sup 6} are demonstrated. Moreover, the magnetic response of high-Q modes demonstrates behaviour which is unusual for paramagnetic systems. This behaviour includes hysteresis and memory effects. Such qualitative change of the system's magnetic field response is interpreted as a phase transition of rare earth ion impurities. This phenomenon is similar to the phenomenon of dilute ferromagnetism in semiconductors. The clear temperature dependence of themore » phenomenon is demonstrated.« less

Cataract in a patient with 47,XYY sex chromosome aneuploidy.

PubMed

Medina-Andrade, A; Villanueva-Mendoza, C; Arenas, S; Cortés-González, V

2018-06-01

The case concerns a 16 year-old boy with a history of high myopia and unilateral congenital cataract, tall stature for age, facial dysmorphism, hypermobile metacarpal-phalangeal joints, as well as behavioural problems. The mother had a history of recurrent pregnancy loss. Chromosomal analysis of the peripheral blood lymphocytes reported 47,XYY. Patients with sex chromosome aneuploidy 47,XYY have higher risk of congenital malformations, although ophthalmological anomalies are unusual. Evaluation of patients with tall stature and behavioural problems should include a chromosomal analysis in order to determine the aetiology. Copyright © 2017 Sociedad Española de Oftalmología. Publicado por Elsevier España, S.L.U. All rights reserved.

Nonlinear microwave response of an MgB2 thin film

NASA Astrophysics Data System (ADS)

Purnell, A. J.; Cohen, L. F.; Zhai, H. Y.; Christen, H. M.; Paranthaman, M. P.; Lowndes, D. H.; Hao, Ling; Gallop, J. C.

2004-04-01

MgB2 is a two-gap superconductor and as a result may manifest unusual physical properties. The performance of MgB2 films at microwave frequencies has so far been rather poor compared to that of Nb alloys and this may result from intrinsic behaviour related to the double-gap structure or extrinsic properties due to non-optimized thin films. Here we give a detailed report on the microwave magnetic field dependent surface impedance of an MgB2 thin film, using a parallel plate resonator, as a function of temperature. We discuss whether the framework used to analyse nonlinear behaviour for other superconductors, both low and high Tc, but single-gap, has any validity for MgB2 and whether the films are limited by intrinsic or extrinsic behaviour. The key result is the observation of junction-type switching effects at high microwave power.

Starvation-Induced Dietary Behaviour in Drosophila melanogaster Larvae and Adults

PubMed Central

Ahmad, Muhammad; Chaudhary, Safee Ullah; Afzal, Ahmed Jawaad; Tariq, Muhammad

2015-01-01

Drosophila melanogaster larvae are classified as herbivores and known to feed on non-carnivorous diet under normal conditions. However, when nutritionally challenged these larvae exhibit cannibalistic behaviour by consuming a diet composed of larger conspecifics. Herein, we report that cannibalism in Drosophila larvae is confined not only to scavenging on conspecifics that are larger in size, but also on their eggs. Moreover, such cannibalistic larvae develop as normally as those grown on standard cornmeal medium. When stressed, Drosophila melanogaster larvae can also consume a carnivorous diet derived from carcasses of organisms belonging to diverse taxonomic groups, including Musca domestica, Apis mellifera, and Lycosidae sp. While adults are ill-equipped to devour conspecific carcasses, they selectively oviposit on them and also consume damaged cadavers of conspecifics. Thus, our results suggest that nutritionally stressed Drosophila show distinct as well as unusual feeding behaviours that can be classified as detritivorous, cannibalistic and/or carnivorous. PMID:26399327

Starvation-Induced Dietary Behaviour in Drosophila melanogaster Larvae and Adults.

PubMed

Ahmad, Muhammad; Chaudhary, Safee Ullah; Afzal, Ahmed Jawaad; Tariq, Muhammad

2015-09-24

Drosophila melanogaster larvae are classified as herbivores and known to feed on non-carnivorous diet under normal conditions. However, when nutritionally challenged these larvae exhibit cannibalistic behaviour by consuming a diet composed of larger conspecifics. Herein, we report that cannibalism in Drosophila larvae is confined not only to scavenging on conspecifics that are larger in size, but also on their eggs. Moreover, such cannibalistic larvae develop as normally as those grown on standard cornmeal medium. When stressed, Drosophila melanogaster larvae can also consume a carnivorous diet derived from carcasses of organisms belonging to diverse taxonomic groups, including Musca domestica, Apis mellifera, and Lycosidae sp. While adults are ill-equipped to devour conspecific carcasses, they selectively oviposit on them and also consume damaged cadavers of conspecifics. Thus, our results suggest that nutritionally stressed Drosophila show distinct as well as unusual feeding behaviours that can be classified as detritivorous, cannibalistic and/or carnivorous.

Afterslip behavior following the M6.0, 2014 South Napa earthquake with implications for afterslip forecasting on other seismogenic faults

USGS Publications Warehouse

Lienkaemper, James J.; DeLong, Stephen B.; Domrose, Carolyn J; Rosa, Carla M.

2016-01-01

The M6.0, 24 Aug. 2014 South Napa, California, earthquake exhibited unusually large slip for a California strike-slip event of its size with a maximum coseismic surface slip of 40-50 cm in the north section of the 15 km-long rupture. Although only minor (<10 cm) surface slip occurred coseismically in the southern 9-km section of the rupture, there was considerable postseismic slip, so that the maximum total slip one year after the event approached 40-50 cm, about equal to the coseismic maximum in the north. We measured the accumulation of postseismic surface slip on four, ~100-m-long alignment arrays for one year following the event. Because prolonged afterslip can delay reconstruction of fault-damaged buildings and infrastructure, we analyzed its gradual decay to estimate when significant afterslip would likely end. This forecasting of Napa afterslip suggests how we might approach the scientific and engineering challenges of afterslip from a much larger M~7 earthquake anticipated on the nearby, urban Hayward Fault. However, we expect its afterslip to last much longer than one year.The M6.0, 24 Aug. 2014 South Napa, California, earthquake exhibited unusually large slip for a California strike-slip event of its size with a maximum coseismic surface slip of 40-50 cm in the north section of the 15 km-long rupture. Although only minor (<10 cm) surface slip occurred coseismically in the southern 9-km section of the rupture, there was considerable postseismic slip, so that the maximum total slip one year after the event approached 40-50 cm, about equal to the coseismic maximum in the north. We measured the accumulation of postseismic surface slip on four, ~100-m-long alignment arrays for one year following the event. Because prolonged afterslip can delay reconstruction of fault-damaged buildings and infrastructure, we analyzed its gradual decay to estimate when significant afterslip would likely end. This forecasting of Napa afterslip suggests how we might approach the scientific and engineering challenges of afterslip from a much larger M~7 earthquake anticipated on the nearby, urban Hayward Fault. However, we expect its afterslip to last much longer than one year.

Information Theory Broadens the Spectrum of Molecular Ecology and Evolution.

PubMed

Sherwin, W B; Chao, A; Jost, L; Smouse, P E

2017-12-01

Information or entropy analysis of diversity is used extensively in community ecology, and has recently been exploited for prediction and analysis in molecular ecology and evolution. Information measures belong to a spectrum (or q profile) of measures whose contrasting properties provide a rich summary of diversity, including allelic richness (q=0), Shannon information (q=1), and heterozygosity (q=2). We present the merits of information measures for describing and forecasting molecular variation within and among groups, comparing forecasts with data, and evaluating underlying processes such as dispersal. Importantly, information measures directly link causal processes and divergence outcomes, have straightforward relationship to allele frequency differences (including monotonicity that q=2 lacks), and show additivity across hierarchical layers such as ecology, behaviour, cellular processes, and nongenetic inheritance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Habitat use and diving behaviour of gravid olive ridley sea turtles under riverine conditions in French Guiana

NASA Astrophysics Data System (ADS)

Chambault, Philippine; Giraudou, Lucie; de Thoisy, Benoît; Bonola, Marc; Kelle, Laurent; Reis, Virginie Dos; Blanchard, Fabian; Le Maho, Yvon; Chevallier, Damien

2017-01-01

The identification of the inter-nesting habitat used by gravid sea turtles has become a crucial factor in their protection. Their aggregation in large groups of individuals during the inter-nesting period exposes them to increased threats to their survival - particularly along the French Guiana shield, where intense legal and illegal fisheries occur. Among the three sea turtle species nesting in French Guiana, the olive ridley appears to have the most generalist diet, showing strong behavioural plasticity according to the environment encountered. The large amounts of sediments that are continuously discharged by the Amazon River create a very unusual habitat for olive ridleys, i.e. turbid waters with low salinity. This study assesses the behavioural adjustments of 20 adult female olive ridleys under such riverine conditions. Individuals were tracked by satellite from Remire-Montjoly rookery in French Guiana using tags that recorded the location and diving parameters of individuals, as well as the immediate environment of the turtles including the in situ temperature and salinity. Data concerning potential preys was provided via collection of epifauna by a trawler. Multiple behavioural shifts were observed in both horizontal and vertical dimensions. During the first half of the inter-nesting season, the turtles moved away from the nesting beach (21.9 ± 24.7 km), performing deeper (12.6 ± 7.4 m) and longer (29.7 ± 21.0 min) dives than during the second half of the period (7.4 ± 7.8 km, 10.4 ± 4.9 m and 25.9 ± 19.3 min). Olive ridleys remained in waters that were warm (range: 26-33 °C) and which fluctuated in terms of salinity (range: 19.5-36.4 psu), in a relatively small estuarine habitat covering 423 km2. If olive ridleys were foraging during this period, the potential preys that might be available were mostly crustaceans (43%) and fish (39%), as expected for the diet of this generalist species during this period. This study highlights the numerous behavioural adaptations of this species in response to the unusual riverine conditions of the French Guiana continental shelf.

Near-surface wind speed statistical distribution: comparison between ECMWF System 4 and ERA-Interim

NASA Astrophysics Data System (ADS)

Marcos, Raül; Gonzalez-Reviriego, Nube; Torralba, Verónica; Cortesi, Nicola; Young, Doo; Doblas-Reyes, Francisco J.

2017-04-01

In the framework of seasonal forecast verification, knowing whether the characteristics of the climatological wind speed distribution, simulated by the forecasting systems, are similar to the observed ones is essential to guide the subsequent process of bias adjustment. To bring some light about this topic, this work assesses the properties of the statistical distributions of 10m wind speed from both ERA-Interim reanalysis and seasonal forecasts of ECMWF system 4. The 10m wind speed distribution has been characterized in terms of the four main moments of the probability distribution (mean, standard deviation, skewness and kurtosis) together with the coefficient of variation and goodness of fit Shapiro-Wilks test, allowing the identification of regions with higher wind variability and non-Gaussian behaviour at monthly time-scales. Also, the comparison of the predicted and observed 10m wind speed distributions has been measured considering both inter-annual and intra-seasonal variability. Such a comparison is important in both climate research and climate services communities because it provides useful climate information for decision-making processes and wind industry applications.

Application of The Rainfall-runoff Model Topkapi For The Entire Basin of The Po River As Part of The European Project Effs

NASA Astrophysics Data System (ADS)

Todini, E.; Bartholmes, J.

The project EFFS (European Flood Forecasting System) aims at developing a flood forecasting system for the major river basins all over Europe. To extend the forecast- ing and thus the warning time in a significant way (up to 10 days) meteorological forecasting data from the ECMWF will be used as input to hydrological models. For this purpose it is fundamental to have a reliable rainfall-runoff model. For the river Po basin we chose the TOPKAPI model (Ciarapica, Todini 1998). TOPKAPI is a physi- cally based rainfall-runoff model that maintains its physical significance passing from hillslope to large basin scale. The aim of the distributed version is to reproduce the spatial variability and to lead to a better understanding of scaling effects on meteo- rological data used as well as of physical phenomena and parameters. By now the TOPKAPI model has been applied successfully to basins of smaller and medium size (up to 8000 km2). The present work also proves that TOPKAPI is a valuable flood forecasting tool for larger basins such as the Po river. An advantage of the TOPKAPI model is its physical basis. It doesn't need a "real" calibration in the common sense of the expression. The calibration work that has to be done is due to the unavoidable averaging and approximation in the input data representing various phenomena. This reduces the calibration work as well as the length of data required. The model was implemented on the Po river at spatial steps of 1km and time steps of 1 hour using available data during the year 1994. After the calibration phase, mesoscale forecasts (from ECMWF) as well as forecasts of LAM models (DWD,DMI) will be used as input to the Po river models and their behaviour will be studied as a function of the prediction quality and of the coarseness of the spatial discretisation.

Do bowerbirds exhibit cultures?

PubMed

Madden, Joah R

2008-01-01

Definitions of what features constitute cultural behaviour, and hence define cultures are numerous. Many seem designed to describe those aspects of human behaviour which set us apart from other animals. A broad definition prescribing that the behaviour is: learned; learned socially; normative and collective is considered to apply to several species of great ape. In this paper, I review observations and experiments covering a suite of different behavioural characteristics displayed in members of the bowerbird family (Ptilonorhynchidae) and ask whether they fulfil these criteria. These include vocalisations, bower design, decoration use, bower orientation and display movements. Such a range of behaviours refutes the suggestion that these species are "one-trick ponies"--a criticism that is often levelled at claims for culture in non-primate species. I suggest that, despite a paucity of data in comparison with primate studies, it could be argued that bowerbirds may be considered to fulfil the same criteria on which we base our use of the term culture when applied to our close relatives, the great apes. If bowerbirds do have cultures, then their unusual natural history makes them a highly tractable system in which questions of social learning and culture can be tackled.

An industry perspective on the use of seasonal forecasts and weather information for evaluating sensitivities in traded commodity supply chains

NASA Astrophysics Data System (ADS)

Domeisen, Daniela; Slavov, Georgi

2015-04-01

Weather information on seasonal timescales is crucial to various end users, from the level of subsistence farming to the government level. Also the financial industry is ever more aware of and interested in the benefits that early and correctly interpreted forecast information provides. Straight forward and often cited applications include the estimation of rainfall and temperature anomalies for drought - prone agricultural areas producing traded commodities, as well as some of the rather direct impacts of weather on energy production. Governments, weather services, as well as both academia and private companies are working on tailoring climate and weather information to a growing number of customers. However, also other large markets, such as coal, iron ore, and gas, are crucially dependent on seasonal weather information and forecasts, while the needs are again very dependent on the direction of the predicted signal. So far, relatively few providers in climate services address these industries. All of these commodities show a strong seasonal and weather dependence, and an unusual winter or summer can crucially impact their demand and supply. To name a few impacts, gas is crucially driven by heating demand, iron ore excavation is dependent on the available water resources, and coal mining is dependent on winter temperatures and rainfall. This contribution will illustrate and provide an inside view of the type of climate and weather information needed for the various large commodity industries.

Forecasting European Droughts using the North American Multi-Model Ensemble (NMME)

NASA Astrophysics Data System (ADS)

Thober, Stephan; Kumar, Rohini; Samaniego, Luis; Sheffield, Justin; Schäfer, David; Mai, Juliane

2015-04-01

Soil moisture droughts have the potential to diminish crop yields causing economic damage or even threatening the livelihood of societies. State-of-the-art drought forecasting systems incorporate seasonal meteorological forecasts to estimate future drought conditions. Meteorological forecasting skill (in particular that of precipitation), however, is limited to a few weeks because of the chaotic behaviour of the atmosphere. One of the most important challenges in drought forecasting is to understand how the uncertainty in the atmospheric forcings (e.g., precipitation and temperature) is further propagated into hydrologic variables such as soil moisture. The North American Multi-Model Ensemble (NMME) provides the latest collection of a multi-institutional seasonal forecasting ensemble for precipitation and temperature. In this study, we analyse the skill of NMME forecasts for predicting European drought events. The monthly NMME forecasts are downscaled to daily values to force the mesoscale hydrological model (mHM). The mHM soil moisture forecasts obtained with the forcings of the dynamical models are then compared against those obtained with the Ensemble Streamflow Prediction (ESP) approach. ESP recombines historical meteorological forcings to create a new ensemble forecast. Both forecasts are compared against reference soil moisture conditions obtained using observation based meteorological forcings. The study is conducted for the period from 1982 to 2009 and covers a large part of the Pan-European domain (10°W to 40°E and 35°N to 55°N). Results indicate that NMME forecasts are better at predicting the reference soil moisture variability as compared to ESP. For example, NMME explains 50% of the variability in contrast to only 31% by ESP at a six-month lead time. The Equitable Threat Skill Score (ETS), which combines the hit and false alarm rates, is analysed for drought events using a 0.2 threshold of a soil moisture percentile index. On average, the NMME based ensemble forecasts have consistently higher skill than the ESP based ones (ETS of 13% as compared to 5% at a six-month lead time). Additionally, the ETS ensemble spread of NMME forecasts is considerably narrower than that of ESP; the lower boundary of the NMME ensemble spread coincides most of the time with the ensemble median of ESP. Among the NMME models, NCEP-CFSv2 outperforms the other models in terms of ETS most of the time. Removing the three worst performing models does not deteriorate the ensemble performance (neither in skill nor in spread), but would substantially reduce the computational resources required in an operational forecasting system. For major European drought events (e.g., 1990, 1992, 2003, and 2007), NMME forecasts tend to underestimate area under drought and drought magnitude during times of drought development. During drought recovery, this underestimation is weaker for area under drought or even reversed into an overestimation for drought magnitude. This indicates that the NMME models are too wet during drought development and too dry during drought recovery. In summary, soil moisture drought forecasts by NMME are more skillful than those of an ESP based approach. However, they still show systematic biases in reproducing the observed drought dynamics during drought development and recovery.

Influence of safety motivation and climate on safety behaviour and outcomes: evidence from the Saudi Arabian construction industry.

PubMed

Panuwatwanich, Kriengsak; Al-Haadir, Saeed; Stewart, Rodney A

2017-03-01

Over the last three decades, safety literature has focused on safety climate and its role in forecasting injuries and accidents. However, research findings regarding the relationships between safety climate and other key outcome constructs are somewhat inconsistent. Recent safety climate literature suggests that examining the role of safety motivation may help provide a better explanation of such relationships. The research presented in this article aimed to empirically analyse the relationships among safety motivation, safety climate, safety behaviour and safety outcomes within the context of the Saudi Arabian construction industry. A conceptual model was developed to examine the relationships among four main constructs: safety motivation, safety climate, safety behaviour and safety outcomes. Based on the survey data collected in Saudi Arabia from site engineers and project managers (n = 295), statistical analyses were carried out, including confirmatory and exploratory factor analysis, and structural equation modelling to assess the model and test the hypotheses. The main results indicated that safety motivation could positively influence safety behaviour through safety climate, which plays a mediating role for this mechanism. The results also confirmed that safety behaviour could predict safety outcomes within the context of the Saudi Arabian construction industry.

Reversible dilatancy in entangled single-wire materials.

PubMed

Rodney, David; Gadot, Benjamin; Martinez, Oriol Riu; du Roscoat, Sabine Rolland; Orgéas, Laurent

2016-01-01

Designing structures that dilate rapidly in both tension and compression would benefit devices such as smart filters, actuators or fasteners. This property however requires an unusual Poisson ratio, or Poisson function at finite strains, which has to vary with applied strain and exceed the familiar bounds: less than 0 in tension and above 1/2 in compression. Here, by combining mechanical tests and discrete element simulations, we show that a simple three-dimensional architected material, made of a self-entangled single long coiled wire, behaves in between discrete and continuum media, with a large and reversible dilatancy in both tension and compression. This unusual behaviour arises from an interplay between the elongation of the coiled wire and rearrangements due to steric effects, which, unlike in traditional discrete media, are hysteretically reversible when the architecture is made of an elastic fibre.

Behavioural responses of the yellow emitting annelid Tomopteris helgolandica to photic stimuli.

PubMed

Gouveneaux, Anaïd; Gielen, Marie-Charlotte; Mallefet, Jérôme

2018-05-01

In contrast to most mesopelagic bioluminescent organisms specialised in the emission and reception of blue light, the planktonic annelid Tomopteris helgolandica produces yellow light. This unusual feature has long been suggested to serve for intraspecific communication. Yet, this virtually admitted hypothesis has never been tested. In this behavioural study of spectral colour sensitivity, we first present an illustrated repertoire of the postures and action patterns described by captive specimens. Then video tracking and motion analysis are used to quantify the behavioural responses of singled out worms to photic stimuli imitating intraspecific (yellow) or interspecific (blue) bioluminescent signals. We show the ability of T. helgolandica to react and to contrast its responses to bioluminescent-like blue and yellow light signals. In particular, the attractive effect of yellow light and the variation of angular velocity observed according to the pattern of yellow stimuli (flashes versus glows) support the intraspecific communication hypothesis. However, given the behavioural patterns of T. helgolandica, including mechanically induced light emission, the possibility that bioluminescence may be part of escape/defence responses to predation, should remain an open question. Copyright © 2018 John Wiley & Sons, Ltd.

An unanticipated cardiac arrest and unusual post-resuscitation psycho-behavioural phenomena/near death experience in a patient with pregnancy induced hypertension and twin pregnancy undergoing elective lower segment caesarean section.

PubMed

Panditrao, Mridul M; Singh, Chanchal; Panditrao, Minnu M

2010-09-01

A case report of a primigravida, who was admitted with severe pregnancy induced hypertension (BP 160/122 mmHg) and twin pregnancy, is presented here. Antihypertensive therapy was initiated. Elective LSCS under general anaesthesia was planned. After the birth of both the babies, intramyometrial injections of Carboprost and Pitocin were administered. Immediately, she suffered cardiac arrest. Cardio pulmonary resucitation (CPR) was started and within 3 minutes, she was successfully resuscitated. The patient initially showed peculiar psychological changes and with passage of time, certain psycho-behavioural patterns emerged which could be attributed to near death experiences, as described in this case report.

On the validity of cosmological Fisher matrix forecasts

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

Wolz, Laura; Kilbinger, Martin; Weller, Jochen

2012-09-01

We present a comparison of Fisher matrix forecasts for cosmological probes with Monte Carlo Markov Chain (MCMC) posterior likelihood estimation methods. We analyse the performance of future Dark Energy Task Force (DETF) stage-III and stage-IV dark-energy surveys using supernovae, baryon acoustic oscillations and weak lensing as probes. We concentrate in particular on the dark-energy equation of state parameters w{sub 0} and w{sub a}. For purely geometrical probes, and especially when marginalising over w{sub a}, we find considerable disagreement between the two methods, since in this case the Fisher matrix can not reproduce the highly non-elliptical shape of the likelihood function.more » More quantitatively, the Fisher method underestimates the marginalized errors for purely geometrical probes between 30%-70%. For cases including structure formation such as weak lensing, we find that the posterior probability contours from the Fisher matrix estimation are in good agreement with the MCMC contours and the forecasted errors only changing on the 5% level. We then explore non-linear transformations resulting in physically-motivated parameters and investigate whether these parameterisations exhibit a Gaussian behaviour. We conclude that for the purely geometrical probes and, more generally, in cases where it is not known whether the likelihood is close to Gaussian, the Fisher matrix is not the appropriate tool to produce reliable forecasts.« less

Fitting mechanistic epidemic models to data: A comparison of simple Markov chain Monte Carlo approaches.

PubMed

Li, Michael; Dushoff, Jonathan; Bolker, Benjamin M

2018-07-01

Simple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical frameworks in these contexts. Here we build a simple stochastic, discrete-time, discrete-state epidemic model with both process and observation error and use it to characterize the effectiveness of different flavours of Bayesian Markov chain Monte Carlo (MCMC) techniques. We use fits to simulated data, where parameters (and future behaviour) are known, to explore the limitations of different platforms and quantify parameter estimation accuracy, forecasting accuracy, and computational efficiency across combinations of modeling decisions (e.g. discrete vs. continuous latent states, levels of stochasticity) and computational platforms (JAGS, NIMBLE, Stan).

Real-Time Diffusion of Information on Twitter and the Financial Markets

PubMed Central

Tafti, Ali; Zotti, Ryan; Jank, Wolfgang

2016-01-01

Do spikes in Twitter chatter about a firm precede unusual stock market trading activity for that firm? If so, Twitter activity may provide useful information about impending financial market activity in real-time. We study the real-time relationship between chatter on Twitter and the stock trading volume of 96 firms listed on the Nasdaq 100, during 193 days of trading in the period from May 21, 2012 to September 18, 2013. We identify observations featuring firm-specific spikes in Twitter activity, and randomly assign each observation to a ten-minute increment matching on the firm and a number of repeating time indicators. We examine the extent that unusual levels of chatter on Twitter about a firm portend an oncoming surge of trading of its stock within the hour, over and above what would normally be expected for the stock for that time of day and day of week. We also compare the findings from our explanatory model to the predictive power of Tweets. Although we find a compelling and potentially informative real-time relationship between Twitter activity and trading volume, our forecasting exercise highlights how difficult it can be to make use of this information for monetary gain. PMID:27504639

Real-Time Diffusion of Information on Twitter and the Financial Markets.

PubMed

Tafti, Ali; Zotti, Ryan; Jank, Wolfgang

2016-01-01

Do spikes in Twitter chatter about a firm precede unusual stock market trading activity for that firm? If so, Twitter activity may provide useful information about impending financial market activity in real-time. We study the real-time relationship between chatter on Twitter and the stock trading volume of 96 firms listed on the Nasdaq 100, during 193 days of trading in the period from May 21, 2012 to September 18, 2013. We identify observations featuring firm-specific spikes in Twitter activity, and randomly assign each observation to a ten-minute increment matching on the firm and a number of repeating time indicators. We examine the extent that unusual levels of chatter on Twitter about a firm portend an oncoming surge of trading of its stock within the hour, over and above what would normally be expected for the stock for that time of day and day of week. We also compare the findings from our explanatory model to the predictive power of Tweets. Although we find a compelling and potentially informative real-time relationship between Twitter activity and trading volume, our forecasting exercise highlights how difficult it can be to make use of this information for monetary gain.

A radon-thoron isotope pair as a reliable earthquake precursor

PubMed Central

Hwa Oh, Yong; Kim, Guebuem

2015-01-01

Abnormal increases in radon (222Rn, half-life = 3.82 days) activity have occasionally been observed in underground environments before major earthquakes. However, 222Rn alone could not be used to forecast earthquakes since it can also be increased due to diffusive inputs over its lifetime. Here, we show that a very short-lived isotope, thoron (220Rn, half-life = 55.6 s; mean life = 80 s), in a cave can record earthquake signals without interference from other environmental effects. We monitored 220Rn together with 222Rn in air of a limestone-cave in Korea for one year. Unusually large 220Rn peaks were observed only in February 2011, preceding the 2011 M9.0 Tohoku-Oki Earthquake, Japan, while large 222Rn peaks were observed in both February 2011 and the summer. Based on our analyses, we suggest that the anomalous peaks of 222Rn and 220Rn activities observed in February were precursory signals related to the Tohoku-Oki Earthquake. Thus, the 220Rn-222Rn combined isotope pair method can present new opportunities for earthquake forecasting if the technique is extensively employed in earthquake monitoring networks around the world. PMID:26269105

Animal behaviour shapes the ecological effects of ocean acidification and warming: moving from individual to community-level responses.

PubMed

Nagelkerken, Ivan; Munday, Philip L

2016-03-01

Biological communities are shaped by complex interactions between organisms and their environment as well as interactions with other species. Humans are rapidly changing the marine environment through increasing greenhouse gas emissions, resulting in ocean warming and acidification. The first response by animals to environmental change is predominantly through modification of their behaviour, which in turn affects species interactions and ecological processes. Yet, many climate change studies ignore animal behaviour. Furthermore, our current knowledge of how global change alters animal behaviour is mostly restricted to single species, life phases and stressors, leading to an incomplete view of how coinciding climate stressors can affect the ecological interactions that structure biological communities. Here, we first review studies on the effects of warming and acidification on the behaviour of marine animals. We demonstrate how pervasive the effects of global change are on a wide range of critical behaviours that determine the persistence of species and their success in ecological communities. We then evaluate several approaches to studying the ecological effects of warming and acidification, and identify knowledge gaps that need to be filled, to better understand how global change will affect marine populations and communities through altered animal behaviours. Our review provides a synthesis of the far-reaching consequences that behavioural changes could have for marine ecosystems in a rapidly changing environment. Without considering the pervasive effects of climate change on animal behaviour we will limit our ability to forecast the impacts of ocean change and provide insights that can aid management strategies. © 2015 John Wiley & Sons Ltd.

Carbon nanotube dry adhesives with temperature-enhanced adhesion over a large temperature range.

PubMed

Xu, Ming; Du, Feng; Ganguli, Sabyasachi; Roy, Ajit; Dai, Liming

2016-11-16

Conventional adhesives show a decrease in the adhesion force with increasing temperature due to thermally induced viscoelastic thinning and/or structural decomposition. Here, we report the counter-intuitive behaviour of carbon nanotube (CNT) dry adhesives that show a temperature-enhanced adhesion strength by over six-fold up to 143 N cm -2 (4 mm × 4 mm), among the strongest pure CNT dry adhesives, over a temperature range from -196 to 1,000 °C. This unusual adhesion behaviour leads to temperature-enhanced electrical and thermal transports, enabling the CNT dry adhesive for efficient electrical and thermal management when being used as a conductive double-sided sticky tape. With its intrinsic thermal stability, our CNT adhesive sustains many temperature transition cycles over a wide operation temperature range. We discover that a 'nano-interlock' adhesion mechanism is responsible for the adhesion behaviour, which could be applied to the development of various dry CNT adhesives with novel features.

Seven 365-Million-Year-Old Trilobites Moulting within a Nautiloid Conch

NASA Astrophysics Data System (ADS)

Zong, Rui-Wen; Fan, Ruo-Ying; Gong, Yi-Ming

2016-10-01

A nautiloid conch containing many disarticulated exoskeletons of Omegops cornelius (Phacopidae, Trilobita) was found in the Upper Devonian Hongguleleng Formation of the northwestern margin of the Junggar Basin, NW China. The similar number of cephala, thoraces and pygidia, unbroken thoraces, explicit exuviae, and lack of other macrofossils in the conch, indicate that at least seven individual trilobites had moulted within the nautiloid living chamber, using the vacant chamber of a dead nautiloid as a communal place for ecdysis. This exuvial strategy manifests cryptic behaviour of trilobites, which may have resulted from the adaptive evolution induced by powerful predation pressure, unstable marine environments, and competition pressure of organisms occupying the same ecological niche in the Devonian period. The unusual presence of several trilobites moulting within a nautiloid conch is possibly associated with social behaviours in face of a serious crisis. New materials in this study open a window for understanding the survival strategy of marine benthic organisms, especially predator-prey interactions and the behavioural ecology of trilobites in the middle Palaeozoic.

Pre-orbital gland opening during aggressive interactions in rusa deer (Rusa timorensis).

PubMed

Ceacero, Francisco; Pluháček, Jan; Komárková, Martina; Zábranský, Martin

2015-02-01

The opening of the preorbital gland in cervids has a visual meaning and is frequently associated with agonistic and/or stress related situations. Apart from in red deer, this behaviour has scarcely been studied and the range of situations when it may occur remains unclear. In this study we report the unusual case of preorbital gland opening in rusa deer, Rusa timorensis, associated to direct aggressive agonistic interaction (biting/kicking) between two adult hinds. This case observed in Tierpark Berlin (Germany) is the first one ever recorded in female-female interactions in cervids. Preorbital gland opening was also studied in 116 social interactions in Plzeň Zoo (Czech Republic). Preorbital gland opening by the dominant adult male was twice observed with relation to alert behaviour, which is also rare. In order to contextualise our observations we summarise the current knowledge about the behaviour associated with preorbital gland opening in R. timorensis and in cervids in general. Copyright © 2014 Elsevier B.V. All rights reserved.

A randomised study of leadership interventions for healthcare managers.

PubMed

Lornudd, Caroline; Bergman, David; Sandahl, Christer; von Thiele Schwarz, Ulrica

2016-10-03

Purpose The purpose of this paper was to assess two different leader development interventions by comparing their effects on leadership behaviour and evaluating their combined impact after two years, from the viewpoints of both the participating managers and external raters. Design/methodology/approach The study was a longitudinal randomised controlled trial with a cross-over design. Health care managers ( n = 177) were first randomised to either of two 10-month interventions and a year later were switched to the other intervention. Leadership behaviour was rated at pre-test and 12 and 24 months by participating managers and their superiors, colleagues and subordinates using a 360-degree instrument. Analysis of variance and multilevel regression analysis was performed. Findings No difference in effect on leadership behaviour was found between the two interventions. The evaluation of the combined effect of the interventions on leadership behaviour showed inconsistent (i.e. both increased and decreased) ratings by the various rater sources. Practical implications This study provides some evidence that participation in leadership development programmes can improve managers' leadership behaviours, but the results also highlight the interpretive challenges connected with using a 360-degree instrument to evaluate such development. Originality/value The longitudinal randomised controlled design and the large sample comprising both managers and external raters make this study unusually rigorous in the field of leadership development evaluations.

Development of Hydrological Model of Klang River Valley for flood forecasting

NASA Astrophysics Data System (ADS)

Mohammad, M.; Andras, B.

2012-12-01

This study is to review the impact of climate change and land used on flooding through the Klang River and to compare the changes in the existing river system in Klang River Basin with the Storm water Management and Road Tunnel (SMART) which is now already operating in the city centre of Kuala Lumpur. Klang River Basin is the most urbanized region in Malaysia. More than half of the basin has been urbanized on the land that is prone to flooding. Numerous flood mitigation projects and studies have been carried out to enhance the existing flood forecasting and mitigation project. The objective of this study is to develop a hydrological model for flood forecasting in Klang Basin Malaysia. Hydrological modelling generally requires large set of input data and this is more often a challenge for a developing country. Due to this limitation, the Tropical Rainfall Measuring Mission (TRMM) rainfall measurement, initiated by the US space agency NASA and Japanese space agency JAXA was used in this study. TRMM data was transformed and corrected by quantile to quantile transformation. However, transforming the data based on ground measurement doesn't make any significant improvement and the statistical comparison shows only 10% difference. The conceptual HYMOD model was used in this study and calibrated using ROPE algorithm. But, using the whole time series of the observation period in this area resulted in insufficient performance. The depth function which used in ROPE algorithm are then used to identified and calibrated using only unusual event to observed the improvement and efficiency of the model.

Is incest harmful?

PubMed

Henderson, J

1983-02-01

Classically, incest has been considered from both a psychological and sociological point of view to have harmful consequences. Genetic research, though by no means lacking controversy of its own, generally supports the notion that inbreeding has untoward genetic consequences. The psychodynamics of all three parties to father-daughter incest seem to indicate that people who become involved in incestuous behaviour are often psychologically damaged before the fact, so that if they show subsequent evidence of psychological impairment the incestuous behaviour can be as plausibly viewed as a dysfunctional attempt at solving problems as it can a cause of subsequent psychopathology. Girls involved in the father-daughter incest present in one of half a dozen frequent clinical syndromes. The presentation is influenced by the degree to which the girl may have participated in ongoing incestuous behaviour as opposed to being the presumed victim of an older adult's coercive actions or her own temporary suspension of a behavioural taboo. Research is inconclusive as to the psychological harmfulness of incestuous behaviour, and evidence is reviewed on both sides of this complicated and controversial question. Quite apart from the general issue of the harmfulness of incest, a number of indicators can be derived from the nature of the incestuous episode and the early response to therapeutic assessment which aid in the clinical forecasting of probable outcome.

Development of the Mathematical Model for Ingot Quality Forecasting with Consideration of Thermal and Physical Characteristics of Mould Powder

NASA Astrophysics Data System (ADS)

Anisimov, K. N.; Loginov, A. M.; Gusev, M. P.; Zarubin, S. V.; Nikonov, S. V.; Krasnov, A. V.

2017-12-01

This paper presents the results of physical modelling of the mould powder skull in the gap between an ingot and the mould. Based on the results obtained from this and previous works, the mathematical model of mould powder behaviour in the gap and its influence on formation of surface defects was developed. The results of modelling satisfactorily conform to the industrial data on ingot surface defects.

Predicting financial market crashes using ghost singularities.

PubMed

Smug, Damian; Ashwin, Peter; Sornette, Didier

2018-01-01

We analyse the behaviour of a non-linear model of coupled stock and bond prices exhibiting periodically collapsing bubbles. By using the formalism of dynamical system theory, we explain what drives the bubbles and how foreshocks or aftershocks are generated. A dynamical phase space representation of that system coupled with standard multiplicative noise rationalises the log-periodic power law singularity pattern documented in many historical financial bubbles. The notion of 'ghosts of finite-time singularities' is introduced and used to estimate the end of an evolving bubble, using finite-time singularities of an approximate normal form near the bifurcation point. We test the forecasting skill of this method on different stochastic price realisations and compare with Monte Carlo simulations of the full system. Remarkably, the approximate normal form is significantly more precise and less biased. Moreover, the method of ghosts of singularities is less sensitive to the noise realisation, thus providing more robust forecasts.

Predicting financial market crashes using ghost singularities

PubMed Central

2018-01-01

We analyse the behaviour of a non-linear model of coupled stock and bond prices exhibiting periodically collapsing bubbles. By using the formalism of dynamical system theory, we explain what drives the bubbles and how foreshocks or aftershocks are generated. A dynamical phase space representation of that system coupled with standard multiplicative noise rationalises the log-periodic power law singularity pattern documented in many historical financial bubbles. The notion of ‘ghosts of finite-time singularities’ is introduced and used to estimate the end of an evolving bubble, using finite-time singularities of an approximate normal form near the bifurcation point. We test the forecasting skill of this method on different stochastic price realisations and compare with Monte Carlo simulations of the full system. Remarkably, the approximate normal form is significantly more precise and less biased. Moreover, the method of ghosts of singularities is less sensitive to the noise realisation, thus providing more robust forecasts. PMID:29596485

The behaviour of PM10 and ozone in Malaysia through non-linear dynamical systems

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

Sapini, Muhamad Luqman; Rahim, Nurul Zahirah binti Abd; Noorani, Mohd Salmi Md.

Prediction of ozone (O3) and PM10 is very important as both these air pollutants affect human health, human activities and more. Short-term forecasting of air quality is needed as preventive measures and effective action can be taken. Therefore, if it is detected that the ozone data is of a chaotic dynamical systems, a model using the nonlinear dynamic from chaos theory data can be made and thus forecasts for the short term would be more accurate. This study uses two methods, namely the 0-1 Test and Lyapunov Exponent. In addition, the effect of noise reduction on the analysis of timemore » series data will be seen by using two smoothing methods: Rectangular methods and Triangle methods. At the end of the study, recommendations were made to get better results in the future.« less

How to pose the question matters: Behavioural Economics concepts in decision making on the basis of ensemble forecasts

NASA Astrophysics Data System (ADS)

Alfonso, Leonardo; van Andel, Schalk Jan

2014-05-01

Part of recent research in ensemble and probabilistic hydro-meteorological forecasting analyses which probabilistic information is required by decision makers and how it can be most effectively visualised. This work, in addition, analyses if decision making in flood early warning is also influenced by the way the decision question is posed. For this purpose, the decision-making game "Do probabilistic forecasts lead to better decisions?", which Ramos et al (2012) conducted at the EGU General Assembly 2012 in the city of Vienna, has been repeated with a small group and expanded. In that game decision makers had to decide whether or not to open a flood release gate, on the basis of flood forecasts, with and without uncertainty information. A conclusion of that game was that, in the absence of uncertainty information, decision makers are compelled towards a more risk-averse attitude. In order to explore to what extent the answers were driven by the way the questions were framed, in addition to the original experiment, a second variant was introduced where participants were asked to choose between a sure value (for either loosing or winning with a giving probability) and a gamble. This set-up is based on Kahneman and Tversky (1979). Results indicate that the way how the questions are posed may play an important role in decision making and that Prospect Theory provides promising concepts to further understand how this works.

The influence of dielectric relaxation on intramolecular electron transfer

NASA Astrophysics Data System (ADS)

Heitele, H.; Michel-Beyerle, M. E.; Finckh, P.

1987-07-01

An unusually strong temperature dependence on the intramolecular electron-transfer rate has been observed for bridged donor-acceptor compounds in propylene glycol solution. In the frame of recent electron-transfer theories this effect reflects the influence of dielectric relaxation dynamics on electron transfer. With increasing dielectric relaxation time a smooth transition from non-adiabatic to solvent-controlled adiabatic behaviour is observed. The electron transfer rate in the solvent-controlled adiabatic limit is dominated by an inhomogeneous distribution of relaxation times.

Sterics level the rates of proton transfer to [Ni(XPh){PhP(CH₂CH₂PPh₂)₂}]⁺ (X = O, S or Se).

PubMed

Alwaaly, Ahmed; Henderson, Richard A

2014-09-04

Rates of proton transfers between lutH(+) (lut = 2,6-dimethylpyridine) and [Ni(XPh)(PhP{CH2CH2PPh2}2)](+) (X = O, S or Se) are slow and show little variation (k(O) : k(S) : k(Se) = 1 : 12 : 9). This unusual behaviour is a consequence of sterics affecting the optimal interaction between the reactants prior to proton transfer.

Operational forecasting of daily temperatures in the Valencia Region. Part II: minimum temperatures in winter.

NASA Astrophysics Data System (ADS)

Gómez, I.; Estrela, M.

2009-09-01

Extreme temperature events have a great impact on human society. Knowledge of minimum temperatures during winter is very useful for both the general public and organisations whose workers have to operate in the open, e.g. railways, roadways, tourism, etc. Moreover, winter minimum temperatures are considered a parameter of interest and concern since persistent cold-waves can affect areas as diverse as public health, energy consumption, etc. Thus, an accurate forecasting of these temperatures could help to predict cold-wave conditions and permit the implementation of strategies aimed at minimizing the negative effects that low temperatures have on human health. The aim of this work is to evaluate the skill of the RAMS model in determining daily minimum temperatures during winter over the Valencia Region. For this, we have used the real-time configuration of this model currently running at the CEAM Foundation. To carry out the model verification process, we have analysed not only the global behaviour of the model for the whole Valencia Region, but also its behaviour for the individual stations distributed within this area. The study has been performed for the winter forecast period from 1 December 2007 - 31 March 2008. The results obtained are encouraging and indicate a good agreement between the observed and simulated minimum temperatures. Moreover, the model captures quite well the temperatures in the extreme cold episodes. Acknowledgement. This work was supported by "GRACCIE" (CSD2007-00067, Programa Consolider-Ingenio 2010), by the Spanish Ministerio de Educación y Ciencia, contract number CGL2005-03386/CLI, and by the Regional Government of Valencia Conselleria de Sanitat, contract "Simulación de las olas de calor e invasiones de frío y su regionalización en la Comunidad Valenciana" ("Heat wave and cold invasion simulation and their regionalization at Valencia Region"). The CEAM Foundation is supported by the Generalitat Valenciana and BANCAIXA (Valencia, Spain).

Operational forecasting of daily temperatures in the Valencia Region. Part I: maximum temperatures in summer.

NASA Astrophysics Data System (ADS)

Gómez, I.; Estrela, M.

2009-09-01

Extreme temperature events have a great impact on human society. Knowledge of summer maximum temperatures is very useful for both the general public and organisations whose workers have to operate in the open, e.g. railways, roadways, tourism, etc. Moreover, summer maximum daily temperatures are considered a parameter of interest and concern since persistent heat-waves can affect areas as diverse as public health, energy consumption, etc. Thus, an accurate forecasting of these temperatures could help to predict heat-wave conditions and permit the implementation of strategies aimed at minimizing the negative effects that high temperatures have on human health. The aim of this work is to evaluate the skill of the RAMS model in determining daily maximum temperatures during summer over the Valencia Region. For this, we have used the real-time configuration of this model currently running at the CEAM Foundation. To carry out the model verification process, we have analysed not only the global behaviour of the model for the whole Valencia Region, but also its behaviour for the individual stations distributed within this area. The study has been performed for the summer forecast period of 1 June - 30 September, 2007. The results obtained are encouraging and indicate a good agreement between the observed and simulated maximum temperatures. Moreover, the model captures quite well the temperatures in the extreme heat episodes. Acknowledgement. This work was supported by "GRACCIE" (CSD2007-00067, Programa Consolider-Ingenio 2010), by the Spanish Ministerio de Educación y Ciencia, contract number CGL2005-03386/CLI, and by the Regional Government of Valencia Conselleria de Sanitat, contract "Simulación de las olas de calor e invasiones de frío y su regionalización en la Comunidad Valenciana" ("Heat wave and cold invasion simulation and their regionalization at Valencia Region"). The CEAM Foundation is supported by the Generalitat Valenciana and BANCAIXA (Valencia, Spain).

A Maple package for improved global mapping forecast

NASA Astrophysics Data System (ADS)

Carli, H.; Duarte, L. G. S.; da Mota, L. A. C. P.

2014-03-01

We present a Maple implementation of the well known global approach to time series analysis and some further developments designed to improve the computational efficiency of the forecasting capabilities of the approach. This global approach can be summarized as being a reconstruction of the phase space, based on a time ordered series of data obtained from the system. After that, using the reconstructed vectors, a portion of this space is used to produce a mapping, a polynomial fitting, through a minimization procedure, that represents the system and can be employed to forecast further entries for the series. In the present implementation, we introduce a set of commands, tools, in order to perform all these tasks. For example, the command VecTS deals mainly with the reconstruction of the vector in the phase space. The command GfiTS deals with producing the minimization and the fitting. ForecasTS uses all these and produces the prediction of the next entries. For the non-standard algorithms, we here present two commands: IforecasTS and NiforecasTS that, respectively deal with the one-step and the N-step forecasting. Finally, we introduce two further tools to aid the forecasting. The commands GfiTS and AnalysTS, basically, perform an analysis of the behavior of each portion of a series regarding the settings used on the commands just mentioned above. Catalogue identifier: AERW_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERW_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 3001 No. of bytes in distributed program, including test data, etc.: 95018 Distribution format: tar.gz Programming language: Maple 14. Computer: Any capable of running Maple Operating system: Any capable of running Maple. Tested on Windows ME, Windows XP, Windows 7. RAM: 128 MB Classification: 4.3, 4.9, 5 Nature of problem: Time series analysis and improving forecast capability. Solution method: The method of solution is partially based on a result published in [1]. Restrictions: If the time series that is being analyzed presents a great amount of noise or if the dynamical system behind the time series is of high dimensionality (Dim≫3), then the method may not work well. Unusual features: Our implementation can, in the cases where the dynamics behind the time series is given by a system of low dimensionality, greatly improve the forecast. Running time: This depends strongly on the command that is being used. References: [1] Barbosa, L.M.C.R., Duarte, L.G.S., Linhares, C.A. and da Mota, L.A.C.P., Improving the global fitting method on nonlinear time series analysis, Phys. Rev. E 74, 026702 (2006).

Comparative analysis of model behaviour for flood prediction purposes using Self-Organizing Maps

NASA Astrophysics Data System (ADS)

Herbst, M.; Casper, M. C.; Grundmann, J.; Buchholz, O.

2009-03-01

Distributed watershed models constitute a key component in flood forecasting systems. It is widely recognized that models because of their structural differences have varying capabilities of capturing different aspects of the system behaviour equally well. Of course, this also applies to the reproduction of peak discharges by a simulation model which is of particular interest regarding the flood forecasting problem. In our study we use a Self-Organizing Map (SOM) in combination with index measures which are derived from the flow duration curve in order to examine the conditions under which three different distributed watershed models are capable of reproducing flood events present in the calibration data. These indices are specifically conceptualized to extract data on the peak discharge characteristics of model output time series which are obtained from Monte-Carlo simulations with the distributed watershed models NASIM, LARSIM and WaSIM-ETH. The SOM helps to analyze this data by producing a discretized mapping of their distribution in the index space onto a two dimensional plane such that their pattern and consequently the patterns of model behaviour can be conveyed in a comprehensive manner. It is demonstrated how the SOM provides useful information about details of model behaviour and also helps identifying the model parameters that are relevant for the reproduction of peak discharges and thus for flood prediction problems. It is further shown how the SOM can be used to identify those parameter sets from among the Monte-Carlo data that most closely approximate the peak discharges of a measured time series. The results represent the characteristics of the observed time series with partially superior accuracy than the reference simulation obtained by implementing a simple calibration strategy using the global optimization algorithm SCE-UA. The most prominent advantage of using SOM in the context of model analysis is that it allows to comparatively evaluating the data from two or more models. Our results highlight the individuality of the model realizations in terms of the index measures and shed a critical light on the use and implementation of simple and yet too rigorous calibration strategies.

Large and unexpected runup events and their relation to the incident wave field

NASA Astrophysics Data System (ADS)

Li, C.; Ozkan-Haller, H. T.; Garcia-Medina, G.; Holman, R. A.; Ruggiero, P.

2016-12-01

Unusually large runup events are important for the prediction of dune erosion, inundation and coastal flooding during storms and lie at the tail of swash maxima probability distributions. We also distinguish a unique type of large runup event that is sudden and unexpected even if the landward reach of the runup is not a statistical extreme. These unusual runup events are anecdotally reported to be more prevalent on dissipative beaches and are the leading cause of death by drowning along the U.S. Pacific Northwest (northern California, Oregon, and Washington). Herein we examine the environmental conditions that are conducive to large and unexpected runup events and begin to forecast their potential occurrence, validating these predictions with ongoing observations. We explore and compare the statistics of large runup events on two beach types, a dissipative beach at Agate Beach, OR, and the intermediate/reflective site at Duck, NC. Video-based runup observations along with incident wave information from offshore instrumentation are used to assess how frequently large or unexpected runup events occur, how the statistics of these runup events relate to the incident wave characteristics (e.g. height, period, narrow-bandedness), and whether or not these events are indeed more prevalent on dissipative beaches.

Statewide Floods in Pennsylvania, January 1996

USGS Publications Warehouse

Thompson, R.E.

1996-01-01

Rivers and streams throughout Pennsylvania (fig. 1) experienced major flooding during January 1996. Flood stages (water-surface heights) and discharges (flows) in many of the Commonwealth's waterways were measured by the U.S. Geological Survey (USGS) and approached or exceeded record levels established during previous floods. Setting the stage for the flooding was an unusually cold beginning to the winter of 1995-96, which resulted in the early formation of ice in streams statewide. The anomaly of early ice was followed by a sequence of unusual meteorological events in January 1996, which, in many areas, resulted in the most widespread and severe flooding since that produced by tropical storm Agnes in June 1972. Locally, the flooding was the worst since August 1955 and, in some areas, since March 1936. In approximately 50 localities throughout Pennsylvania, flood effects were magnified when ice jams caused temporary damming of stream channels, resulting in the rapid rise of water levels and the subsequent overflow of water and ice onto flood plains. During the floods, the USGS collected stream-stage information on a near real- 42°-GffEAWa/CESJ DRWNAG. time basis at 189 streamflow-gaging stations across the Commonwealth. This information was used by various Federal, State, and local agencies to prepare flood forecasts and develop plans for emergency response.

[Ignatius of Loyola--gifted or mentally ill?].

PubMed

Heinrich, K; Walter, C

1995-06-01

Subsequent to a severe injury and under the influence of religious reading, Loyola experienced a dramatic mental change in his spiritual values in the sense of a sublimation to an alternative knighthood. His behaviour patterns observed thereafter were determined by a totality of his attachment to God. Based on this certainty in his faith, which was free from any doubts, and on God, and with the background of fasting and praying, he had visionary and pseudo-hallucinatory experiences. As the founder of an order and head of the community of Jesuits, Ignatius of Loyola proved to be diplomatically highly talented. There is no evidence of any psychotic disease. Also, there is no probability of a personality disorder in the sense of a neurosis. The numerous unusual behaviour patterns of Ignatius cannot be interpreted as psychopathological symptoms. It is justified to call him a genius.

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

Ramey, H.J. Jr.

Most of the significant contributions to reservoir engineering were made by a handful of prodigious giants in the 1930's and 1940's. The most significant contribution that can be made in the next 20 yr will be to fully understand--perhaps with the help of that latest prodigy, the computer--what those giants were driving at. Even if only the presently known oil-recovery processes are considered, exciting happenings in the area of oil recovery can be forecast for the next 20 yr. During the 1950's and 1960's, thermal recovery, miscible fluid injection, and non-Newtonian (mobility control) fluid injection were developed and widely pilotmore » tested. All of these methods offer the potential for very high oil recoveries--on the order of 80 to 100% of oil in the displaced region. It is hoped that the development of methods will occur, which are capable of recovering 75% of oil in place at the start of fluid injection. Technologically, this is really not a bold forecast--both wet combustion and micellar solution slug injection already appear to have this capability in well-designed operations. The late 1960's was a period of unusually successful exploration. Large finds were made, worldwide, almost daily: Prudhoe Bay, the North Sea, Australia, and Indonesia. (11 refs.)« less

Modelling the development of defects during composite reinforcements and prepreg forming

PubMed Central

Hamila, N.; Madeo, A.

2016-01-01

Defects in composite materials are created during manufacture to a large extent. To avoid them as much as possible, it is important that process simulations model the onset and the development of these defects. It is then possible to determine the manufacturing conditions that lead to the absence or to the controlled presence of such defects. Three types of defects that may appear during textile composite reinforcement or prepreg forming are analysed and modelled in this paper. Wrinkling is one of the most common flaws that occur during textile composite reinforcement forming processes. The influence of the different rigidities of the textile reinforcement is studied. The concept of ‘locking angle’ is questioned. A second type of unusual behaviour of fibrous composite reinforcements that can be seen as a flaw during their forming process is the onset of peculiar ‘transition zones’ that are directly related to the bending stiffness of the fibres. The ‘transition zones’ are due to the bending stiffness of fibres. The standard continuum mechanics of Cauchy is not sufficient to model these defects. A second gradient approach is presented that allows one to account for such unusual behaviours and to master their onset and development during forming process simulations. Finally, the large slippages that may occur during a preform forming are discussed and simulated with meso finite-element models used for macroscopic forming. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’. PMID:27242300

Modelling the development of defects during composite reinforcements and prepreg forming.

PubMed

Boisse, P; Hamila, N; Madeo, A

2016-07-13

Defects in composite materials are created during manufacture to a large extent. To avoid them as much as possible, it is important that process simulations model the onset and the development of these defects. It is then possible to determine the manufacturing conditions that lead to the absence or to the controlled presence of such defects. Three types of defects that may appear during textile composite reinforcement or prepreg forming are analysed and modelled in this paper. Wrinkling is one of the most common flaws that occur during textile composite reinforcement forming processes. The influence of the different rigidities of the textile reinforcement is studied. The concept of 'locking angle' is questioned. A second type of unusual behaviour of fibrous composite reinforcements that can be seen as a flaw during their forming process is the onset of peculiar 'transition zones' that are directly related to the bending stiffness of the fibres. The 'transition zones' are due to the bending stiffness of fibres. The standard continuum mechanics of Cauchy is not sufficient to model these defects. A second gradient approach is presented that allows one to account for such unusual behaviours and to master their onset and development during forming process simulations. Finally, the large slippages that may occur during a preform forming are discussed and simulated with meso finite-element models used for macroscopic forming. This article is part of the themed issue 'Multiscale modelling of the structural integrity of composite materials'. © 2016 The Author(s).

Response of Amazon Fires to the 2015/2016 El Niño and Evaluation of a Seasonal Fire Season Severity Forecast

NASA Astrophysics Data System (ADS)

Randerson, J. T.

2016-12-01

Recent work has established that year-to-year variability in drought and fire within the Amazon responds to a dual forcing from ocean-atmosphere interactions in the tropical Pacific and North Atlantic. Teleconnections between the Pacific and the Amazon are strongest between October and March, when El Niño contributes to below-average precipitation during the wet season. A reduced build-up of soil moisture during the wet season, in turn, may limit water availability and transpiration in tropical forests during the following dry season, lowering surface humidity, drying fuels, and allowing fires to spread more easily through the understory. The delayed influence of soil moisture through this land - atmosphere coupling provides a means to predict fire season severity 3-6 months before the onset of the dry season. With the aim of creating new opportunities for forest conservation, we have developed an experimental seasonal fire forecasting system for the Amazon. The 2016 fire season severity forecast, released in June by UCI and NASA, predicts unusually high risk across eastern Peru, northern Bolivia, and Brazil. Several surface and satellite data streams confirm that El Niño teleconnections had a significant impact on wet season hydrology within the Amazon. Rainfall observations from the Global Precipitation Climatology Centre provided evidence that cumulative precipitation deficits during August-April were 1 to 2 standard deviations below the long-term mean for most of the basin. These observations were corroborated by strong negative terrestrial water storage anomalies measured by the Gravity Recovery and Climate Experiment, and by fluorescence and vegetation index observations from other sensors that indicated elevated canopy stress. By August 3rd, satellite observations showed above average fire activity in most, but not all, forecast regions. Using additional satellite observations that become available later this year, we plan to describe the full spatial and temporal pattern of fires within the Amazon during the 2016 dry season and evaluate the success of our forecast. As a part of this analysis, we will compare fires from 2016 with other years of extreme drought (i.e., 2005 and 2010), and assess how trends in land use, including regional changes in deforestation, modify El Niño-driven fire risk.

Impacts of Aerosol-Monsoon Interaction on Rainfall and Circulation over Northern India and the Himalaya Foothills

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kim, Kyu-Myong; Shi, Jainn-Jong; Matsui, T.; Chin, M.; Tan, Qian; Peters-Lidard, C.; Tao, W. K.

2016-01-01

The boreal summer of 2008 was unusual for the Indian monsoon, featuring exceptional heavy loading of dust aerosols over the Arabian Sea and northern-central India, near normal all- India rainfall, but excessive heavy rain, causing disastrous flooding in the Northern Indian Himalaya Foothills (NIHF) regions, accompanied by persistent drought conditions in central and southern India. Using NASA Unified-physics Weather Research Forecast (NUWRF) model with fully interactive aerosol physics and dynamics, we carried out three sets of 7-day ensemble model forecast experiments: 1) control with no aerosol, 2) aerosol radiative effect only and 3) aerosol radiative and aerosol-cloud-microphysics effects, to study the impacts of aerosol monsoon interactions on monsoon variability over the NIHF during the summer of 2008. Results show that aerosol-radiation interaction (ARI), i.e., dust aerosol transport, and dynamical feedback processes induced by aerosol-radiative heating, plays a key role in altering the large scale monsoon circulation system, reflected by an increased north-south tropospheric temperature gradient, a northward shift of heavy monsoon rainfall, advancing the monsoon onset by 1-5 days over the HF, consistent with the EHP hypothesis (Lau et al. 2006). Additionally, we found that dust aerosols, via the semi-direct effect, increase atmospheric stability, and cause the dissipation of a developing monsoon onset cyclone over northeastern India northern Bay of Bengal. Eventually, in a matter of several days, ARI transforms the developing monsoon cyclone into mesoscale convective cells along the HF slopes. Aerosol-Cloud-microphysics Interaction (ACI) further enhances the ARI effect in invigorating the deep convection cells and speeding up the transformation processes. Results indicate that even in short-term (up to weekly) numerical forecasting of monsoon circulation and rainfall, effects of aerosol-monsoon interaction can be substantial and cannot be ignored.

A Sinuous Tumulus over an Active Lava Tube at Klauea Volcano: Evolution, Analogs, and Hazard Forecasts

NASA Technical Reports Server (NTRS)

Orr, Tim R.; Bleacher, Jacob E.; Patrick, Matthew R.; Wooten, Kelly M.

2015-01-01

Inflation of narrow tube-fed basaltic lava flows (tens of meters across), such as those confined by topography, can be focused predominantly along the roof of a lava tube. This can lead to the development of an unusually long tumulus, its shape matching the sinuosity of the underlying lava tube. Such a situation occurred during Klauea Volcanos (Hawaii, USA) ongoing East Rift Zone eruption on a lava tube active from July through November 2010. Short-lived breakouts from the tube buried the flanks of the sinuous, ridge-like tumulus, while the tumulus crest, its surface composed of lava formed very early in the flows emplacement history, remained poised above the surrounding younger flows. At least several of these breakouts resulted in irrecoverable uplift of the tube roof. Confined sections of the prehistoric Carrizozo and McCartys flows (New Mexico, USA) display similar sinuous, ridge-like features with comparable surface age relationships. We contend that these distinct features formed in a fashion equivalent to that of the sinuous tumulus that formed at Kilauea in 2010. Moreover, these sinuous tumuli may be analogs for some sinuous ridges evident in orbital images of the Tharsis volcanic province on Mars. The short-lived breakouts from the sinuous tumulus at Kilauea were caused by surges in discharge through the lava tube, in response to cycles of deflation and inflation (DI events) at Kilauea's summit. The correlation between DI events and subsequent breakouts aided in lava flow forecasting. Breakouts from the sinuous tumulus advanced repeatedly toward the sparsely populated Kalapana Gardens subdivision, destroying two homes and threatening others. Hazard assessments, including flow occurrence and advance forecasts, were relayed regularly to the Hawai?i County Civil Defense to aid their lava flow hazard mitigation efforts while this lava tube was active.

The impact of vertical resolution in mesoscale model AROME forecasting of radiation fog

NASA Astrophysics Data System (ADS)

Philip, Alexandre; Bergot, Thierry; Bouteloup, Yves; Bouyssel, François

2015-04-01

Airports short-term forecasting of fog has a security and economic impact. Numerical simulations have been performed with the mesoscale model AROME (Application of Research to Operations at Mesoscale) (Seity et al. 2011). Three vertical resolutions (60, 90 and 156 levels) are used to show the impact of radiation fog on numerical forecasting. Observations at Roissy Charles De Gaulle airport are compared to simulations. Significant differences in the onset, evolution and dissipation of fog were found. The high resolution simulation is in better agreement with observations than a coarser one. The surface boundary layer and incoming long-wave radiations are better represented. A more realistic behaviour of liquid water content evolution allows a better anticipation of low visibility procedures (ceiling < 60m and/or visibility < 600m). The case study of radiation fog shows that it is necessary to have a well defined vertical grid to better represent local phenomena. A statistical study over 6 months (October 2011 - March 2012 ) using different configurations was carried out. Statistically, results were the same as in the case study of radiation fog. Seity Y., P. Brousseau, S. Malardel, G. Hello, P. Bénard, F. Bouttier, C. Lac, V. Masson, 2011: The AROME-France convective scale operational model. Mon.Wea.Rev., 139, 976-991.

Micro and macro benefits of random investments in financial markets

NASA Astrophysics Data System (ADS)

Biondo, A. E.; Pluchino, A.; Rapisarda, A.

2014-10-01

In this paper, making use of recent statistical physics techniques and models, we address the specific role of randomness in financial markets, both at the micro and the macro level. In particular, we review some recent results obtained about the effectiveness of random strategies of investment, compared with some of the most used trading strategies for forecasting the behaviour of real financial indexes. We also push forward our analysis by means of a self-organised criticality model, able to simulate financial avalanches in trading communities with different network topologies, where a Pareto-like power law behaviour of wealth spontaneously emerges. In this context, we present new findings and suggestions for policies based on the effects that random strategies can have in terms of reduction of dangerous financial extreme events, i.e. bubbles and crashes.

Energetics of intrinsic defects in NiO and the consequences for its resistive random access memory performance

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

Dawson, J. A., E-mail: jad95@cam.ac.uk; Guo, Y.; Robertson, J.

2015-09-21

Energetics for a variety of intrinsic defects in NiO are calculated using state-of-the-art ab initio hybrid density functional theory calculations. At the O-rich limit, Ni vacancies are the lowest cost defect for all Fermi energies within the gap, in agreement with the well-known p-type behaviour of NiO. However, the ability of the metal electrode in a resistive random access memory metal-oxide-metal setup to shift the oxygen chemical potential towards the O-poor limit results in unusual NiO behaviour and O vacancies dominating at lower Fermi energy levels. Calculated band diagrams show that O vacancies in NiO are positively charged at themore » operating Fermi energy giving it the advantage of not requiring a scavenger metal layer to maximise drift. Ni and O interstitials are generally found to be higher in energy than the respective vacancies suggesting that significant recombination of O vacancies and interstitials does not take place as proposed in some models of switching behaviour.« less

A comparison of behavioural (Landolt C) and anatomical estimates of visual acuity in archerfish (Toxotes chatareus).

PubMed

Temple, S E; Manietta, D; Collin, S P

2013-05-03

Archerfish forage by shooting jets of water at insects above the water's surface. The challenge of detecting small prey items against a complex background suggests that they have good visual acuity, but to date this has never been tested, despite archerfish becoming an increasingly important model species for vertebrate vision. We used a modified Landolt C test to measure visual acuity behaviourally, and compared the results to their predicted minimum separable angle based on both photoreceptor and ganglion cell spacing in the retina. Both measures yielded similar estimates of visual acuity; between 3.23 and 3.57 cycles per degree (0.155-0.140° of visual arc). Such a close match between behavioural and anatomical estimates of visual acuity in fishes is unusual and may be due to our use of an ecologically relevant task that measured the resolving power of the part of the retina that has the highest photoreceptor density and that is used in aligning their spitting angle with potential targets. Copyright © 2013 Elsevier Ltd. All rights reserved.

A New Framework to Compare Mass-Flux Schemes Within the AROME Numerical Weather Prediction Model

NASA Astrophysics Data System (ADS)

Riette, Sébastien; Lac, Christine

2016-08-01

In the Application of Research to Operations at Mesoscale (AROME) numerical weather forecast model used in operations at Météo-France, five mass-flux schemes are available to parametrize shallow convection at kilometre resolution. All but one are based on the eddy-diffusivity-mass-flux approach, and differ in entrainment/detrainment, the updraft vertical velocity equation and the closure assumption. The fifth is based on a more classical mass-flux approach. Screen-level scores obtained with these schemes show few discrepancies and are not sufficient to highlight behaviour differences. Here, we describe and use a new experimental framework, able to compare and discriminate among different schemes. For a year, daily forecast experiments were conducted over small domains centred on the five French metropolitan radio-sounding locations. Cloud base, planetary boundary-layer height and normalized vertical profiles of specific humidity, potential temperature, wind speed and cloud condensate were compared with observations, and with each other. The framework allowed the behaviour of the different schemes in and above the boundary layer to be characterized. In particular, the impact of the entrainment/detrainment formulation, closure assumption and cloud scheme were clearly visible. Differences mainly concerned the transport intensity thus allowing schemes to be separated into two groups, with stronger or weaker updrafts. In the AROME model (with all interactions and the possible existence of compensating errors), evaluation diagnostics gave the advantage to the first group.

Unusual Attenuation Recovery Process After Fiber Optic Cable Irradiation

NASA Astrophysics Data System (ADS)

Konečná, Z.; Plaček, V.; Havránek, P.

2017-11-01

At present, the number of optical cables in nuclear power plants has been increasing. Fiber optic cables are commonly used at nuclear power plants in instrumentation and control systems but they are usually used in environments without radiation. Nevertheless, currently, the number of applications in NPP containment with radiation is increasing. One of the most prevalent effects of radiation exposure is an increase of signal attenuation (signal loss). This is the result of fiber darkening due to radiation exposure and it is the main limitation factor in application of fiber optics in radiation environment. However, after the irradiation, the fiber optics go through a “recovery process” during which the optical properties improve again; i.e. attenuation decreases. However, we have found cable, where the expected healing process after few days changed its trend and the attenuation increased again to a value well above the attenuation just after the irradiation. This paper describes experiments that were carried out to explain this unusual recovery behaviour.

Peer socialization of masculinity and femininity: differential effects of overt and relational forms of peer victimization.

PubMed

Ewing Lee, Elizabeth A; Troop-Gordon, Wendy

2011-06-01

Although peer influence has been implicated in recent theories of gender socialization, few investigations have tested whether children's gendered behaviours change over time as a function of peer experiences and whether some peer experiences may exacerbate, rather than dampen, gender non-conformity. Accordingly, the current study examined prospective links between specific forms of peer victimization and children's adherence to traditional gender roles. Peer reports of victimization and self-reports of engagement in stereotypically masculine and feminine activities were collected from 199 children (104 girls; 95 boys) in the Fall and Spring of their fifth-grade year. Multi-group path analysis was used to explore the relations between forms of victimization and masculinity and femininity for girls and boys. For girls, peer victimization predicted withdrawal from both feminine and masculine behaviours. For boys, physical, verbal, and general victimization predicted lower levels of feminine behaviours, but social exclusion forecast heightened engagement in traditionally feminine activities. These findings underscore how social experiences can amplify, as well as reduce, gender non-conformity.

Application of stochastic methods for wind speed forecasting and wind turbines design at the area of Thessaly, Greece

NASA Astrophysics Data System (ADS)

Dimitriadis, Panayiotis; Lazaros, Lappas; Daskalou, Olympia; Filippidou, Ariadni; Giannakou, Marianna; Gkova, Eleni; Ioannidis, Romanos; Polydera, Angeliki; Polymerou, Eleni; Psarrou, Eleftheria; Vyrini, Alexandra; Papalexiou, Simon; Koutsoyiannis, Demetris

2015-04-01

Several methods exist for estimating the statistical properties of wind speed, most of them being deterministic or probabilistic, disregarding though its long-term behaviour. Here, we focus on the stochastic nature of wind. After analyzing several historical timeseries at the area of interest (AoI) in Thessaly (Greece), we show that a Hurst-Kolmogorov (HK) behaviour is apparent. Thus, disregarding the latter could lead to unrealistic predictions and wind load situations, causing some impact on the energy production and management. Moreover, we construct a stochastic model capable of preserving the HK behaviour and we produce synthetic timeseries using a Monte-Carlo approach to estimate the future wind loads in the AoI. Finally, we identify the appropriate types of wind turbines for the AoI (based on the IEC 61400 standards) and propose several industrial solutions. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Kin discrimination via odour in the cooperatively breeding banded mongoose.

PubMed

Mitchell, J; Kyabulima, S; Businge, R; Cant, M A; Nichols, H J

2018-03-01

Kin discrimination is often beneficial for group-living animals as it aids in inbreeding avoidance and providing nepotistic help. In mammals, the use of olfactory cues in kin discrimination is widespread and may occur through learning the scents of individuals that are likely to be relatives, or by assessing genetic relatedness directly through assessing odour similarity (phenotype matching). We use scent presentations to investigate these possibilities in a wild population of the banded mongoose Mungos mungo , a cooperative breeder in which inbreeding risk is high and females breed communally, disrupting behavioural cues to kinship. We find that adults show heightened behavioural responses to unfamiliar (extra-group) scents than to familiar (within-group) scents. Interestingly, we found that responses to familiar odours, but not unfamiliar odours, varied with relatedness. This suggests that banded mongooses are either able to use an effective behavioural rule to identify likely relatives from within their group, or that phenotype matching is used in the context of within-group kin recognition but not extra-group kin recognition. In other cooperative breeders, familiarity is used within the group and phenotype matching may be used to identify unfamiliar kin. However, for the banded mongoose this pattern may be reversed, most likely due to their unusual breeding system which disrupts within-group behavioural cues to kinship.

Potentially exploitable supercritical geothermal resources in the ductile crust

USGS Publications Warehouse

Watanabe, Noriaki; Numakura, Tatsuya; Sakaguchi, Kiyotoshi; Saishu, Hanae; Okamoto, Atsushi; Ingebritsen, Steven E.; Tsuchiya, Noriyoshi

2017-01-01

The hypothesis that the brittle–ductile transition (BDT) drastically reduces permeability implies that potentially exploitable geothermal resources (permeability >10−16 m2) consisting of supercritical water could occur only in rocks with unusually high transition temperatures such as basalt. However, tensile fracturing is possible even in ductile rocks, and some permeability–depth relations proposed for the continental crust show no drastic permeability reduction at the BDT. Here we present experimental results suggesting that the BDT is not the first-order control on rock permeability, and that potentially exploitable resources may occur in rocks with much lower BDT temperatures, such as the granitic rocks that comprise the bulk of the continental crust. We find that permeability behaviour for fractured granite samples at 350–500 °C under effective confining stress is characterized by a transition from a weakly stress-dependent and reversible behaviour to a strongly stress-dependent and irreversible behaviour at a specific, temperature-dependent effective confining stress level. This transition is induced by onset of plastic normal deformation of the fracture surface (elastic–plastic transition) and, importantly, causes no ‘jump’ in the permeability. Empirical equations for this permeability behaviour suggest that potentially exploitable resources exceeding 450 °C may form at depths of 2–6 km even in the nominally ductile crust.

Impact of rheology on probabilistic forecasts of sea ice trajectories: application for search and rescue operations in the Arctic

NASA Astrophysics Data System (ADS)

Rabatel, Matthias; Rampal, Pierre; Carrassi, Alberto; Bertino, Laurent; Jones, Christopher K. R. T.

2018-03-01

We present a sensitivity analysis and discuss the probabilistic forecast capabilities of the novel sea ice model neXtSIM used in hindcast mode. The study pertains to the response of the model to the uncertainty on winds using probabilistic forecasts of ice trajectories. neXtSIM is a continuous Lagrangian numerical model that uses an elasto-brittle rheology to simulate the ice response to external forces. The sensitivity analysis is based on a Monte Carlo sampling of 12 members. The response of the model to the uncertainties is evaluated in terms of simulated ice drift distances from their initial positions, and from the mean position of the ensemble, over the mid-term forecast horizon of 10 days. The simulated ice drift is decomposed into advective and diffusive parts that are characterised separately both spatially and temporally and compared to what is obtained with a free-drift model, that is, when the ice rheology does not play any role in the modelled physics of the ice. The seasonal variability of the model sensitivity is presented and shows the role of the ice compactness and rheology in the ice drift response at both local and regional scales in the Arctic. Indeed, the ice drift simulated by neXtSIM in summer is close to the one obtained with the free-drift model, while the more compact and solid ice pack shows a significantly different mechanical and drift behaviour in winter. For the winter period analysed in this study, we also show that, in contrast to the free-drift model, neXtSIM reproduces the sea ice Lagrangian diffusion regimes as found from observed trajectories. The forecast capability of neXtSIM is also evaluated using a large set of real buoy's trajectories and compared to the capability of the free-drift model. We found that neXtSIM performs significantly better in simulating sea ice drift, both in terms of forecast error and as a tool to assist search and rescue operations, although the sources of uncertainties assumed for the present experiment are not sufficient for complete coverage of the observed IABP positions.

What won't Turnstones eat?

USGS Publications Warehouse

Gill, Robert E.

1986-01-01

The Turnstone Arenaria interpres probably has one of the most varied diets of any wader species. Besides the 'normal' foods taken (see, e.g., Prater 1972, Nettleship 1973, Jones 1975), a considerable variety of 'unusual' foods and feeding behaviours has also been reported. Items taken include soap, gull excrement, dog food, potato peels, cheese, oatmeal, and the flesh of dead animals, including birds, a sheep Ovis, a wolf Lupus, a cat Felis, and a human corpse (Bell 1961; Campbell 1966; King 1961, 1964, 1982; King 1982; MacDonald & Parmelee 1962; Mercer 1966; Selway & Kendall 1965; Spencer 1966).

Dancing partners at the synapse: auxiliary subunits that shape kainate receptor function

PubMed Central

Copits, Bryan A.; Swanson, Geoffrey T.

2012-01-01

Kainate receptors are a family of ionotropic glutamate receptors whose physiological roles differ from those of other subtypes of glutamate receptors in that they predominantly serve as modulators, rather than mediators, of synaptic transmission. Neuronal kainate receptors exhibit unusually slow kinetic properties that have been difficult to reconcile with the behaviour of recombinant kainate receptors. Recently, however, the neuropilin and tolloid-like 1 (NETO1) and NETO2 proteins were identified as auxiliary kainate receptor subunits that shape both the biophysical properties and synaptic localization of these receptors. PMID:22948074

Detecting and diagnosing hotspots for the enhanced management of hospital emergency departments in Queensland, Australia

PubMed Central

2013-01-01

Background Predictive tools are already being implemented to assist in Emergency Department bed management by forecasting the expected total volume of patients. Yet these tools are unable to detect and diagnose when estimates fall short. Early detection of hotspots, that is subpopulations of patients presenting in unusually high numbers, would help authorities to manage limited health resources and communicate effectively about emerging risks. We evaluate an anomaly detection tool that signals when, and in what way Emergency Departments in 18 hospitals across the state of Queensland, Australia, are significantly exceeding their forecasted patient volumes. Methods The tool in question is an adaptation of the Surveillance Tree methodology initially proposed in Sparks and Okugami (IntStatl 1:2–24, 2010). for the monitoring of vehicle crashes. The methodology was trained on presentations to 18 Emergency Departments across Queensland over the period 2006 to 2008. Artificial increases were added to simulated, in-control counts for these data to evaluate the tool’s sensitivity, timeliness and diagnostic capability. The results were compared with those from a univariate control chart. The tool was then applied to data from 2009, the year of the H1N1 (or ‘Swine Flu’) pandemic. Results The Surveillance Tree method was found to be at least as effective as a univariate, exponentially weighted moving average (EWMA) control chart when increases occurred in a subgroup of the monitored population. The method has advantages over the univariate control chart in that it allows for the monitoring of multiple disease groups while still allowing control of the overall false alarm rate. It is also able to detect changes in the makeup of the Emergency Department presentations, even when the total count remains unchanged. Furthermore, the Surveillance Tree method provides diagnostic information useful for service improvements or disease management. Conclusions Multivariate surveillance provides a useful tool in the management of hospital Emergency Departments by not only efficiently detecting unusually high numbers of presentations, but by providing information about which groups of patients are causing the increase. PMID:24313914

The Predictability of Dry-Season Precipitation in Tropical West Africa

NASA Astrophysics Data System (ADS)

Knippertz, P.; Davis, J.; Fink, A. H.

2012-04-01

Precipitation during the boreal winter dry season in tropical West Africa is rare but occasionally connected to high-impacts for the local population. Previous work has shown that these events are usually connected to a trough over northwestern Africa, an extensive cloud plume on its eastern side, unusual precipitation at the northern and western fringes of the Sahara, and reduced surface pressure over the southern Sahara and Sahel, which allows an inflow of moist southerlies from the Gulf of Guinea to feed the unusual dry-season rainfalls. These results also suggest that the extratropical influence enhances the predictability of these events on the synoptic timescale. Here we further investigate this question for the 11 dry seasons (November-March) 1998/99-2008/09 using rainfall estimates from TRMM (Tropical Rainfall Measuring Mission) and GPCP (Global Precipitation Climatology Project), and operational ensemble predictions from the European Centre for Medium-Range Forecasts (ECMWF). All fields are averaged over the study area 7.5-15°N, 10°W-10°E that spans most of southern West Africa. For each 0000 UTC analysis time, the daily precipitation estimates are accumulated to pentads and compared with 120-hour predictions starting at the same time. Compared to TRMM, the ensemble mean shows a weak positive bias, whereas there is a substantial negative bias with regard to GPCP. Temporal correlations reach a high value of 0.8 for both datasets, showing similar synoptic variability despite the differences in total amount. Standard probabilistic evaluation methods such as relative operating characteristic (ROC) diagrams indicate remarkably good reliability, resolution and skill, particularly for lower precipitation thresholds. Not surprisingly, forecasts cluster at low probabilities for higher thresholds, but the reliability and ROC score are still reasonably high. The results show that global ensemble prediction systems are capable to predict dry-season rainfall events in southern West Africa well, at least on regional spatial and synoptic time scales. These results should encourage West African weather services to capitalize more on the valuable information provided by ensemble prediction systems during the dry season.

Skin rash, headache and abnormal behaviour: unusual presentation of intracranial haemorrhage in dengue fever

PubMed Central

Wani, Abdul Majid; Mejally, Mousa Ali Al; Hussain, Waleed Mohd; Maimani, Wail Al; Hanif, Sadia; Khoujah, Amer Mohd; Siddiqi, Ahmad; Akhtar, Mubeena; Bafaraj, Mazen G; Fareed, Khurram

2010-01-01

Dengue viral infections are one of the most important mosquito borne diseases in the world. The dengue virus is a single stranded RNA virus belonging to the Flaviviridae family. There are four serotypes (DEN 1–4) classified according to biological and immunological criteria. Patients may be asymptomatic or their condition may give rise to undifferentiated fever, dengue fever, dengue haemorrhagic fever (DHF), or dengue shock syndrome. Annually, 100 million cases of dengue fever and half a million cases of DHF occur worldwide and 2.5 billion people are at risk. At present, dengue is endemic in 112 countries. Early recognition and prompt initiation of appropriate treatment are vital if disease related morbidity and mortality are to be limited. We present an interesting case of dengue fever with headache, skin rash and abnormal behaviour who had a massive intracranial haemorrhage with fatal outcome. PMID:22242067

A model for seasonal phytoplankton blooms.

PubMed

Huppert, Amit; Blasius, Bernd; Olinky, Ronen; Stone, Lewi

2005-10-07

We analyse a generic bottom-up nutrient phytoplankton model to help understand the dynamics of seasonally recurring algae blooms. The deterministic model displays a wide spectrum of dynamical behaviours, from simple cyclical blooms which trigger annually, to irregular chaotic blooms in which both the time between outbreaks and their magnitudes are erratic. Unusually, despite the persistent seasonal forcing, it is extremely difficult to generate blooms that are both annually recurring and also chaotic or irregular (i.e. in amplitude) even though this characterizes many real time-series. Instead the model has a tendency to 'skip' with outbreaks often being suppressed from 1 year to the next. This behaviour is studied in detail and we develop analytical expressions to describe the model's flow in phase space, yielding insights into the mechanism of the bloom recurrence. We also discuss how modifications to the equations through the inclusion of appropriate functional forms can generate more realistic dynamics.

Protein-like fully reversible tetramerisation and super-association of an aminocellulose

NASA Astrophysics Data System (ADS)

Nikolajski, Melanie; Adams, Gary G.; Gillis, Richard B.; Besong, David Tabot; Rowe, Arthur J.; Heinze, Thomas; Harding, Stephen E.

2014-01-01

Unusual protein-like, partially reversible associative behaviour has recently been observed in solutions of the water soluble carbohydrates known as 6-deoxy-6-(ω-aminoalkyl)aminocelluloses, which produce controllable self-assembling films for enzyme immobilisation and other biotechnological applications. Now, for the first time, we have found a fully reversible self-association (tetramerisation) within this family of polysaccharides. Remarkably these carbohydrate tetramers are then seen to associate further in a regular way into supra-molecular complexes. Fully reversible oligomerisation has been hitherto completely unknown for carbohydrates and instead resembles in some respects the assembly of polypeptides and proteins like haemoglobin and its sickle cell mutation. Our traditional perceptions as to what might be considered ``protein-like'' and what might be considered as ``carbohydrate-like'' behaviour may need to be rendered more flexible, at least as far as interaction phenomena are concerned.

The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

DOE PAGES

Boer, George J.; Smith, Douglas M.; Cassou, Christophe; ...

2016-01-01

The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less

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

Boer, George J.; Smith, Douglas M.; Cassou, Christophe

The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less

Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle.

PubMed

Deo, Ravinesh C; Downs, Nathan; Parisi, Alfio V; Adamowski, Jan F; Quilty, John M

2017-05-01

Exposure to erythemally-effective solar ultraviolet radiation (UVR) that contributes to malignant keratinocyte cancers and associated health-risk is best mitigated through innovative decision-support systems, with global solar UV index (UVI) forecast necessary to inform real-time sun-protection behaviour recommendations. It follows that the UVI forecasting models are useful tools for such decision-making. In this study, a model for computationally-efficient data-driven forecasting of diffuse and global very short-term reactive (VSTR) (10-min lead-time) UVI, enhanced by drawing on the solar zenith angle (θ s ) data, was developed using an extreme learning machine (ELM) algorithm. An ELM algorithm typically serves to address complex and ill-defined forecasting problems. UV spectroradiometer situated in Toowoomba, Australia measured daily cycles (0500-1700h) of UVI over the austral summer period. After trialling activations functions based on sine, hard limit, logarithmic and tangent sigmoid and triangular and radial basis networks for best results, an optimal ELM architecture utilising logarithmic sigmoid equation in hidden layer, with lagged combinations of θ s as the predictor data was developed. ELM's performance was evaluated using statistical metrics: correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe efficiency coefficient (E NS ), root mean square error (RMSE), and mean absolute error (MAE) between observed and forecasted UVI. Using these metrics, the ELM model's performance was compared to that of existing methods: multivariate adaptive regression spline (MARS), M5 Model Tree, and a semi-empirical (Pro6UV) clear sky model. Based on RMSE and MAE values, the ELM model (0.255, 0.346, respectively) outperformed the MARS (0.310, 0.438) and M5 Model Tree (0.346, 0.466) models. Concurring with these metrics, the Willmott's Index for the ELM, MARS and M5 Model Tree models were 0.966, 0.942 and 0.934, respectively. About 57% of the ELM model's absolute errors were small in magnitude (±0.25), whereas the MARS and M5 Model Tree models generated 53% and 48% of such errors, respectively, indicating the latter models' errors to be distributed in larger magnitude error range. In terms of peak global UVI forecasting, with half the level of error, the ELM model outperformed MARS and M5 Model Tree. A comparison of the magnitude of hourly-cumulated errors of 10-min lead time forecasts for diffuse and global UVI highlighted ELM model's greater accuracy compared to MARS, M5 Model Tree or Pro6UV models. This confirmed the versatility of an ELM model drawing on θ s data for VSTR forecasting of UVI at near real-time horizon. When applied to the goal of enhancing expert systems, ELM-based accurate forecasts capable of reacting quickly to measured conditions can enhance real-time exposure advice for the public, mitigating the potential for solar UV-exposure-related disease. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Smart procurement of naturally generated energy (SPONGE) for PHEVs

NASA Astrophysics Data System (ADS)

Gu, Yingqi; Häusler, Florian; Griggs, Wynita; Crisostomi, Emanuele; Shorten, Robert

2016-07-01

In this paper, we propose a new engine management system for hybrid vehicles to enable energy providers and car manufacturers to provide new services. Energy forecasts are used to collaboratively orchestrate the behaviour of engine management systems of a fleet of plug-in hybrid electric vehicle (PHEVs) to absorb oncoming energy in a smart manner. Cooperative algorithms are suggested to manage the energy absorption in an optimal manner for a fleet of vehicles, and the mobility simulator SUMO (Simulation of Urban MObility) is used to demonstrate the efficacy of the proposed idea.

A recurrence-weighted prediction algorithm for musical analysis

NASA Astrophysics Data System (ADS)

Colucci, Renato; Leguizamon Cucunuba, Juan Sebastián; Lloyd, Simon

2018-03-01

Forecasting the future behaviour of a system using past data is an important topic. In this article we apply nonlinear time series analysis in the context of music, and present new algorithms for extending a sample of music, while maintaining characteristics similar to the original piece. By using ideas from ergodic theory, we adapt the classical prediction method of Lorenz analogues so as to take into account recurrence times, and demonstrate with examples, how the new algorithm can produce predictions with a high degree of similarity to the original sample.

Scenario analysis and disaster preparedness for port and maritime logistics risk management.

PubMed

Kwesi-Buor, John; Menachof, David A; Talas, Risto

2016-08-01

System Dynamics (SD) modelling is used to investigate the impacts of policy interventions on industry actors' preparedness to mitigate risks and to recover from disruptions along the maritime logistics and supply chain network. The model suggests a bi-directional relation between regulation and industry actors' behaviour towards Disaster Preparedness (DP) in maritime logistics networks. The model also showed that the level of DP is highly contingent on forecast accuracy, technology change, attitude to risk prevention, port activities, and port environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Visualizing disaster attitudes resulting from terrorist activities.

PubMed

Khalid, Halimahtun M; Helander, Martin G; Hood, Nilwan A

2013-09-01

The purpose of this study was to analyze people's attitudes to disasters by investigating how people feel, behave and think during disasters. We focused on disasters induced by humans, such as terrorist attacks. Two types of textual information were collected - from Internet blogs and from research papers. The analysis enabled forecasting of attitudes for the design of proactive disaster advisory scheme. Text was analyzed using a text mining tool, Leximancer. The outcome of this analysis revealed core themes and concepts in the text concerning people's attitudes. The themes and concepts were sorted into three broad categories: Affect, Behaviour, and Cognition (ABC), and the data was visualized in semantic maps. The maps reveal several knowledge pathways of ABC for developing attitudinal ontologies, which describe the relations between affect, behaviour and cognition, and the sequence in which they develop. Clearly, terrorist attacks induced trauma and people became highly vulnerable. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Operational tools to help stakeholders to protect and alert municipalities facing uncertainties and changes in karst flash floods

NASA Astrophysics Data System (ADS)

Borrell Estupina, V.; Raynaud, F.; Bourgeois, N.; Kong-A-Siou, L.; Collet, L.; Haziza, E.; Servat, E.

2015-06-01

Flash floods are often responsible for many deaths and involve many material damages. Regarding Mediterranean karst aquifers, the complexity of connections, between surface and groundwater, as well as weather non-stationarity patterns, increase difficulties in understanding the basins behaviour and thus warning and protecting people. Furthermore, given the recent changes in land use and extreme rainfall events, knowledge of the past floods is no longer sufficient to manage flood risks. Therefore the worst realistic flood that could occur should be considered. Physical and processes-based hydrological models are considered among the best ways to forecast floods under diverse conditions. However, they rarely match with the stakeholders' needs. In fact, the forecasting services, the municipalities, and the civil security have difficulties in running and interpreting data-consuming models in real-time, above all if data are uncertain or non-existent. To face these social and technical difficulties and help stakeholders, this study develops two operational tools derived from these models. These tools aim at planning real-time decisions given little, changing, and uncertain information available, which are: (i) a hydrological graphical tool (abacus) to estimate flood peak discharge from the karst past state and the forecasted but uncertain intense rainfall; (ii) a GIS-based method (MARE) to estimate the potential flooded pathways and areas, accounting for runoff and karst contributions and considering land use changes. Then, outputs of these tools are confronted to past and recent floods and municipalities observations, and the impacts of uncertainties and changes on planning decisions are discussed. The use of these tools on the recent 2014 events demonstrated their reliability and interest for stakeholders. This study was realized on French Mediterranean basins, in close collaboration with the Flood Forecasting Services (SPC Med-Ouest, SCHAPI, municipalities).

Solar irradiance assessment in insular areas using Himawari-8 satellite images

NASA Astrophysics Data System (ADS)

Liandrat, O.; Cros, S.; Turpin, M.; Pineau, J. F.

2016-12-01

The high amount of surface solar irradiance (SSI) in the tropics is an advantage for a profitable PV production. It will allow many tropical islands to pursue their economic growth with a clean, affordable and locally produced energy. However, the local meteorological conditions induce a very high variability which is problematic for a safe and gainful injection into the power grid. This issue is even more critical in non-interconnected territories where network stability is an absolute necessity. Therefore, the injection of PV power is legally limited in some European oversea territories. In this context, intraday irradiance forecasting (several hours ahead) is particularly useful to mitigate the production variability by reducing the cost of power storage management. At this time scale, cloud cover evolves with a stochastic behaviour not properly represented in numerical weather prediction (NWP) models. Analysing cloud motion using images from geostationary meteorological satellites is a well-known alternative to forecasting SSI up to 6 hours ahead with a better accuracy than NWP models. In this study, we present and apply our satellite-based solar irradiance forecasting methods over two measurement sites located in the field of view of the satellite Himawari-8: Cocos (Keeling) Islands (Australia) and New Caledonia (France). In particular, we converted 4 months of images from Himawari-8 visible channel into cloud index maps. Then, we applied an algorithm computing a cloud motion vector field from a short sequence of consecutive images. Comparisons between forecasted SSI at 1 hour of time horizon and collocated pyranometric measurements show a relative RMSE between 20 and 27%. Error sources related to the tropic insular context (coastal area heterogeneity, sub-pixel scale orographic cloud appearance, convective situation…) are discussed at every implementation step for the different methods.

Using multiple data sets to populate probabilistic volcanic event trees

USGS Publications Warehouse

Newhall, C.G.; Pallister, John S.

2014-01-01

The key parameters one needs to forecast outcomes of volcanic unrest are hidden kilometers beneath the Earth’s surface, and volcanic systems are so complex that there will invariably be stochastic elements in the evolution of any unrest. Fortunately, there is sufficient regularity in behaviour that some, perhaps many, eruptions can be forecast with enough certainty for populations to be evacuated and kept safe. Volcanologists charged with forecasting eruptions must try to understand each volcanic system well enough that unrest can be interpreted in terms of pre-eruptive process, but must simultaneously recognize and convey uncertainties in their assessment. We have found that use of event trees helps to focus discussion, integrate data from multiple sources, reach consensus among scientists about both pre-eruptive process and uncertainties and, in some cases, to explain all of this to officials. Figure 1 shows a generic volcanic event tree from Newhall and Hoblitt (2002) that can be modified as needed for each specific volcano. This paper reviews how we and our colleagues have used such trees during a number of volcanic crises worldwide, for rapid hazard assessments in situations in which more formal expert elicitations could not be conducted. We describe how Multiple Data Sets can be used to estimate probabilities at each node and branch. We also present case histories of probability estimation during crises, how the estimates were used by public officials, and some suggestions for future improvements.

Numerical and Statistical Analysis of Fractures in Mechanically Dissimilar Rocks of Limestone Interbedded with Shale from Nash Point in Bristol Channel, South Wales, UK.

NASA Astrophysics Data System (ADS)

Adeoye-Akinde, K.; Gudmundsson, A.

2017-12-01

Heterogeneity and anisotropy, especially with layered strata within the same reservoir, makes the geometry and permeability of an in-situ fracture network challenging to forecast. This study looks at outcrops analogous to reservoir rocks for a better understanding of in-situ fracture networks and permeability, especially fracture formation, propagation, and arrest/deflection. Here, fracture geometry (e.g. length and aperture) from interbedded limestone and shale is combined with statistical and numerical modelling (using the Finite Element Method) to better forecast fracture network properties and permeability. The main aim is to bridge the gap between fracture data obtained at the core level (cm-scale) and at the seismic level (km-scale). Analysis has been made of geometric properties of over 250 fractures from the blue Lias in Nash Point, UK. As fractures propagate, energy is required to keep them going, and according to the laws of thermodynamics, this energy can be linked to entropy. As fractures grow, entropy increases, therefore, the result shows a strong linear correlation between entropy and the scaling exponent of fracture length and aperture-size distributions. Modelling is used to numerically simulate the stress/fracture behaviour in mechanically dissimilar rocks. Results show that the maximum principal compressive stress orientation changes in the host rock as the fracture-induced stress tip moves towards a more compliant (shale) layer. This behaviour can be related to the three mechanisms of fracture arrest/deflection at an interface, namely: elastic mismatch, stress barrier and Cook-Gordon debonding. Tensile stress concentrates at the contact between the stratigraphic layers, ahead of and around the propagating fracture. However, as shale stiffens with time, the stresses concentrated at the contact start to dissipate into it. This can happen in nature through diagenesis, and with greater depth of burial. This study also investigates how induced fractures propagate and interact with existing discontinuities in layered rocks using analogue modelling. Further work will introduce the Maximum Entropy Method for more accurate statistical modelling. This method is mainly useful to forecast likely fracture-size probability distributions from incomplete subsurface information.

Teleconnection, Regime Shift, and Predictability of Climate Extremes: A Case Study for the Russian Heat Wave and Pakistan Flood in Summer 2010

NASA Technical Reports Server (NTRS)

Lau, W. K.; Reale, O.; Kim, K.

2011-01-01

In this talk, we present observational evidence showing that the two major extremes events of the summer of 2010, i.e., the Russian heat wave and the Pakistan flood were physically connected. We find that the Pakistan flood was contributed by a series of unusually heavy rain events over the upper Indus River Basin in July-August. The rainfall regimes shifted from an episodic heavy rain regime in mid-to-late July to a steady heavy rain regime in August. An atmospheric Rossby wave associated with the development of the Russian heat wave was instrumental in spurring the episodic rain events , drawing moisture from the Bay of Bengal and the northern Arabian Sea. The steady rain regime was maintained primarily by monsoon moisture surges from the deep tropics. From experiments with the GEOS-5 forecast system, we assess the predictability of the heavy rain events associated with the Pakistan flood. Preliminary results indicate that there are significantly higher skills in the rainfall forecasts during the episodic heavy rain events in July, compared to the steady rain period in early to mid-August. The change in rainfall predictability may be related to scale interactions between the extratropics and the tropics resulting in a modulation of rainfall predictability by the circulation regimes.

Health-seeking behaviour in Pakistan: a narrative review of the existing literature.

PubMed

Anwar, M; Green, J; Norris, P

2012-06-01

This narrative review was carried out to collate the work of researchers on health-seeking behaviour in Pakistan, to discuss the methods used, highlight the emerging themes and identify areas that have yet to be studied. Review. An overview of studies on health-seeking behaviour in Pakistan, found via searches on scholarly databases intended to locate material of medical and anthropological relevance. In total, 29 articles were reviewed with a range of different methodologies. A retrospective approach was the most common. A variety of medical conditions have been studied in terms of health-seeking behaviour of people experiencing such conditions. However, a wide range of chronic illnesses have yet to be studied. Nevertheless, some studies highlighting unusual issues such as snake bites and health-seeking behaviour of street children were also found. In terms of geographical area, the majority of studies reviewed were performed in the provinces of Sind and Punjab, with little research targeting the people from the two other provinces (Balochistan and Khyber Pakhtunkhwa) of Pakistan. Predominant utilization of private healthcare facilities, self-medication, involvement of traditional healers in the healthcare system, women's autonomy, and superstitions and fallacies associated with health-seeking behaviour were found to be the themes that repeatedly emerged in the literature reviewed. The sociocultural and religious background of Pakistan means that health-seeking behaviour resembles a mosaic. There is a need to improve the quality of service provided by the public healthcare sector and the recruitment of female staff. Traditional healers should be trained and integrated into the mainstream to provide adequate healthcare. Serious efforts are required to increase the awareness and educational level of the public, especially women in rural areas, in order to fight against myths and superstitions associated with health-seeking behaviour. Copyright © 2012 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Application of bayesian networks to real-time flood risk estimation

NASA Astrophysics Data System (ADS)

Garrote, L.; Molina, M.; Blasco, G.

2003-04-01

This paper presents the application of a computational paradigm taken from the field of artificial intelligence - the bayesian network - to model the behaviour of hydrologic basins during floods. The final goal of this research is to develop representation techniques for hydrologic simulation models in order to define, develop and validate a mechanism, supported by a software environment, oriented to build decision models for the prediction and management of river floods in real time. The emphasis is placed on providing decision makers with tools to incorporate their knowledge of basin behaviour, usually formulated in terms of rainfall-runoff models, in the process of real-time decision making during floods. A rainfall-runoff model is only a step in the process of decision making. If a reliable rainfall forecast is available and the rainfall-runoff model is well calibrated, decisions can be based mainly on model results. However, in most practical situations, uncertainties in rainfall forecasts or model performance have to be incorporated in the decision process. The computation paradigm adopted for the simulation of hydrologic processes is the bayesian network. A bayesian network is a directed acyclic graph that represents causal influences between linked variables. Under this representation, uncertain qualitative variables are related through causal relations quantified with conditional probabilities. The solution algorithm allows the computation of the expected probability distribution of unknown variables conditioned to the observations. An approach to represent hydrologic processes by bayesian networks with temporal and spatial extensions is presented in this paper, together with a methodology for the development of bayesian models using results produced by deterministic hydrologic simulation models

The link between behavioural type and natal dispersal propensity reveals a dispersal syndrome in a large herbivore

PubMed Central

Debeffe, L.; Morellet, N.; Bonnot, N.; Gaillard, J. M.; Cargnelutti, B.; Verheyden-Tixier, H.; Vanpé, C.; Coulon, A.; Clobert, J.; Bon, R.; Hewison, A. J. M.

2014-01-01

When individuals disperse, they modify the physical and social composition of their reproductive environment, potentially impacting their fitness. The choice an individual makes between dispersal and philopatry is thus critical, hence a better understanding of the mechanisms involved in the decision to leave the natal area is crucial. We explored how combinations of behavioural (exploration, mobility, activity and stress response) and morphological (body mass) traits measured prior to dispersal were linked to the subsequent dispersal decision in 77 roe deer Capreolus capreolus fawns. Using an unusually detailed multi-trait approach, we identified two independent behavioural continuums related to dispersal. First, a continuum of energetic expenditure contrasted individuals of low mobility, low variability in head activity and low body temperature with those that displayed opposite traits. Second, a continuum of neophobia contrasted individuals that explored more prior to dispersal and were more tolerant of capture with those that displayed opposite traits. While accounting for possible confounding effects of condition-dependence (body mass), we showed that future dispersers were less neophobic and had higher energetic budgets than future philopatric individuals, providing strong support for a dispersal syndrome in this species. PMID:25030983

Doping-induced disappearance of ice II from water's phase diagram

NASA Astrophysics Data System (ADS)

Shephard, Jacob J.; Slater, Ben; Harvey, Peter; Hart, Martin; Bull, Craig L.; Bramwell, Steven T.; Salzmann, Christoph G.

2018-06-01

Water and the many phases of ice display a plethora of complex physical properties and phase relationships1-4 that are of paramount importance in a range of settings including processes in Earth's hydrosphere, the geology of icy moons, industry and even the evolution of life. Well-known examples include the unusual behaviour of supercooled water2, the emergent ferroelectric ordering in ice films4 and the fact that the `ordinary' ice Ih floats on water. We report the intriguing observation that ice II, one of the high-pressure phases of ice, disappears in a selective fashion from water's phase diagram following the addition of small amounts of ammonium fluoride. This finding exposes the strict topologically constrained nature of the ice II hydrogen-bond network, which is not found for the competing phases. In analogy to the behaviour of frustrated magnets5, the presence of the exceptional ice II is argued to have a wider impact on water's phase diagram, potentially explaining its general tendency to display anomalous behaviour. Furthermore, the impurity-induced disappearance of ice II raises the prospect that specific dopants may not only be able to suppress certain phases but also induce the formation of new phases of ice in future studies.

Chimpanzees are indifferent to the welfare of unrelated group members.

PubMed

Silk, Joan B; Brosnan, Sarah F; Vonk, Jennifer; Henrich, Joseph; Povinelli, Daniel J; Richardson, Amanda S; Lambeth, Susan P; Mascaro, Jenny; Schapiro, Steven J

2005-10-27

Humans are an unusually prosocial species-we vote, give blood, recycle, give tithes and punish violators of social norms. Experimental evidence indicates that people willingly incur costs to help strangers in anonymous one-shot interactions, and that altruistic behaviour is motivated, at least in part, by empathy and concern for the welfare of others (hereafter referred to as other-regarding preferences). In contrast, cooperative behaviour in non-human primates is mainly limited to kin and reciprocating partners, and is virtually never extended to unfamiliar individuals. Here we present experimental tests of the existence of other-regarding preferences in non-human primates, and show that chimpanzees (Pan troglodytes) do not take advantage of opportunities to deliver benefits to familiar individuals at no material cost to themselves, suggesting that chimpanzee behaviour is not motivated by other-regarding preferences. Chimpanzees are among the primates most likely to demonstrate prosocial behaviours. They participate in a variety of collective activities, including territorial patrols, coalitionary aggression, cooperative hunting, food sharing and joint mate guarding. Consolation of victims of aggression and anecdotal accounts of solicitous treatment of injured individuals suggest that chimpanzees may feel empathy. Chimpanzees sometimes reject exchanges in which they receive less valuable rewards than others, which may be one element of a 'sense of fairness', but there is no evidence that they are averse to interactions in which they benefit more than others.

Numerical Modelling of Fire-Atmosphere Interactions and the 2003 Canberra Bushfires

NASA Astrophysics Data System (ADS)

Simpson, C.; Sturman, A.; Zawar-Reza, P.

2010-12-01

It is well known that the behaviour of a wildland fire is strongly associated with the conditions of its surrounding atmosphere. However, the two-way interactions between fire behaviour and the atmospheric conditions are not well understood. A numerical model is used to simulate wildland fires so that the nature of these fire-atmosphere interactions, and how they might affect fire behaviour, can be further investigated. The 2003 Canberra bushfires are used as a case study due to their highly destructive and unusual behaviour. On the 18th January 2003, these fires spread to the urban suburbs of Canberra, resulting in the loss of four lives and the destruction of over 500 homes. Fire-atmosphere interactions are believed to have played an important role in making these fires so destructive. WRF-Fire is used to perform real data simulations of the 2003 Canberra bushfires. WRF-Fire is a coupled fire-atmosphere model, which combines a semi-empirical fire spread model with an atmospheric model, allowing it to directly simulate the two-way interactions between a fire and its surrounding atmosphere. These simulations show the impact of the presence of a fire on conditions within the atmospheric boundary layer. This modification of the atmosphere, resulting from the injection of heat and moisture released by the fire, appears to have a direct feedback onto the overall fire behaviour. The bushfire simulations presented in this paper provide important scientific insights into the nature of fire-atmosphere interactions for a real situation. It is expected that they will also help fire managers in Australia to better understand why the 2003 Canberra bushfires were so destructive, as well as to gain improved insight into bushfire behaviour in general.

Simulating the propagation of sulphur dioxide emissions from the fissure eruption in the Holuhraun lava field (Iceland) with the EURAD-IM

NASA Astrophysics Data System (ADS)

Fröhlich, Luise; Franke, Philipp; Friese, Elmar; Haas, Sarah; Lange, Anne Caroline; Elbern, Hendrik

2015-04-01

In the emergency case of a volcano eruption accurate forecasts of the transport of ash and gas emissions are crucial for health protection and aviation safety. In the frame of Earth System Knowledge Platform (ESKP) near real-time forecasts of ash and SO2 dispersion emitted by active volcanoes are simulated by the European Air pollution Dispersion Inverse Model (EURAD-IM). The model is driven by the Weather Research and Forecasting Model (WRF) and includes detailed gas phase and particle dynamics modules, which allow for quantitative estimates of measured volcano releases. Former simulations, for example related to the Eyjafjallajökull outbreak in 2010, were in good agreement with measurement records of particle number and SO2 at several European stations. At the end of August 2014 an fissure eruption has begun on Iceland in the Holuhraun lava field to the north-east of the Bardarbunga volcano system. In contrast to the explosive eruption of the Eyjafjallajökull in 2010, the Holuhraun eruption is rather effusive with a large and continuous flow of lava and a significant release of sulphur dioxide (SO2) in the lower troposphere, while ash emissions are insignificant. Since the Holuhraun fissure eruption has started, daily forecasts of SO2 dispersion are produced for the European region (15 km horizontal resolution grid) and published on our website (http://apps.fz-juelich.de/iek-8/RIU/vorhersage_node.php). To simulate the transport of volcanic emissions, realistic source terms like mass release rates of ash and SO2 or plume heights are required. Since no representative measurements are currently available for the simulations, rough qualitative assumptions, based on reports from the Icelandic Met Office (IMO), are used. However, frequent comparisons with satellite observations show that the actual propagation of the volcanic emissions is generally well reflected by the model. In the middle of September 2014 several European measurement sides recorded extremely high SO2 concentrations at ground level which were predicted quite accurately in advance by the EURAD-IM. Further more, the simulations indicate that the unusual high SO2 values are due to the transport of sulphur dioxide rich air from the Bardarbunga towards continental Europe. Presently, SO2 dispersion forecasts are also conducted on a finer spatial resolution grid (1 km) for the Icelandic region. These simulations will be validated against measurements from different observation sides in Iceland.

Transport mechanisms in Schottky diodes realized on GaN

NASA Astrophysics Data System (ADS)

Amor, Sarrah; Ahaitouf, Ali; Ahaitouf, Abdelaziz; Salvestrini, Jean Paul; Ougazzaden, Abdellah

2017-03-01

This work is focused on the conducted transport mechanisms involved on devices based in gallium nitride GaN and its alloys. With considering all conduction mechanisms of current, its possible to understanded these transport phenomena. Thanks to this methodology the current-voltage characteristics of structures with unusual behaviour are further understood and explain. Actually, the barrier height (SBH) is a complex problem since it depends on several parameters like the quality of the metal-semiconductor interface. This study is particularly interesting as solar cells are made on this material and their qualification is closely linked to their transport properties.

Conceiving processes in atmospheric models-General equations, subscale parameterizations, and 'superparameterizations'

NASA Astrophysics Data System (ADS)

Gramelsberger, Gabriele

The scientific understanding of atmospheric processes has been rooted in the mechanical and physical view of nature ever since dynamic meteorology gained ground in the late 19th century. Conceiving the atmosphere as a giant 'air mass circulation engine' entails applying hydro- and thermodynamical theory to the subject in order to describe the atmosphere's behaviour on small scales. But when it comes to forecasting, it turns out that this view is far too complex to be computed. The limitation of analytical methods precludes an exact solution, forcing scientists to make use of numerical simulation. However, simulation introduces two prerequisites to meteorology: First, the partitioning of the theoretical view into two parts-the large-scale behaviour of the atmosphere, and the effects of smaller-scale processes on this large-scale behaviour, so-called parametrizations; and second, the dependency on computational power in order to achieve a higher resolution. The history of today's atmospheric circulation modelling can be reconstructed as the attempt to improve the handling of these basic constraints. It can be further seen as the old schism between theory and application under new circumstances, which triggers a new discussion about the question of how processes may be conceived in atmospheric modelling.

Fatigue behaviour analysis for the durability prequalification of strengthening mortars

NASA Astrophysics Data System (ADS)

Bocca, P.; Grazzini, A.; Masera, D.

2011-07-01

An innovative laboratory procedure used as a preliminary design stage for the pre-qualification of strengthening mortars applied to historical masonry buildings is described. In the analysis of the behaviour of masonry structures and their constituent materials, increasing importance has been assumed by the study of the long-term evolution of deformation and mechanical characteristics, which may be affected by both loading and environmental conditions. Through static and fatigue tests on mixed specimens historical brick-reinforced mortar it has been possible to investigate the durability of strengthening materials, in order to select, from a range of alternatives, the most suitable for the historical masonry. Cyclic fatigue stress has been applied to accelerate the static creep and to forecast the corresponding creep behaviour of the historical brick-strengthening mortar system under static long-time loading. This methodology has proved useful in avoiding the errors associated with materials that are not mechanically compatible and guarantees the durability of strengthening work. The experimental procedure has been used effectively in the biggest restoration building site in Europe, the Royal Palace of Venaria, and it is in progress of carrying out at the Special Natural Reserve of the Sacro Monte di Varallo, in Piedmont (Italy).

The effect of a prudent adaptive behaviour on disease transmission

NASA Astrophysics Data System (ADS)

Scarpino, Samuel V.; Allard, Antoine; Hébert-Dufresne, Laurent

2016-11-01

The spread of disease can be slowed by certain aspects of real-world social networks, such as clustering and community structure, and of human behaviour, including social distancing and increased hygiene, many of which have already been studied. Here, we consider a model in which individuals with essential societal roles--be they teachers, first responders or health-care workers--fall ill, and are replaced with healthy individuals. We refer to this process as relational exchange, and incorporate it into a dynamic network model to demonstrate that replacing individuals can accelerate disease transmission. We find that the effects of this process are trivial in the context of a standard mass-action model, but dramatic when considering network structure, featuring accelerating spread, discontinuous transitions and hysteresis loops. This result highlights the inability of mass-action models to account for many behavioural processes. Using empirical data, we find that this mechanism parsimoniously explains observed patterns across 17 influenza outbreaks in the USA at a national level, 25 years of influenza data at the state level, and 19 years of dengue virus data from Puerto Rico. We anticipate that our findings will advance the emerging field of disease forecasting and better inform public health decision making during outbreaks.

Weather forecasting by insects: modified sexual behaviour in response to atmospheric pressure changes.

PubMed

Pellegrino, Ana Cristina; Peñaflor, Maria Fernanda Gomes Villalba; Nardi, Cristiane; Bezner-Kerr, Wayne; Guglielmo, Christopher G; Bento, José Maurício Simões; McNeil, Jeremy N

2013-01-01

Prevailing abiotic conditions may positively or negatively impact insects at both the individual and population levels. For example while moderate rainfall and wind velocity may provide conditions that favour development, as well as movement within and between habitats, high winds and heavy rains can significantly decrease life expectancy. There is some evidence that insects adjust their behaviours associated with flight, mating and foraging in response to changes in barometric pressure. We studied changes in different mating behaviours of three taxonomically unrelated insects, the curcurbit beetle, Diabrotica speciosa (Coleoptera), the true armyworm moth, Pseudaletia unipuncta (Lepidoptera) and the potato aphid, Macrosiphum euphorbiae (Hemiptera), when subjected to natural or experimentally manipulated changes in atmospheric pressure. In response to decreasing barometric pressure, male beetles exhibited decreased locomotory activity in a Y-tube olfactometer with female pheromone extracts. However, when placed in close proximity to females, they exhibited reduced courtship sequences and the precopulatory period. Under the same situations, females of the true armyworm and the potato aphid exhibited significantly reduced calling behaviour. Neither the movement of male beetles nor the calling of armyworm females differed between stable and increasing atmospheric pressure conditions. However, in the case of the armyworm there was a significant decrease in the incidence of mating under rising atmospheric conditions, suggesting an effect on male behaviour. When atmospheric pressure rose, very few M. euphorbiae oviparae called. This was similar to the situation observed under decreasing conditions, and consequently very little mating was observed in this species except under stable conditions. All species exhibited behavioural modifications, but there were interspecific differences related to size-related flight ability and the diel periodicity of mating activity. We postulate that the observed behavioral modifications, especially under decreasing barometric pressure would reduce the probability of injury or death under adverse weather conditions.

Electron Reconfiguration and Enhanced Phonon Activation in the Superconducting State of a FeSe0.3Te0.7 Single Crystal, as Evidenced by Mössbauer Spectroscopy

NASA Astrophysics Data System (ADS)

Greculeasa, Simona; Miu, Lucica; Badica, Petre; Nie, Jiacai; Tolea, Mugurel; Kuncser, Victor

2015-01-01

The Mössbauer spectra of a FeSe0.3Te0.7 single crystal grown by the Bridgman method were analysed across the superconducting transition by considering the interplay between the structure and electron configuration of the transition metal. The magnetically determined superconducting critical temperature is TC ˜ 14 K. The 57Fe Mössbauer spectra collected in the temperature range from 5 to 200 K mainly have an asymmetric doublet pattern, which was conveniently fitted by the full Hamiltonian method. No effective magnetic moment ascribed to the superconducting phase was observed down to 5 K. The unusual behaviour observed below ˜17 K for the chemical isomer shift and quadrupole splitting may be associated with an electron reconfiguration process intimately related to an unusual lattice distortion accompanying the superconducting transition. The decreasing trend of the total absorption spectral area and second-order Doppler shift during cooling the sample below the critical temperature, point to enhanced phonon activation in the superconducting state.

Vortex arrays and ciliary tangles underlie the feeding-swimming trade-off in starfish larvae

NASA Astrophysics Data System (ADS)

Gilpin, William; Prakash, Vivek N.; Prakash, Manu

2017-04-01

Many marine invertebrates have larval stages covered in linear arrays of beating cilia, which propel the animal while simultaneously entraining planktonic prey. These bands are strongly conserved across taxa spanning four major superphyla, and they are responsible for the unusual morphologies of many invertebrate larvae. However, few studies have investigated their underlying hydrodynamics. Here, we study the ciliary bands of starfish larvae, and discover a beautiful pattern of slowly evolving vortices that surrounds the swimming animals. Closer inspection of the bands reveals unusual ciliary `tangles' analogous to topological defects that break up and re-form as the animal adjusts its swimming stroke. Quantitative experiments and modelling demonstrate that these vortices create a physical trade-off between feeding and swimming in heterogeneous environments, which manifests as distinct flow patterns or `eigenstrokes' representing each behaviour--potentially implicating neuronal control of cilia. This quantitative interplay between larval form and hydrodynamic function may generalize to other invertebrates with ciliary bands, and illustrates the potential effects of active boundary conditions in other biological and synthetic systems.

Use of mammal manure by nesting burrowing owls: a test of four functional hypotheses

USGS Publications Warehouse

Smith, M.D.; Conway, C.J.

2007-01-01

Animals have evolved an impressive array of behavioural traits to avoid depredation. Olfactory camouflage of conspicuous odours is a strategy to avoid depredation that has been implicated only in a few species of birds. Burrowing owls, Athene cunicularia, routinely collect dried manure from mammals and scatter it in their nest chamber, in the tunnel leading to their nest and at the entrance to their nesting burrow. This unusual behaviour was thought to reduce nest depredation by concealing the scent of adults and juveniles, but a recent study suggests that manure functions to attract arthropod prey. However, burrowing owls routinely scatter other materials in the same way that they scatter manure, and this fact seems to be at odds with both of these hypotheses. Thus, we examined the function of this behaviour by testing four alternative hypotheses. We found no support for the widely cited olfactory-camouflage hypothesis (manure did not lower the probability of depredation), or for the mate-attraction hypothesis (males collected manure after, not before, pair formation). Predictions of the burrow-occupied hypothesis (manure indicates occupancy to conspecifics and thereby reduces agonistic interactions) were supported, but results were not statistically significant. Our results also supported several predictions of the prey-attraction hypothesis. Pitfall traps at sampling sites with manure collected more arthropod biomass (of taxa common in the diet of burrowing owls) than pitfall traps at sampling sites without manure. Scattering behaviour of burrowing owls appears to function to attract arthropod prey, but may also signal occupancy of a burrow to conspecifics. ?? 2006 The Association for the Study of Animal Behaviour.

Big data in fashion industry

NASA Astrophysics Data System (ADS)

Jain, S.; Bruniaux, J.; Zeng, X.; Bruniaux, P.

2017-10-01

Significant work has been done in the field of big data in last decade. The concept of big data includes analysing voluminous data to extract valuable information. In the fashion world, big data is increasingly playing a part in trend forecasting, analysing consumer behaviour, preference and emotions. The purpose of this paper is to introduce the term fashion data and why it can be considered as big data. It also gives a broad classification of the types of fashion data and briefly defines them. Also, the methodology and working of a system that will use this data is briefly described.

Multi-objective optimization of GENIE Earth system models.

PubMed

Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J

2009-07-13

The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

A Probabilistic Assessment of the Next Geomagnetic Reversal

NASA Astrophysics Data System (ADS)

Buffett, Bruce; Davis, William

2018-02-01

Deterministic forecasts for the next geomagnetic reversal are not feasible due to large uncertainties in the present-day state of the Earth's core. A more practical approach relies on probabilistic assessments using paleomagnetic observations to characterize the amplitude of fluctuations in the geomagnetic dipole. We use paleomagnetic observations for the past 2 Myr to construct a stochastic model for the axial dipole field and apply well-established methods to evaluate the probability of the next geomagnetic reversal as a function of time. For a present-day axial dipole moment of 7.6 × 1022 A m2, the probability of the dipole entering a reversed state is less than 2% after 20 kyr. This probability rises to 11% after 50 kyr. An imminent geomagnetic reversal is not supported by paleomagnetic observations. The current rate of decline in the dipole moment is unusual but within the natural variability predicted by the stochastic model.

A twenty-first century California observing network for monitoring extreme weather events

USGS Publications Warehouse

White, A.B.; Anderson, M.L.; Dettinger, M.D.; Ralph, F.M.; Hinojosa, A.; Cayan, D.R.; Hartman, R.K.; Reynolds, D.W.; Johnson, L.E.; Schneider, T.L.; Cifelli, R.; Toth, Z.; Gutman, S.I.; King, C.W.; Gehrke, F.; Johnston, P.E.; Walls, C.; Mann, Dorte; Gottas, D.J.; Coleman, T.

2013-01-01

During Northern Hemisphere winters, the West Coast of North America is battered by extratropical storms. The impact of these storms is of paramount concern to California, where aging water supply and flood protection infrastructures are challenged by increased standards for urban flood protection, an unusually variable weather regime, and projections of climate change. Additionally, there are inherent conflicts between releasing water to provide flood protection and storing water to meet requirements for water supply, water quality, hydropower generation, water temperature and flow for at-risk species, and recreation. In order to improve reservoir management and meet the increasing demands on water, improved forecasts of precipitation, especially during extreme events, is required. Here we describe how California is addressing their most important and costliest environmental issue – water management – in part, by installing a state-of-the-art observing system to better track the area’s most severe wintertime storms.

A temporal and spatial analysis of ground-water levels for effective monitoring in Huron County, Michigan

USGS Publications Warehouse

Holtschlag, David J.; Sweat, M.J.

1999-01-01

Quarterly water-level measurements were analyzed to assess the effectiveness of a monitoring network of 26 wells in Huron County, Michigan. Trends were identified as constant levels and autoregressive components were computed at all wells on the basis of data collected from 1993 to 1997, using structural time series analysis. Fixed seasonal components were identified at 22 wells and outliers were identified at 23 wells. The 95- percent confidence intervals were forecast for water-levels during the first and second quarters of 1998. Intervals in the first quarter were consistent with 92.3 percent of the measured values. In the second quarter, measured values were within the forecast intervals only 65.4 percent of the time. Unusually low precipitation during the second quarter is thought to have contributed to the reduced reliability of the second-quarter forecasts. Spatial interrelations among wells were investigated on the basis of the autoregressive components, which were filtered to create a set of innovation sequences that were temporally uncorrelated. The empirical covariance among the innovation sequences indicated both positive and negative spatial interrelations. The negative covariance components are considered to be physically implausible and to have resulted from random sampling error. Graphical modeling, a form of multivariate analysis, was used to model the covariance structure. Results indicate that only 29 of the 325 possible partial correlations among the water-level innovations were statistically significant. The model covariance matrix, corresponding to the model partial correlation structure, contained only positive elements. This model covariance was sequentially partitioned to compute a set of partial covariance matrices that were used to rank the effectiveness of the 26 monitoring wells from greatest to least. Results, for example, indicate that about 50 percent of the uncertainty of the water-level innovations currently monitored by the 26- well network could be described by the 6 most effective wells.

Project Ukko - Design of a climate service visualisation interface for seasonal wind forecasts

NASA Astrophysics Data System (ADS)

Hemment, Drew; Stefaner, Moritz; Makri, Stephann; Buontempo, Carlo; Christel, Isadora; Torralba-Fernandez, Veronica; Gonzalez-Reviriego, Nube; Doblas-Reyes, Francisco; de Matos, Paula; Dykes, Jason

2016-04-01

Project Ukko is a prototype climate service to visually communicate probabilistic seasonal wind forecasts for the energy sector. In Project Ukko, an interactive visualisation enhances the accessibility and readability to the latests advances in seasonal wind speed predictions developed as part of the RESILIENCE prototype of the EUPORIAS (EC FP7) project. Climate services provide made-to-measure climate information, tailored to the specific requirements of different users and industries. In the wind energy sector, understanding of wind conditions in the next few months has high economic value, for instance, for the energy traders. Current energy practices use retrospective climatology, but access to reliable seasonal predictions based in the recent advances in global climate models has potential to improve their resilience to climate variability and change. Despite their potential benefits, a barrier to the development of commercially viable services is the complexity of the probabilistic forecast information, and the challenge of communicating complex and uncertain information to decision makers in industry. Project Ukko consists of an interactive climate service interface for wind energy users to explore probabilistic wind speed predictions for the coming season. This interface enables fast visual detection and exploration of interesting features and regions likely to experience unusual changes in wind speed in the coming months.The aim is not only to support users to better understand the future variability in wind power resources, but also to bridge the gap between practitioners' traditional approach and the advanced prediction systems developed by the climate science community. Project Ukko is presented as a case study of cross-disciplinary collaboration between climate science and design, for the development of climate services that are useful, usable and effective for industry users. The presentation will reflect on the challenge of developing a climate service for industry users in the wind energy sector, the background to this challenge, our approach, and the evaluation of the visualisation interface.

Impacts of aerosol-monsoon interaction on rainfall and circulation over Northern India and the Himalaya Foothills

NASA Astrophysics Data System (ADS)

Lau, William K. M.; Kim, Kyu-Myong; Shi, Jainn-Jong; Matsui, T.; Chin, M.; Tan, Qian; Peters-Lidard, C.; Tao, W. K.

2017-09-01

The boreal summer of 2008 was unusual for the Indian monsoon, featuring exceptional heavy loading of dust aerosols over the Arabian Sea and northern-central India, near normal all-India rainfall, but excessive heavy rain, causing disastrous flooding in the Northern Indian Himalaya Foothills (NIHF) regions, accompanied by persistent drought conditions in central and southern India. Using the NASA Unified-physics Weather Research Forecast (NUWRF) model with fully interactive aerosol physics and dynamics, we carried out three sets of 7-day ensemble model forecast experiments: (1) control with no aerosol, (2) aerosol radiative effect only and (3) aerosol radiative and aerosol-cloud-microphysics effects, to study the impacts of aerosol-monsoon interactions on monsoon variability over the NIHF during the summer of 2008. Results show that aerosol-radiation interaction (ARI), i.e., dust aerosol transport, and dynamical feedback processes induced by aerosol-radiative heating, plays a key role in altering the large-scale monsoon circulation system, reflected by an increased north-south tropospheric temperature gradient, a northward shift of heavy monsoon rainfall, advancing the monsoon onset by 1-5 days over the HF, consistent with the EHP hypothesis (Lau et al. in Clim Dyn 26(7-8):855-864, 2006). Additionally, we found that dust aerosols, via the semi-direct effect, increase atmospheric stability, and cause the dissipation of a developing monsoon onset cyclone over northeastern India/northern Bay of Bengal. Eventually, in a matter of several days, ARI transforms the developing monsoon cyclone into meso-scale convective cells along the HF slopes. Aerosol-Cloud-microphysics Interaction (ACI) further enhances the ARI effect in invigorating the deep convection cells and speeding up the transformation processes. Results indicate that even in short-term (up to weekly) numerical forecasting of monsoon circulation and rainfall, effects of aerosol-monsoon interaction can be substantial and cannot be ignored.

A sinuous tumulus over an active lava tube at Kīlauea Volcano: evolution, analogs, and hazard forecasts

USGS Publications Warehouse

Orr, Tim R.; Bleacher, Jacob E.; Patrick, Matthew R.; Wooten, Kelly M.

2015-01-01

Inflation of narrow tube-fed basaltic lava flows (tens of meters across), such as those confined by topography, can be focused predominantly along the roof of a lava tube. This can lead to the development of an unusually long tumulus, its shape matching the sinuosity of the underlying lava tube. Such a situation occurred during Kīlauea Volcano's (Hawai'i, USA) ongoing East Rift Zone eruption on a lava tube active from July through November 2010. Short-lived breakouts from the tube buried the flanks of the sinuous, ridge-like tumulus, while the tumulus crest, its surface composed of lava formed very early in the flow's emplacement history, remained poised above the surrounding younger flows. At least several of these breakouts resulted in irrecoverable uplift of the tube roof. Confined sections of the prehistoric Carrizozo and McCartys flows (New Mexico, USA) display similar sinuous, ridge-like features with comparable surface age relationships. We contend that these distinct features formed in a fashion equivalent to that of the sinuous tumulus that formed at Kīlauea in 2010. Moreover, these sinuous tumuli may be analogs for some sinuous ridges evident in orbital images of the Tharsis volcanic province on Mars. The short-lived breakouts from the sinuous tumulus at Kīlauea were caused by surges in discharge through the lava tube, in response to cycles of deflation and inflation (DI events) at Kīlauea's summit. The correlation between DI events and subsequent breakouts aided in lava flow forecasting. Breakouts from the sinuous tumulus advanced repeatedly toward the sparsely populated Kalapana Gardens subdivision, destroying two homes and threatening others. Hazard assessments, including flow occurrence and advance forecasts, were relayed regularly to the Hawai'i County Civil Defense to aid their lava flow hazard mitigation efforts while this lava tube was active.

A sinuous tumulus over an active lava tube at Kīlauea Volcano: Evolution, analogs, and hazard forecasts

NASA Astrophysics Data System (ADS)

Orr, Tim R.; Bleacher, Jacob E.; Patrick, Matthew R.; Wooten, Kelly M.

2015-01-01

Inflation of narrow tube-fed basaltic lava flows (tens of meters across), such as those confined by topography, can be focused predominantly along the roof of a lava tube. This can lead to the development of an unusually long tumulus, its shape matching the sinuosity of the underlying lava tube. Such a situation occurred during Kīlauea Volcano's (Hawai'i, USA) ongoing East Rift Zone eruption on a lava tube active from July through November 2010. Short-lived breakouts from the tube buried the flanks of the sinuous, ridge-like tumulus, while the tumulus crest, its surface composed of lava formed very early in the flow's emplacement history, remained poised above the surrounding younger flows. At least several of these breakouts resulted in irrecoverable uplift of the tube roof. Confined sections of the prehistoric Carrizozo and McCartys flows (New Mexico, USA) display similar sinuous, ridge-like features with comparable surface age relationships. We contend that these distinct features formed in a fashion equivalent to that of the sinuous tumulus that formed at Kīlauea in 2010. Moreover, these sinuous tumuli may be analogs for some sinuous ridges evident in orbital images of the Tharsis volcanic province on Mars. The short-lived breakouts from the sinuous tumulus at Kīlauea were caused by surges in discharge through the lava tube, in response to cycles of deflation and inflation (DI events) at Kīlauea's summit. The correlation between DI events and subsequent breakouts aided in lava flow forecasting. Breakouts from the sinuous tumulus advanced repeatedly toward the sparsely populated Kalapana Gardens subdivision, destroying two homes and threatening others. Hazard assessments, including flow occurrence and advance forecasts, were relayed regularly to the Hawai'i County Civil Defense to aid their lava flow hazard mitigation efforts while this lava tube was active.

Ferromagnetism induced by entangled charge and orbital orderings in ferroelectric titanate perovskites

PubMed Central

Bristowe, N. C.; Varignon, J.; Fontaine, D.; Bousquet, E.; Ghosez, Ph.

2015-01-01

In magnetic materials, the Pauli exclusion principle typically drives anti-alignment between electron spins on neighbouring species resulting in antiferromagnetic behaviour. Ferromagnetism exhibiting spontaneous spin alignment is a fairly rare behaviour, but once materialized is often associated with itinerant electrons in metals. Here we predict and rationalize robust ferromagnetism in an insulating oxide perovskite structure based on the popular titanate series. In half-doped layered titanates, the combination of Jahn–Teller and oxygen breathing motions opens a band gap and creates an unusual charge and orbital ordering of the Ti d electrons. It is argued that this intriguingly intricate electronic network favours the elusive inter-site ferromagnetic (FM) ordering, on the basis of intra-site Hund's rules. Finally, we find that the layered oxides are also ferroelectric with a spontaneous polarization approaching that of BaTiO3. The concepts are general and design principles of the technologically desirable FM ferroelectric multiferroics are presented. PMID:25807180

Flood alert system based on bayesian techniques

NASA Astrophysics Data System (ADS)

Gulliver, Z.; Herrero, J.; Viesca, C.; Polo, M. J.

2012-04-01

The problem of floods in the Mediterranean regions is closely linked to the occurrence of torrential storms in dry regions, where even the water supply relies on adequate water management. Like other Mediterranean basins in Southern Spain, the Guadalhorce River Basin is a medium sized watershed (3856 km2) where recurrent yearly floods occur , mainly in autumn and spring periods, driven by cold front phenomena. The torrential character of the precipitation in such small basins, with a concentration time of less than 12 hours, produces flash flood events with catastrophic effects over the city of Malaga (600000 inhabitants). From this fact arises the need for specific alert tools which can forecast these kinds of phenomena. Bayesian networks (BN) have been emerging in the last decade as a very useful and reliable computational tool for water resources and for the decision making process. The joint use of Artificial Neural Networks (ANN) and BN have served us to recognize and simulate the two different types of hydrological behaviour in the basin: natural and regulated. This led to the establishment of causal relationships between precipitation, discharge from upstream reservoirs, and water levels at a gauging station. It was seen that a recurrent ANN model working at an hourly scale, considering daily precipitation and the two previous hourly values of reservoir discharge and water level, could provide R2 values of 0.86. BN's results slightly improve this fit, but contribute with uncertainty to the prediction. In our current work to Design a Weather Warning Service based on Bayesian techniques the first steps were carried out through an analysis of the correlations between the water level and rainfall at certain representative points in the basin, along with the upstream reservoir discharge. The lower correlation found between precipitation and water level emphasizes the highly regulated condition of the stream. The autocorrelations of the variables were also analyzed, where the water level, with time lags of 12 hours related to the concentration time, was found to be most significant. In short, the fits to the different distribution functions of extremes were unsatisfactory, as the data were of poor quality and scant. This problem with data is not unusual in small and medium sized Mediterranean basins and becomes the real challenge to any prediction system based only on statistical methods. The aim of the resulting tool is to develop and maintain a numerical short-range weather forecasting system for operational use by the regional water management entities. The development of this tool is also corroborated by recent survey results, which identify the need to develop site specific models for water management in these Mediterranean regions, so prone to flash flood events (NOVIWAM, 2011 Novel Integrated Water Management systems for Southern European Regions, Seventh Framework Programme, EC, 2010-2013).

Forecasting Geomagnetic Activity Using Kalman Filters

NASA Astrophysics Data System (ADS)

Veeramani, T.; Sharma, A.

2006-05-01

The coupling of energy from the solar wind to the magnetosphere leads to the geomagnetic activity in the form of storms and substorms and are characterized by indices such as AL, Dst and Kp. The geomagnetic activity has been predicted near-real time using local linear filter models of the system dynamics wherein the time series of the input solar wind and the output magnetospheric response were used to reconstruct the phase space of the system by a time-delay embedding technique. Recently, the radiation belt dynamics have been studied using a adaptive linear state space model [Rigler et al. 2004]. This was achieved by assuming a linear autoregressive equation for the underlying process and an adaptive identification of the model parameters using a Kalman filter approach. We use such a model for predicting the geomagnetic activity. In the case of substorms, the Bargatze et al [1985] data set yields persistence like behaviour when a time resolution of 2.5 minutes was used to test the model for the prediction of the AL index. Unlike the local linear filters, which are driven by the solar wind input without feedback from the observations, the Kalman filter makes use of the observations as and when available to optimally update the model parameters. The update procedure requires the prediction intervals to be long enough so that the forecasts can be used in practice. The time resolution of the data suitable for such forecasting is studied by taking averages over different durations.

Comment on "Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?" by Mazzoleni et al. (2017)

NASA Astrophysics Data System (ADS)

Viero, Daniele P.

2018-01-01

Citizen science and crowdsourcing are gaining increasing attention among hydrologists. In a recent contribution, Mazzoleni et al. (2017) investigated the integration of crowdsourced data (CSD) into hydrological models to improve the accuracy of real-time flood forecasts. The authors used synthetic CSD (i.e. not actually measured), because real CSD were not available at the time of the study. In their work, which is a proof-of-concept study, Mazzoleni et al. (2017) showed that assimilation of CSD improves the overall model performance; the impact of irregular frequency of available CSD, and that of data uncertainty, were also deeply assessed. However, the use of synthetic CSD in conjunction with (semi-)distributed hydrological models deserves further discussion. As a result of equifinality, poor model identifiability, and deficiencies in model structure, internal states of (semi-)distributed models can hardly mimic the actual states of complex systems away from calibration points. Accordingly, the use of synthetic CSD that are drawn from model internal states under best-fit conditions can lead to overestimation of the effectiveness of CSD assimilation in improving flood prediction. Operational flood forecasting, which results in decisions of high societal value, requires robust knowledge of the model behaviour and an in-depth assessment of both model structure and forcing data. Additional guidelines are given that are useful for the a priori evaluation of CSD for real-time flood forecasting and, hopefully, for planning apt design strategies for both model calibration and collection of CSD.

Forecasting the Risks of Pollution from Ships along the Portuguese Coast

NASA Astrophysics Data System (ADS)

Fernandes, Rodrigo; Neves, Ramiro; Lourenço, Filipe; Braunschweig, Frank

2013-04-01

Pollution risks in coastal and marine environments are in general based in a static approach, considering historical data, reference situations, and typical scenarios. This approach is quite important in a planning stage. However, an alternative approach can be studied, due to the latest implementation of several different real-time monitoring tools as well as faster performances in the generation of numerical forecasts for metocean properties and trajectories of pollutants spilt at sea or costal zones. These developments provide the possibility of developing an integrated support system for better decision-making in emergency or planning issues associated to pollution risks. An innovative methodology to dynamically produce quantified risks in real-time, integrating best available information from numerical forecasts and the existing monitoring tools, has been developed and applied to the Portuguese Coast. The developed system provides coastal pollution risk levels associated to potential (or real) oil spill incidents from ship collision, grounding or foundering, taking into account regional statistic information on vessel accidents and coastal sensitivity indexes, real-time vessel information (positioning, cargo type, speed and vessel type) obtained from AIS, best-available metocean numerical forecasts (hydrodynamics, meteorology - including visibility, wave conditions) and simulated scenarios by the oil spill fate and behaviour component of MOHID Water Modelling System. Different spill fate and behaviour simulations are continuously generated and processed in background (assuming hypothetical spills from vessels), based on variable vessel information and metocean conditions. Results from these simulations are used in the quantification of consequences of potential spills. All historic information is continuously stored in a database (for risk analysis at a later stage). This dynamic approach improves the accuracy in quantification of consequences to the shoreline, as well as the decision support model, allowing a more effective prioritization of individual ships and geographical areas. This system was initially implemented in Portugal for oil spills. The implementation in other Atlantic Regions (starting in Galician Coast, Spain) is being executed in the scope of ARCOPOL+ project (2011-1/150), as well as other relevant updates. The system is being adapted to include risk modelling of chemical spills, as well as fire & explosion accidents and operational illegal discharges. Also the integration of EMSA's THETIS "ship risk profile" (according to Annex 7 from Paris Memorandum of Understanding) in the risk model is being tested. Finally, a new component is being developed to compute the risk for specific time periods, taking advantage of the information previously stored in the database on the positioning of vessels and / or results of numerical models. This component provides the possibility of obtaining a support tool for detailed characterization of risk profiles in certain periods or a sensitivity analysis on different parameters.

A sequential data assimilation approach for the joint reconstruction of mantle convection and surface tectonics

NASA Astrophysics Data System (ADS)

Bocher, M.; Coltice, N.; Fournier, A.; Tackley, P. J.

2016-01-01

With the progress of mantle convection modelling over the last decade, it now becomes possible to solve for the dynamics of the interior flow and the surface tectonics to first order. We show here that tectonic data (like surface kinematics and seafloor age distribution) and mantle convection models with plate-like behaviour can in principle be combined to reconstruct mantle convection. We present a sequential data assimilation method, based on suboptimal schemes derived from the Kalman filter, where surface velocities and seafloor age maps are not used as boundary conditions for the flow, but as data to assimilate. Two stages (a forecast followed by an analysis) are repeated sequentially to take into account data observed at different times. Whenever observations are available, an analysis infers the most probable state of the mantle at this time, considering a prior guess (supplied by the forecast) and the new observations at hand, using the classical best linear unbiased estimate. Between two observation times, the evolution of the mantle is governed by the forward model of mantle convection. This method is applied to synthetic 2-D spherical annulus mantle cases to evaluate its efficiency. We compare the reference evolutions to the estimations obtained by data assimilation. Two parameters control the behaviour of the scheme: the time between two analyses, and the amplitude of noise in the synthetic observations. Our technique proves to be efficient in retrieving temperature field evolutions provided the time between two analyses is ≲10 Myr. If the amplitude of the a priori error on the observations is large (30 per cent), our method provides a better estimate of surface tectonics than the observations, taking advantage of the information within the physics of convection.

A probabilistic, distributed, recursive mechanism for decision-making in the brain

PubMed Central

Gurney, Kevin N.

2018-01-01

Decision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics. PMID:29614077

Rate-based structural health monitoring using permanently installed sensors

PubMed Central

2017-01-01

Permanently installed sensors are becoming increasingly ubiquitous, facilitating very frequent in situ measurements and consequently improved monitoring of ‘trends’ in the observed system behaviour. It is proposed that this newly available data may be used to provide prior warning and forecasting of critical events, particularly system failure. Numerous damage mechanisms are examples of positive feedback; they are ‘self-accelerating’ with an increasing rate of damage towards failure. The positive feedback leads to a common time-response behaviour which may be described by an empirical relation allowing prediction of the time to criticality. This study focuses on Structural Health Monitoring of engineering components; failure times are projected well in advance of failure for fatigue, creep crack growth and volumetric creep damage experiments. The proposed methodology provides a widely applicable framework for using newly available near-continuous data from permanently installed sensors to predict time until failure in a range of application areas including engineering, geophysics and medicine. PMID:28989308

Convectively induced mesoscale weather systems in the tropical and warm-season midlatitude atmosphere

NASA Astrophysics Data System (ADS)

Smull, Bradley F.

1995-07-01

As anticipated by Nelson [1991] in the last U.S. National Report, mesoscale meteorology has continued to be an area of vigorous research activity. Progress is evinced by a growing number of process-oriented studies capitalizing on expanded observational capabilities, as well as more theoretical treatments employing numerical simulations of increasing sophistication. While the majority of papers within the scope of this review fall into the category of basic research, the field's maturation is evident in the emergence of a growing number of applications to operational weather forecasting. Even as our ability to anticipate shifts in synoptic scale upper-air patterns and associated baroclinic developments has steadily improved, lagging skill with regard to quantitative forecasts of precipitation—particularly in situations where deep moist convection is prevalent—has sustained research in warm-season mesoscale meteorology. Each spring and summer midlatitude populations are exposed to life-threatening natural weather phenomena in the form of lightning, tornadoes, straight-line winds, hail, and flash floods. This point was driven home during the summer of 1993, when an extraordinarily persistent series of mesoscale convective systems (MCSs) led to unusually severe and widespread flooding throughout the Mississippi and Missouri river basins. In addition to this obvious impact on regional climate, the 1990's have brought an increased appreciation for the less direct yet potentially significant role that tropical convection may play in shaping global climate through phenomena such as the El Niño-Southern Oscillation (ENSO).

An empirical approach to improving tidal predictions using recent real-time tide gauge data

NASA Astrophysics Data System (ADS)

Hibbert, Angela; Royston, Samantha; Horsburgh, Kevin J.; Leach, Harry

2014-05-01

Classical harmonic methods of tidal prediction are often problematic in estuarine environments due to the distortion of tidal fluctuations in shallow water, which results in a disparity between predicted and observed sea levels. This is of particular concern in the Bristol Channel, where the error associated with tidal predictions is potentially greater due to an unusually large tidal range of around 12m. As such predictions are fundamental to the short-term forecasting of High Water (HW) extremes, it is vital that alternative solutions are found. In a pilot study, using a year-long observational sea level record from the Port of Avonmouth in the Bristol Channel, the UK National Tidal and Sea Level Facility (NTSLF) tested the potential for reducing tidal prediction errors, using three alternatives to the Harmonic Method of tidal prediction. The three methods evaluated were (1) the use of Artificial Neural Network (ANN) models, (2) the Species Concordance technique and (3) a simple empirical procedure for correcting Harmonic Method High Water predictions based upon a few recent observations (referred to as the Empirical Correction Method). This latter method was then successfully applied to sea level records from an additional 42 of the 45 tide gauges that comprise the UK Tide Gauge Network. Consequently, it is to be incorporated into the operational systems of the UK Coastal Monitoring and Forecasting Partnership in order to improve short-term sea level predictions for the UK and in particular, the accurate estimation of HW extremes.

Autoextraction of twelve permanent teeth in a child with autistic spectrum disorder.

PubMed

Williams, Anne C

2016-03-01

This report discusses self-injurious behaviour; this is not unusual in people with autistic spectrum disorders but is not commonly experienced as autoextraction. This case concerns a 12 year old child who presented as a new patient with two teeth missing. He then went on to remove a further ten teeth over a relatively short space of time. The recognition of autoextraction by the dental team is important. its management involves a multidisciplinary team which includes professionals from education, health and social care who work together to prevent progressive self-injury. © 2015 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Magnetic loss and B(H) behaviour of non-oriented electrical sheets under a trapezoidal exciting field

NASA Astrophysics Data System (ADS)

Kedous-Lebouc, A.; Errard, S.; Cornut, B.; Brissonneau, P.

1994-05-01

The excess loss and hysteresis response of electrical steel are measured and discussed in the case of trapezoidal field excitation similar to the current provided by a current commutation supply of a self-synchronous rotating machine. Three industrial non-oriented SiFe samples of different magnetic grades and thicknesses are tested using an automatic Epstein frame equipment. The losses and the unusual observed B( H) loops are analysed in terms of the rate of change of the field, the diffusion of the induction inside the sheet and by the calculation of the theoretical hysteresis cycles due to the eddy currents.

A wrinkle in flight: the role of elastin fibres in the mechanical behaviour of bat wing membranes

PubMed Central

Cheney, Jorn A.; Konow, Nicolai; Bearnot, Andrew; Swartz, Sharon M.

2015-01-01

Bats fly using a thin wing membrane composed of compliant, anisotropic skin. Wing membrane skin deforms dramatically as bats fly, and its three-dimensional configurations depend, in large part, on the mechanical behaviour of the tissue. Large, macroscopic elastin fibres are an unusual mechanical element found in the skin of bat wings. We characterize the fibre orientation and demonstrate that elastin fibres are responsible for the distinctive wrinkles in the surrounding membrane matrix. Uniaxial mechanical testing of the wing membrane, both parallel and perpendicular to elastin fibres, is used to distinguish the contribution of elastin and the surrounding matrix to the overall membrane mechanical behaviour. We find that the matrix is isotropic within the plane of the membrane and responsible for bearing load at high stress; elastin fibres are responsible for membrane anisotropy and only contribute substantially to load bearing at very low stress. The architecture of elastin fibres provides the extreme extensibility and self-folding/self-packing of the wing membrane skin. We relate these findings to flight with membrane wings and discuss the aeromechanical significance of elastin fibre pre-stress, membrane excess length, and how these parameters may aid bats in resisting gusts and preventing membrane flutter. PMID:25833238

Male-Male Mounting Behaviour in Free-Ranging Golden Snub-Nosed Monkeys (Rhinopithecus roxellana).

PubMed

Fang, Gu; Dixson, Alan F; Qi, Xiao-Guang; Li, Bao-Guo

2018-01-01

An all-male band of golden snub-nosed monkeys (Rhinopithecus roxellana) was observed for 3 months in the Qinling Mountains of China, in order to collect data on the frequencies and contextual significance of male-male mounting behaviour. Mounts occurred in a variety of affiliative, dominance-related and sexual contexts, which differed depending upon the ages of the males involved. Mounting behaviour in this group was mainly initiated by adults. Juveniles mounted each other in affiliative contexts (during play and prior to grooming). Adult males mounted subadult and juvenile partners in a greater variety of sociosexual contexts (dominance/rank-related interactions; reconciliation following agonistic encounters, and sometimes as a prelude to receiving grooming). However, subadults and juveniles were never observed to mount adults. In one dyad, involving an adult male and a subadult partner, mounting was more frequent and prolonged, and included bouts of deep pelvic thrusting. Two mounts resulted in anal intromissions and, in 1 case, the subadult partner exhibited seminal emission. Given that the study took place during the annual mating peak period of R. roxellana, it is possible that this unusual male-male sexual activity was related to the absence of mating opportunities for those adults that were excluded from 1-male units. © 2018 S. Karger AG, Basel.

Navigator, a new endemic genus of Cetoniinae (Coleoptera: Scarabaeidae) from Australia, with descriptions of two new species and behavioural studies.

PubMed

Moeseneder, Christian H; Hutchinson, Paul M

2016-10-10

The endemic flower beetle genus Navigator new genus (Coleoptera: Scarabaeidae: Cetoniinae: Schizorhinini) is described from Australia. Navigator contains species that are morphologically and behaviourally unusual when compared to the majority of other Australian flower beetles in several easily visible characters. A differential diagnosis with similar Australian schizorhinine genera and species is performed, and a key to its species is provided. Pseudoclithria fossor Lea, 1914 and Pseudoclithria ruficornis (Westwood, 1874) are moved to the genus Navigator, resulting in Navigator fossor new combination, which is designated as the type species, and Navigator ruficornis new combination. A lectotype is designated for Navigator fossor (Lea, 1914). We describe Navigator interior new species, from Central Australia and Navigator pixii new species, which occurs in Queensland and is the smallest Australian Schizorhinini known. Distribution information for all Navigator species is provided. Our observations of Navigator fossor and Navigator pixii show their larvae are free living in soil and feed on decaying leaves, which is the first time such behaviour is described in Australian cetoniines. We observe that three Navigator species are more tolerant of arid climate than most other Australian cetoniines, adults almost never visit flowers, and males are often in flight searching for sedentary females.

A wrinkle in flight: the role of elastin fibres in the mechanical behaviour of bat wing membranes.

PubMed

Cheney, Jorn A; Konow, Nicolai; Bearnot, Andrew; Swartz, Sharon M

2015-05-06

Bats fly using a thin wing membrane composed of compliant, anisotropic skin. Wing membrane skin deforms dramatically as bats fly, and its three-dimensional configurations depend, in large part, on the mechanical behaviour of the tissue. Large, macroscopic elastin fibres are an unusual mechanical element found in the skin of bat wings. We characterize the fibre orientation and demonstrate that elastin fibres are responsible for the distinctive wrinkles in the surrounding membrane matrix. Uniaxial mechanical testing of the wing membrane, both parallel and perpendicular to elastin fibres, is used to distinguish the contribution of elastin and the surrounding matrix to the overall membrane mechanical behaviour. We find that the matrix is isotropic within the plane of the membrane and responsible for bearing load at high stress; elastin fibres are responsible for membrane anisotropy and only contribute substantially to load bearing at very low stress. The architecture of elastin fibres provides the extreme extensibility and self-folding/self-packing of the wing membrane skin. We relate these findings to flight with membrane wings and discuss the aeromechanical significance of elastin fibre pre-stress, membrane excess length, and how these parameters may aid bats in resisting gusts and preventing membrane flutter. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Assessing the Validity of Sexual Behaviour Reports in a Whole Population Survey in Rural Malawi

PubMed Central

Glynn, Judith R.; Kayuni, Ndoliwe; Banda, Emmanuel; Parrott, Fiona; Floyd, Sian; Francis-Chizororo, Monica; Nkhata, Misheck; Tanton, Clare; Hemmings, Joanne; Molesworth, Anna; Crampin, Amelia C.; French, Neil

2011-01-01

Background Sexual behaviour surveys are widely used, but under-reporting of particular risk behaviours is common, especially by women. Surveys in whole populations provide an unusual opportunity to understand the extent and nature of such under-reporting. Methods All consenting individuals aged between 15 and 59 within a demographic surveillance site in northern Malawi were interviewed about their sexual behaviour. Validity of responses was assessed by analysis of probing questions; by comparison of results with in-depth interviews and with Herpes simplex type-2 (HSV-2) seropositivity; by comparing reports to same sex and opposite sex interviewers; and by quantifying the partnerships within the local community reported by men and by women, adjusted for response rates. Results 6,796 women and 5,253 men (83% and 72% of those eligible) consented and took part in sexual behaviour interviews. Probing questions and HSV-2 antibody tests in those who denied sexual activity identified under-reporting for both men and women. Reports varied little by sex or age of the interviewer. The number of marital partnerships reported was comparable for men and women, but men reported about 4 times as many non-marital partnerships. The discrepancy in reporting of non-marital partnerships was most marked for married women (men reported about 7 times as many non-marital partnerships with married women as were reported by married women themselves), but was only apparent in younger married women. Conclusions We have shown that the under-reporting of non-marital partnerships by women was strongly age-dependent. The extent of under-reporting of sexual activity by young men was surprisingly high. The results emphasise the importance of triangulation, including biomarkers, and the advantages of considering a whole population. PMID:21818398

Discovery of spatio-temporal patterns from location-based social networks

NASA Astrophysics Data System (ADS)

Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

2016-03-01

Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

Attenuated variants of Lesch-Nyhan disease

PubMed Central

Ceballos-Picot, Irene; Torres, Rosa J.; Visser, Jasper E.; Schretlen, David J.; Verdu, Alfonso; Laróvere, Laura E.; Chen, Chung-Jen; Cossu, Antonello; Wu, Chien-Hui; Sampat, Radhika; Chang, Shun-Jen; de Kremer, Raquel Dodelson; Nyhan, William; Harris, James C.; Reich, Stephen G.; Puig, Juan G.

2010-01-01

Lesch–Nyhan disease is a neurogenetic disorder caused by deficiency of the enzyme hypoxanthine–guanine phosphoribosyltransferase. The classic form of the disease is described by a characteristic syndrome that includes overproduction of uric acid, severe generalized dystonia, cognitive disability and self-injurious behaviour. In addition to the classic disease, variant forms of the disease occur wherein some clinical features are absent or unusually mild. The current studies provide the results of a prospective and multi-centre international study focusing on neurological manifestations of the largest cohort of Lesch–Nyhan disease variants evaluated to date, with 46 patients from 3 to 65 years of age coming from 34 families. All had evidence for overproduction of uric acid. Motor abnormalities were evident in 42 (91%), ranging from subtle clumsiness to severely disabling generalized dystonia. Cognitive function was affected in 31 (67%) but it was never severe. Though none exhibited self-injurious behaviours, many exhibited behaviours that were maladaptive. Only three patients had no evidence of neurological dysfunction. Our results were compared with a comprehensive review of 78 prior reports describing a total of 127 Lesch–Nyhan disease variants. Together these results define the spectrum of clinical features associated with hypoxanthine–guanine phosphoribosyltransferase deficiency. At one end of the spectrum are patients with classic Lesch–Nyhan disease and the full clinical phenotype. At the other end of the spectrum are patients with overproduction of uric acid but no apparent neurological or behavioural deficits. Inbetween are patients with varying degrees of motor, cognitive, or behavioural abnormalities. Recognition of this spectrum is valuable for understanding the pathogenesis and diagnosis of all forms of hypoxanthine–guanine phosphoribosyltransferase deficiency. PMID:20176575

Evidence for a critical Earth: the New Geophysics

NASA Astrophysics Data System (ADS)

Crampin, Stuart; Gao, Yuan

2015-04-01

Phenomena that are critical-systems verging on criticality with 'butterfly wings' sensitivity are common - the weather, climate change; stellar radiation; the New York Stock Exchange; population explosions; population collapses; the life cycle of fruit-flies; and many more. It must be expected that the Earth, an archetypal complex heterogeneous interactive phenomena, is a critical-system, hence there is a New Geophysics imposing fundamentally new properties on conventional sub-critical geophysics. We shall show that, despite shear waves and shear-wave splitting (SWS) being observationally neglected, azimuthally-varying stress-aligned SWS is nearly universally observed throughout the Earth's crust and uppermost ~400km of the mantle. Caused by stress-aligned fluid-saturated microcracks (intergranular films of hydrolysed melt in the mantle), the microcracks are so closely-spaced that they verge on failure in fracturing and earthquakes. Phenomena that verge on failure in this way are critical-systems which impose a range of fundamental-new properties on conventional sub-critical geophysics including: self-similarity; monitorability; calculability; predictability; controllability; universality; and butterfly wings' sensitivity. We shall show how these phenomena have been consistently observed along millions of source-to-receiver ray paths confirming the New Geophysics. New Geophysics helps to explain many otherwise inexplicable observations including a number of geophysical conundrums such as the Gutenberg-Richter relationship which is used to describe the behaviour of conventional classic geophysics despite being massively non-linear. The great advantage of the critical Earth is that, unlike other critical-systems, the progress towards criticality can be monitored at almost any point within the deep interior of the material, by analysing observations of seismic SWS. This gives an unrivalled understanding of the detailed behaviour of a particular critical-system. This new understanding of fluid-rock deformation unifies much of the behaviour and has currently-relevant applications: 1) The times, magnitudes, and in some circumstances locations, of impending earthquakes can be stress-forecast (predicted); 2) The times of impending volcanic eruptions can be stress-forecast (predicted); 3) The production of hydrocarbon reservoirs can be, in principle, calculated; 4) Recovery from hydrocarbon reservoirs will be increased if production is slower; 5) Time-lapse of SWS single-well imaging can monitor movement of oil/water contacts; 6) Time-lapse of SWS can monitor behaviour of fluids in fracking reservoirs; 7) Time-lapse SWS can monitor leakage in underground nuclear-waste repositories. Papers referring to these developments can be found in geos.ed.ac.uk/home/scrampin/opinion. Also see abstracts in EGU2015 Sessions: Gao & Crampin (SM3.1), Liu & Crampin (NH2.5), and Crampin & Gao (GD.1).

Comparison of hourly surface downwelling solar radiation estimated from MSG-SEVIRI and forecast by the RAMS model with pyranometers over Italy

NASA Astrophysics Data System (ADS)

Federico, Stefano; Torcasio, Rosa Claudia; Sanò, Paolo; Casella, Daniele; Campanelli, Monica; Fokke Meirink, Jan; Wang, Ping; Vergari, Stefania; Diémoz, Henri; Dietrich, Stefano

2017-06-01

In this paper, we evaluate the performance of two global horizontal solar irradiance (GHI) estimates, one derived from Meteosat Second Generation (MSG) and another from the 1-day forecast of the Regional Atmospheric Modeling System (RAMS) mesoscale model. The horizontal resolution of the MSG-GHI is 3 × 5 km2 over Italy, which is the focus area of this study. For this paper, RAMS has the horizontal resolution of 4 km.The performances of the MSG-GHI estimate and RAMS-GHI 1-day forecast are evaluated for 1 year (1 June 2013-31 May 2014) against data of 12 ground-based pyranometers over Italy spanning a range of climatic conditions, i.e. from maritime Mediterranean to Alpine climate.Statistics for hourly GHI and daily integrated GHI are presented for the four seasons and the whole year for all the measurement sites. Different sky conditions are considered in the analysisResults for hourly data show an evident dependence on the sky conditions, with the root mean square error (RMSE) increasing from clear to cloudy conditions. The RMSE is substantially higher for Alpine stations in all the seasons, mainly because of the increase of the cloud coverage for these stations, which is not well represented at the satellite and model resolutions. Considering the yearly statistics computed from hourly data for the RAMS model, the RMSE ranges from 152 W m-2 (31 %) obtained for Cozzo Spadaro, a maritime station, to 287 W m-2 (82 %) for Aosta, an Alpine site. Considering the yearly statistics computed from hourly data for MSG-GHI, the minimum RMSE is for Cozzo Spadaro (71 W m-2, 14 %), while the maximum is for Aosta (181 W m-2, 51 %). The mean bias error (MBE) shows the tendency of RAMS to over-forecast the GHI, while no specific behaviour is found for MSG-GHI.Results for daily integrated GHI show a lower RMSE compared to hourly GHI evaluation for both RAMS-GHI 1-day forecast and MSG-GHI estimate. Considering the yearly evaluation, the RMSE of daily integrated GHI is at least 9 % lower (in percentage units, from 31 to 22 % for RAMS in Cozzo Spadaro) than the RMSE computed for hourly data for each station. A partial compensation of underestimation and overestimation of the GHI contributes to the RMSE reduction. Furthermore, a post-processing technique, namely model output statistics (MOS), is applied to improve the GHI forecast at hourly and daily temporal scales. The application of MOS shows an improvement of RAMS-GHI forecast, which depends on the site considered, while the impact of MOS on MSG-GHI RMSE is small.

Habitat use, vertical and horizontal behaviour of Atlantic bluefin tuna (Thunnus thynnus) in the Northwestern Mediterranean Sea in relation to oceanographic conditions

NASA Astrophysics Data System (ADS)

Bauer, Robert Klaus; Fromentin, Jean-Marc; Demarcq, Hervé; Bonhommeau, Sylvain

2017-07-01

We investigated the habitat utilization, vertical and horizontal behaviour of Atlantic bluefin tuna Thunnus thynnus (ABFT) in relation to oceanographic conditions in the northwestern Mediterranean Sea, based on 36 pop-up archival tags and different environmental data sets. Tags were deployed on early mature ABFT (127-255 cm) between July and November in 2007-2014, on the shelf area off Marseille, France. The data obtained from these tags provided 1643 daily summaries of ABFT vertical behaviour over 8 years of tag deployment. Based on a hierarchical clustering of this data, we could identify four principle daily vertical behaviour types, representing surface (≦ 10 m) and subsurface (10-100 m) orientation, moderate (50-200 m) and deep (≧ 200 m) diving behaviour. These vertical behaviour types showed seasonal variations with partly opposing trends in their frequencies. Accordingly, ABFT were more surface orientated during summer, while moderate diving behaviour was more common during winter. Depth time series data further revealed inverted day-night patterns for both of these periods. Tagged ABFT frequented the surface waters more regularly during daytime and deeper waters during the night in summer, while the opposite pattern was found in winter. Seasonal changes in the vertical behaviour of ABFT were accompanied by simultaneous changes in environmental conditions (SST, chla, thermal stratification). Accordingly, surface orientation and moderate diving behaviour appeared to be triggered by the thermal stratification of the water column, though less pronounced than previously reported for ABFT in the North Atlantic, probably indicating adaptive vertical behaviour related to the availability of epipelagic food resources (anchovies and sardines). Deep diving behaviour was particularly frequent during months of high biological productivity (February-May), although one recovered tag showed periodic and unusual long spike dives during summer-autumn, in relation to thermal fronts. Regional effects on the vertical behaviour of ABFT were identified through GAMs, with surface orientation being particularly pronounced in the Gulf of Lions, highlighting its suitability for an ongoing annual aerial survey program to estimate ABFT abundance in this region. In addition, increased levels of mesoscale activity/productivity (e.g. related to oceanic fronts) were detected in an area regularly utilized by ABFT, south of the Gulf of Lions, underlining its attractiveness as foraging ground. Kernel densities of geolocation estimates showed a seasonal shift in the horizontal distribution of ABFT from this "high-use" area towards the Gulf of Lions during summer, probably linked to the enhanced availability of epipelagic food resources at this time.

A statistical approach to quasi-extinction forecasting.

PubMed

Holmes, Elizabeth Eli; Sabo, John L; Viscido, Steven Vincent; Fagan, William Fredric

2007-12-01

Forecasting population decline to a certain critical threshold (the quasi-extinction risk) is one of the central objectives of population viability analysis (PVA), and such predictions figure prominently in the decisions of major conservation organizations. In this paper, we argue that accurate forecasting of a population's quasi-extinction risk does not necessarily require knowledge of the underlying biological mechanisms. Because of the stochastic and multiplicative nature of population growth, the ensemble behaviour of population trajectories converges to common statistical forms across a wide variety of stochastic population processes. This paper provides a theoretical basis for this argument. We show that the quasi-extinction surfaces of a variety of complex stochastic population processes (including age-structured, density-dependent and spatially structured populations) can be modelled by a simple stochastic approximation: the stochastic exponential growth process overlaid with Gaussian errors. Using simulated and real data, we show that this model can be estimated with 20-30 years of data and can provide relatively unbiased quasi-extinction risk with confidence intervals considerably smaller than (0,1). This was found to be true even for simulated data derived from some of the noisiest population processes (density-dependent feedback, species interactions and strong age-structure cycling). A key advantage of statistical models is that their parameters and the uncertainty of those parameters can be estimated from time series data using standard statistical methods. In contrast for most species of conservation concern, biologically realistic models must often be specified rather than estimated because of the limited data available for all the various parameters. Biologically realistic models will always have a prominent place in PVA for evaluating specific management options which affect a single segment of a population, a single demographic rate, or different geographic areas. However, for forecasting quasi-extinction risk, statistical models that are based on the convergent statistical properties of population processes offer many advantages over biologically realistic models.

Modelling the 2013 North Aegean (Greece) seismic sequence: geometrical and frictional constraints, and aftershock probabilities

NASA Astrophysics Data System (ADS)

Karakostas, Vassilis; Papadimitriou, Eleftheria; Gospodinov, Dragomir

2014-04-01

The 2013 January 8 Mw 5.8 North Aegean earthquake sequence took place on one of the ENE-WSW trending parallel dextral strike slip fault branches in this area, in the continuation of 1968 large (M = 7.5) rupture. The source mechanism of the main event indicates predominantly strike slip faulting in agreement with what is expected from regional seismotectonics. It was the largest event to have occurred in the area since the establishment of the Hellenic Unified Seismological Network (HUSN), with an adequate number of stations in close distances and full azimuthal coverage, thus providing the chance of an exhaustive analysis of its aftershock sequence. The main shock was followed by a handful of aftershocks with M ≥ 4.0 and tens with M ≥ 3.0. Relocation was performed by using the recordings from HUSN and a proper crustal model for the area, along with time corrections in each station relative to the model used. Investigation of the spatial and temporal behaviour of seismicity revealed possible triggering of adjacent fault segments. Theoretical static stress changes from the main shock give a preliminary explanation for the aftershock distribution aside from the main rupture. The off-fault seismicity is perfectly explained if μ > 0.5 and B = 0.0, evidencing high fault friction. In an attempt to forecast occurrence probabilities of the strong events (Mw ≥ 5.0), estimations were performed following the Restricted Epidemic Type Aftershock Sequence (RETAS) model. The identified best-fitting MOF model was used to execute 1-d forecasts for such aftershocks and follow the probability evolution in time during the sequence. Forecasting was also implemented on the base of a temporal model of aftershock occurrence, different from the modified Omori formula (the ETAS model), which resulted in probability gain (though small) in strong aftershock forecasting for the beginning of the sequence.

Myofibroblastoma Breast with Unusual Morphological Features. Cytohistopathogical Diagnostic Pitfalls and Role of Immunohistochemistry-Review of Literature

PubMed Central

Shivali, B.; S., Kataria; Chandramouleeswari, K.; Anita, S.

2013-01-01

Myofibroblastoma (MFB) is a rare mesenchymal tumour, derived from mammary stromal fibro-myofibroblasts, with diverse biological and morphological behaviour. Large and cellular myofibroblastomas, especially those with epitheliod like cells, can mimic various spindle cell lesions and metaplastic carcinomas, thus posing diagnostic challenge. A 50–year woman presented with slow growing, painless lump in the left breast. Fine Needle Aspiration (FNA) smears showed predominant atypical spindle cell population, pleomorphic epithelial like cells and giant cells. Cytodiagnosis of atypical spindle cell lesion with the possibility of metaplastic carcinoma was suggested. Histopathological examination showed fascicles of spindle cell population admixed with epithelial like cells, atypical cells and tumour giant cells, thus raising differential diagnosis of metaplastic carcinoma, low grade spindle cell sarcoma and myofibroblastic tumour. Lymph nodes were negative for metastatic deposits. Immunohistochemistry revealed variable coexpression of markers for vimentin, fibronectin, CD34, SMA (smooth muscle actin), but negative expression for , S-100, CD99, CK7 (cytokeratin 7), HMWK (high molecular weight keratin), ER (oestrogen receptor) and PR(progesterone receptors). Diagnosis of cellular myofibroblastoma with mixed unusual morphological features was defined, based on both histological and immunohistochemical features. MFB may cause a potential diagnostic pitfall while interpreting FNA and histopathological sections due to its wide differential diagnosis. The distinction of MFB from its cytohistological mimics of malignancy is crucial to avoid unnecessary extensive procedures. The case report emphasizes the role of immunohistochemistry as gold standard in diagnosis of MFB. The case is also being presented because of its large size and rare mixed unusual morphological features. PMID:24298520

Phospholipids of New Zealand Edible Brown Algae.

PubMed

Vyssotski, Mikhail; Lagutin, Kirill; MacKenzie, Andrew; Mitchell, Kevin; Scott, Dawn

2017-07-01

Edible brown algae have attracted interest as a source of beneficial allenic carotenoid fucoxanthin, and glyco- and phospholipids enriched in polyunsaturated fatty acids. Unlike green algae, brown algae contain no or little phosphatidylserine, possessing an unusual aminophospholipid, phosphatidyl-O-[N-(2-hydroxyethyl) glycine], PHEG, instead. When our routinely used technique of 31 P-NMR analysis of phospholipids was applied to the samples of edible New Zealand brown algae, a number of signals corresponding to unidentified phosphorus-containing compounds were observed in total lipids. NI (negative ion) ESI QToF MS spectra confirmed the presence of more familiar phospholipids, and also suggested the presence of PHEG or its isomers. The structure of PHEG was confirmed by comparison with a synthetic standard. An unusual MS fragmentation pattern that was also observed prompted us to synthesise a number of possible candidates, and was found to follow that of phosphatidylhydroxyethyl methylcarbamate, likely an extraction artefact. An unexpected outcome was the finding of ceramidephosphoinositol that has not been reported previously as occurring in brown algae. An uncommon arsenic-containing phospholipid has also been observed and quantified, and its TLC behaviour studied, along with that of the newly synthesised lipids.

Peculiar glitch of PSR J1119-6127 and extension of the vortex creep model

NASA Astrophysics Data System (ADS)

Akbal, O.; Gügercinoğlu, E.; Şaşmaz Muş, S.; Alpar, M. A.

2015-05-01

Glitches are sudden changes in rotation frequency and spin-down rate, observed from pulsars of all ages. Standard glitches are characterized by a positive step in angular velocity (ΔΩ > 0) and a negative step in the spin-down rate (Δ dot{Ω } < 0) of the pulsar. There are no glitch-associated changes in the electromagnetic signature of rotation-powered pulsars in all cases so far. For the first time, in the last glitch of PSR J1119-6127, there is clear evidence for changing emission properties coincident with the glitch. This glitch is also unusual in its signature. Further, the absolute value of the spin-down rate actually decreases in the long term. This is in contrast to usual glitch behaviour. In this paper we extend the vortex creep model in order to take into account these peculiarities. We propose that a starquake with crustal plate movement towards the rotational poles of the star induces inward vortex motion which causes the unusual glitch signature. The component of the magnetic field perpendicular to the rotation axis will decrease, giving rise to a permanent change in the pulsar external torque.

Topological modes bound to dislocations in mechanical metamaterials

NASA Astrophysics Data System (ADS)

Paulose, Jayson; Chen, Bryan Gin-Ge; Vitelli, Vincenzo

2015-02-01

Mechanical metamaterials are artificial structures with unusual properties, such as negative Poisson ratio, bistability or tunable vibrational properties, that originate in the geometry of their unit cell. Often at the heart of such unusual behaviour is a soft mode: a motion that does not significantly stretch or compress the links between constituent elements. When activated by motors or external fields, soft modes become the building blocks of robots and smart materials. Here, we demonstrate the existence of topological soft modes that can be positioned at desired locations in a metamaterial while being robust against a wide range of structural deformations or changes in material parameters. These protected modes, localized at dislocations in deformed kagome and square lattices, are the mechanical analogue of topological states bound to defects in electronic systems. We create physical realizations of the topological modes in prototypes of kagome lattices built out of rigid triangular plates. We show mathematically that they originate from the interplay between two Berry phases: the Burgers vector of the dislocation and the topological polarization of the lattice. Our work paves the way towards engineering topologically protected nanomechanical structures for molecular robotics or information storage and read-out.

Exploring coupled 4D-Var data assimilation using an idealised atmosphere-ocean model

NASA Astrophysics Data System (ADS)

Smith, Polly; Fowler, Alison; Lawless, Amos; Haines, Keith

2014-05-01

The successful application of data assimilation techniques to operational numerical weather prediction and ocean forecasting systems has led to an increased interest in their use for the initialisation of coupled atmosphere-ocean models in prediction on seasonal to decadal timescales. Coupled data assimilation presents a significant challenge but offers a long list of potential benefits including improved use of near-surface observations, reduction of initialisation shocks in coupled forecasts, and generation of a consistent system state for the initialisation of coupled forecasts across all timescales. In this work we explore some of the fundamental questions in the design of coupled data assimilation systems within the context of an idealised one-dimensional coupled atmosphere-ocean model. The system is based on the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) atmosphere model and a K-Profile Parameterisation (KKP) mixed layer ocean model developed by the National Centre for Atmospheric Science (NCAS) climate group at the University of Reading. It employs a strong constraint incremental 4D-Var scheme and is designed to enable the effective exploration of various approaches to performing coupled model data assimilation whilst avoiding many of the issues associated with more complex models. Working with this simple framework enables a greater range and quantity of experiments to be performed. Here, we will describe the development of our simplified single-column coupled atmosphere-ocean 4D-Var assimilation system and present preliminary results from a series of identical twin experiments devised to investigate and compare the behaviour and sensitivities of different coupled data assimilation methodologies. This includes comparing fully and weakly coupled assimilations with uncoupled assimilation, investigating whether coupled assimilation can eliminate or lessen initialisation shock in coupled model forecasts, and exploring the effect of the assimilation window length in coupled assimilations. These experiments will facilitate a greater theoretical understanding of the coupled atmosphere-ocean data assimilation problem and thus help guide the design and implementation of different coupling strategies within operational systems. This research is funded by the European Space Agency (ESA) and the UK Natural Environment Research Council (NERC). The ESA funded component is part of the Data Assimilation Projects - Coupled Model Data Assimilation initiative whose goal is to advance data assimilation techniques in fully coupled atmosphere-ocean models (see http://www.esa-da.org/). It is being conducted in parallel to the development of prototype weakly coupled data assimilation systems at both the UK Met Office and ECMWF.

One hundred and fifty years of sprint and distance running – Past trends and future prospects

PubMed Central

Weiss, Martin; Newman, Alexandra; Whitmore, Ceri; Weiss, Stephan

2016-01-01

Abstract Sprint and distance running have experienced remarkable performance improvements over the past century. Attempts to forecast running performances share an almost similarly long history but have relied so far on relatively short data series. Here, we compile a comprehensive set of season-best performances for eight Olympically contested running events. With this data set, we conduct (1) an exponential time series analysis and (2) a power-law experience curve analysis to quantify the rate of past performance improvements and to forecast future performances until the year 2100. We find that the sprint and distance running performances of women and men improve exponentially with time and converge at yearly rates of 4% ± 3% and 2% ± 2%, respectively, towards their asymptotic limits. Running performances can also be modelled with the experience curve approach, yielding learning rates of 3% ± 1% and 6% ± 2% for the women's and men's events, respectively. Long-term trends suggest that: (1) women will continue to run 10–20% slower than men, (2) 9.50 s over 100 m dash may only be broken at the end of this century and (3) several middle- and long-distance records may be broken within the next two to three decades. The prospects of witnessing a sub-2 hour marathon before 2100 remain inconclusive. Our results should be interpreted cautiously as forecasting human behaviour is intrinsically uncertain. The future season-best sprint and distance running performances will continue to scatter around the trends identified here and may yield unexpected improvements of standing world records. PMID:26088705

On a Possible Unified Scaling Law for Volcanic Eruption Durations

PubMed Central

Cannavò, Flavio; Nunnari, Giuseppe

2016-01-01

Volcanoes constitute dissipative systems with many degrees of freedom. Their eruptions are the result of complex processes that involve interacting chemical-physical systems. At present, due to the complexity of involved phenomena and to the lack of precise measurements, both analytical and numerical models are unable to simultaneously include the main processes involved in eruptions thus making forecasts of volcanic dynamics rather unreliable. On the other hand, accurate forecasts of some eruption parameters, such as the duration, could be a key factor in natural hazard estimation and mitigation. Analyzing a large database with most of all the known volcanic eruptions, we have determined that the duration of eruptions seems to be described by a universal distribution which characterizes eruption duration dynamics. In particular, this paper presents a plausible global power-law distribution of durations of volcanic eruptions that holds worldwide for different volcanic environments. We also introduce a new, simple and realistic pipe model that can follow the same found empirical distribution. Since the proposed model belongs to the family of the self-organized systems it may support the hypothesis that simple mechanisms can lead naturally to the emergent complexity in volcanic behaviour. PMID:26926425

On a Possible Unified Scaling Law for Volcanic Eruption Durations.

PubMed

Cannavò, Flavio; Nunnari, Giuseppe

2016-03-01

Volcanoes constitute dissipative systems with many degrees of freedom. Their eruptions are the result of complex processes that involve interacting chemical-physical systems. At present, due to the complexity of involved phenomena and to the lack of precise measurements, both analytical and numerical models are unable to simultaneously include the main processes involved in eruptions thus making forecasts of volcanic dynamics rather unreliable. On the other hand, accurate forecasts of some eruption parameters, such as the duration, could be a key factor in natural hazard estimation and mitigation. Analyzing a large database with most of all the known volcanic eruptions, we have determined that the duration of eruptions seems to be described by a universal distribution which characterizes eruption duration dynamics. In particular, this paper presents a plausible global power-law distribution of durations of volcanic eruptions that holds worldwide for different volcanic environments. We also introduce a new, simple and realistic pipe model that can follow the same found empirical distribution. Since the proposed model belongs to the family of the self-organized systems it may support the hypothesis that simple mechanisms can lead naturally to the emergent complexity in volcanic behaviour.

The forecaster's added value in QPF

NASA Astrophysics Data System (ADS)

Turco, M.; Milelli, M.

2009-04-01

To the authors' knowledge there are relatively few studies that try to answer this topic: "Are humans able to add value to computer-generated forecasts and warnings ?". Moreover, the answers are not always positive. In particular some postprocessing method is competitive or superior to human forecast (see for instance Baars et al., 2005, Charba et al., 2002, Doswell C., 2003, Roebber et al., 1996, Sanders F., 1986). Within the alert system of ARPA Piemonte it is possible to study in an objective manner if the human forecaster is able to add value with respect to computer-generated forecasts. Every day the meteorology group of the Centro Funzionale of Regione Piemonte produces the HQPF (Human QPF) in terms of an areal average for each of the 13 regional warning areas, which have been created according to meteo-hydrological criteria. This allows the decision makers to produce an evaluation of the expected effects by comparing these HQPFs with predefined rainfall thresholds. Another important ingredient in this study is the very dense non-GTS network of rain gauges available that makes possible a high resolution verification. In this context the most useful verification approach is the measure of the QPF and HQPF skills by first converting precipitation expressed as continuous amounts into ‘‘exceedance'' categories (yes-no statements indicating whether precipitation equals or exceeds selected thresholds) and then computing the performances for each threshold. In particular in this work we compare the performances of the latest three years of QPF derived from two meteorological models COSMO-I7 (the Italian version of the COSMO Model, a mesoscale model developed in the framework of the COSMO Consortium) and IFS (the ECMWF global model) with the HQPF. In this analysis it is possible to introduce the hypothesis test developed by Hamill (1999), in which a confidence interval is calculated with the bootstrap method in order to establish the real difference between the skill scores of two competitive forecast. It is important to underline that the conclusions refer to the analysis of the Piemonte operational alert system, so they cannot be directly taken as universally true. But we think that some of the main lessons that can be derived from this study could be useful for the meteorological community. In details, the main conclusions are the following: · despite the overall improvement in global scale and the fact that the resolution of the limited area models has increased considerably over recent years, the QPF produced by the meteorological models involved in this study has not improved enough to allow its direct use: the subjective HQPF continues to offer the best performance; · in the forecast process, the step where humans have the largest added value with respect to mathematical models, is the communication. In fact the human characterisation and communication of the forecast uncertainty to end users cannot be replaced by any computer code; · the QPFs verification is one of the most important activities of a Centro Funzionale because it allows a better understanding of the model behaviour in the different meteorological configurations, highlights the systematic characteristics, and helps in evaluating the reliability, in average or extreme values, over long term or in current situations; · eventually, although there is no novelty in this study, we would like to show that the correct application of appropriated statistical tecniques permits a better definition and quantification of the errors and, mostly important, allows a correct (unbiased) communication between forecasters and decision makers.

Psychological assessment in children and adolescents with Benign Paroxysmal Vertigo.

PubMed

Reale, Laura; Guarnera, Manuela; Grillo, Caterina; Maiolino, Luigi; Ruta, Liliana; Mazzone, Luigi

2011-02-01

Migraine in childhood and adolescence has been associated with the presence of behavioural and emotional difficulties, but only few data are available with respect to unusual types of headache syndromes such as Benign Paroxysmal Vertigo of Childhood (BPVC). Aim of the present study was to evaluate the behavioural and emotional profiles of clinically referred children and adolescents suffering from BPVC and migraine, as compared to normal controls. According to the revised International Classification of Headache Disorders (ICHD-2) the BPVC belongs to the category of "primary headache", as a migraine equivalent, in a subset that is called "periodic syndromes of childhood". A total of 60 clinically referred children and adolescents (4-15 years) 21 suffering from BPVC and 20 from migraine, according to the diagnostic criteria of the ICHD-2, and 19 normal control (NC) were recruited in this study. Psychological assessment were performed using the Child Behaviour Checklist (CBCL), the Children's Depression Inventory (CDI) and the Multidimensional Anxiety Scale for Children (MASC). Although most of the patients suffering from headache had scores within the normative non-pathological range, both BPVC and migraine patients had significantly higher CBCL total, internalizing, and externalizing scores, as compared to NC. Furthermore, both BPVC and migraine groups displayed significantly higher CDI and MASC scores than NC group. No differences were found between the two types of headache. In conclusion, clinically referred children and adolescents with BPVC and migraine showed higher indices of behavioural and emotional symptoms, both internalizing and externalizing, as compared to normal peers. Copyright © 2010 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Autism characteristics and behavioural disturbances in ~ 500 children with Down's syndrome in England and Wales.

PubMed

Warner, Georgina; Moss, Joanna; Smith, Patrick; Howlin, Patricia

2014-08-01

Recent research shows that a significant minority of children with Down's syndrome (DS) also meet diagnostic criteria for an autism spectrum disorder (ASD). The present study investigated what proportion of children aged 6-15 years with a confirmed diagnosis of DS in England and Wales display autistic-type behaviours, and explored the characteristics of this group of children. The Social Communication Questionnaire (SCQ) was used to screen for autism characteristics and the Strengths and Difficulties Questionnaire (SDQ) to explore behavioural difficulties. The proportion of children who met the cut-off score for ASD on the SCQ (total score ≥ 15) was 37.7% (95% CI: 33.4-42.0%); for autism (total score ≥ 22) the proportion was 16.5% (95% CI: 13.2-19.8%). Children who met the cut-off for ASD were significantly more likely to be reported as having emotional symptoms, conduct problems and hyperactivity on the SDQ than children who scored well below cut-off (total score < 10). However, the profile of their autism characteristics on the SCQ was atypical compared with individuals with idiopathic ASD. The pervasiveness of ASD in children with DS in England and Wales is substantially higher than in the general population. These children also experience significantly greater behavioural problems than children with DS only. Early detection of autism characteristics is important for appropriate intervention. However, the unusual profile of autism characteristics in this group may affect the recognition of the disorder and hinder the implementation of appropriate interventions. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

Adsorption of hydrophobin/β-casein mixtures at the solid-liquid interface.

PubMed

Tucker, I M; Petkov, J T; Penfold, J; Thomas, R K; Cox, A R; Hedges, N

2016-09-15

The adsorption behaviour of mixtures of the proteins β-casein and hydrophobin at the hydrophilic solid-liquid surface have been studied by neutron reflectivity. The results of measurements from sequential adsorption and co-adsorption from solution are contrasted. The adsorption properties of protein mixtures are important for a wide range of applications. Because of competing factors the adsorption behaviour of protein mixtures at interfaces is often difficult to predict. This is particularly true for mixtures containing hydrophobin as hydrophobin possesses some unusual surface properties. At β-casein concentrations ⩾0.1wt% β-casein largely displaces a pre-adsorbed layer of hydrophobin at the interface, similar to that observed in hydrophobin-surfactant mixtures. In the composition and concentration range studied here for the co-adsorption of β-casein-hydrophobin mixtures the adsorption is dominated by the β-casein adsorption. The results provide an important insight into how the competitive adsorption in protein mixtures of hydrophobin and β-casein can impact upon the modification of solid surface properties and the potential for a wide range of colloid stabilisation applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Nanoscale capillary freezing of ionic liquids confined between metallic interfaces and the role of electronic screening.

PubMed

Comtet, Jean; Niguès, Antoine; Kaiser, Vojtech; Coasne, Benoit; Bocquet, Lydéric; Siria, Alessandro

2017-06-01

Room-temperature ionic liquids (RTILs) are new materials with fundamental importance for energy storage and active lubrication. They are unusual liquids, which challenge the classical frameworks of electrolytes, whose behaviour at electrified interfaces remains elusive, with exotic responses relevant to their electrochemical activity. Using tuning-fork-based atomic force microscope nanorheological measurements, we explore here the properties of confined RTILs, unveiling a dramatic change of the RTIL towards a solid-like phase below a threshold thickness, pointing to capillary freezing in confinement. This threshold is related to the metallic nature of the confining materials, with more metallic surfaces facilitating freezing. This behaviour is interpreted in terms of the shift of the freezing transition, taking into account the influence of the electronic screening on RTIL wetting of the confining surfaces. Our findings provide fresh views on the properties of confined RTIL with implications for their properties inside nanoporous metallic structures, and suggests applications to tune nanoscale lubrication with phase-changing RTILs, by varying the nature and patterning of the substrate, and application of active polarization.

Hashimoto's Encephalopathy Presenting with Unusual Behavioural Disturbances in an Adolescent Girl

PubMed Central

Subashini, Viswanath; Balakrishnan, Ramasamy

2017-01-01

Hashimoto's encephalopathy (HE) is a rare autoimmune disorder with neurological and neuropsychiatric manifestations and elevated titres of anti-thyroid antibodies. Here we are reporting a case of HE in a 19-year-old girl who presented with seizure-like episodes, confusion, and behavioural disturbances with catatonic symptoms such as posturing, echopraxia, echolalia, and ambivalence. Patient did not respond to antipsychotics and anticonvulsants. On further investigation, patient was found to have high serum anti-TPO antibodies of about 1261 U/mL with euthyroid status, which supported a suspicion of HE. Our consultant neurologist confirmed the diagnosis and she was started on injection of methylprednisolone 750 mg OD. Since patient started showing clinical improvement, her antipsychotic medications were tapered off. On follow-up, patient has recovered and is functioning well. Since HE is a diagnosis of exclusion, very high anti-TPO antibodies and good response to steroids supported the diagnosis of HE in this patient after excluding other etiological possibilities. This case has been reported because the clinical presentation was predominantly neurobehavioural manifestations which is uncommon with HE. PMID:28607558

Urease immobilized polymer hydrogel: Long-term stability and enhancement of enzymatic activity.

PubMed

Kutcherlapati, S N Raju; Yeole, Niranjan; Jana, Tushar

2016-02-01

A method has been developed in which an enzyme namely urease was immobilized inside hydrogel matrix to study the stability and enzymatic activity in room temperature (∼27-30°C). This urease coupled hydrogel (UCG) was obtained by amine-acid coupling reaction and this procedure is such that it ensured the wider opening of mobile flap of enzyme active site. A systematic comparison of urea-urease assay and the detailed kinetic data clearly revealed that the urease shows activity for more than a month when stored at ∼27-30°C in case of UCG whereas it becomes inactive in case of free urease (enzyme in buffer solution). The aqueous microenvironment inside the hydrogel, unusual morphological features and thermal behaviour were believed to be the reasons for unexpected behaviour. UCG displayed enzyme activity at basic pH and up to 60°C. UCG showed significant enhancement in activity against thermal degradation compared to free urease. In summary, this method is a suitable process to stabilize the biomacromolecules in standard room temperature for many practical uses. Copyright © 2015 Elsevier Inc. All rights reserved.

Nanoscale capillary freezing of ionic liquids confined between metallic interfaces and the role of electronic screening

NASA Astrophysics Data System (ADS)

Comtet, Jean; Niguès, Antoine; Kaiser, Vojtech; Coasne, Benoit; Bocquet, Lydéric; Siria, Alessandro

2017-06-01

Room-temperature ionic liquids (RTILs) are new materials with fundamental importance for energy storage and active lubrication. They are unusual liquids, which challenge the classical frameworks of electrolytes, whose behaviour at electrified interfaces remains elusive, with exotic responses relevant to their electrochemical activity. Using tuning-fork-based atomic force microscope nanorheological measurements, we explore here the properties of confined RTILs, unveiling a dramatic change of the RTIL towards a solid-like phase below a threshold thickness, pointing to capillary freezing in confinement. This threshold is related to the metallic nature of the confining materials, with more metallic surfaces facilitating freezing. This behaviour is interpreted in terms of the shift of the freezing transition, taking into account the influence of the electronic screening on RTIL wetting of the confining surfaces. Our findings provide fresh views on the properties of confined RTIL with implications for their properties inside nanoporous metallic structures, and suggests applications to tune nanoscale lubrication with phase-changing RTILs, by varying the nature and patterning of the substrate, and application of active polarization.

Observation of short range order driven large refrigerant capacity in chemically disordered single phase compound Dy2Ni0.87Si2.95.

PubMed

Pakhira, Santanu; Mazumdar, Chandan; Choudhury, Dibyasree; Ranganathan, R; Giri, S

2018-05-16

In this work, we report the successful synthesis of a new intermetallic compound Dy2Ni0.87Si2.95 forming in single phase only with a chemically disordered structure. The random distribution of Ni/Si and crystal defects create a variation in the local electronic environment between the magnetic Dy ions. In the presence of both disorder and competing exchange interactions driven magnetic frustration, originating due to c/a ∼ 1, the compound undergoes spin freezing behaviour below 5.6 K. In the non-equilibrium state below the spin freezing behaviour, the compound exhibits aging phenomena and magnetic memory effects. In the magnetically short-range ordered region, much above the freezing temperature, an unusual occurrence of considerable magnetic entropy change, -ΔSmaxM ∼ 21 J kg-1 K-1 with large cooling power RCP ∼ 531 J kg-1 and adiabatic temperature change, ΔTad ∼ 10 K for a field change of 70 kOe, is observed for this short range ordered cluster-glass compound without any magnetic hysteresis loss.

Ruminations on Hildegard of Bingen (1098-1179) and autism.

PubMed

Ranft, Patricia

2014-05-01

The article brings together contemporary research on autism spectrum disorder and historical sources concerning the medical condition of a 12th century nun, Hildegard of Bingen, to test two hypotheses: first, that Hildegard manifested disabilities that meet the criteria for autism spectrum disorder and, second, that medieval monasticism was unwittingly well-suited to treat Hildegard's condition. Abundant Hildegardian sources document traces of autism spectrum disorder behaviour in Hildegard's unusual childhood and the composite picture that emerges, when these individual traits are gathered together, is consistent with an autism spectrum disorder diagnosis. The role monasticism played in helping Hildegard overcome these behaviours is documented and aspects that monasticism shares with modern autism spectrum disorder treatment programs are identified. By recognizing the presence of autism spectrum disorder traits in a major cultural leader of another era and by identifying the type of life she lived while those traits were minimized, we gain insight into the history of autism, medieval monastic life and effective elements of autism spectrum disorder treatment. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

A Pro-active Real-time Forecasting and Decision Support System for Daily Management of Marine Works

NASA Astrophysics Data System (ADS)

Bollen, Mark; Leyssen, Gert; Smets, Steven; De Wachter, Tom

2016-04-01

Marine Works involving turbidity generating activities (eg. dredging, dredge spoil placement) can generate environmental stress in and around a project area in the form of sediment plumes causing light reduction and sedimentation. If these works are situated near sensitive habitats like sea-grass beds, coral reefs or sensitive human activities eg. aquaculture farms or water intakes, or if contaminants are present in the water soil environmental scrutiny is advised. Environmental Regulations can impose limitations to these activities in the form of turbidity thresholds, spill budgets, contaminant levels. Breaching environmental regulations can result in increased monitoring, adaptation of the works planning and production rates and ultimately in a (temporary) stop of activities all of which entail time and cost impacts for a contractor and/or client. Sediment plume behaviour is governed by the dredging process, soil properties and ambient conditions (currents, water depth) and can be modelled. Usually this is done during the preparatory EIA phase of a project, for estimation of environmental impact based on climatic scenarios. An operational forecasting tool is developed to adapt marine work schedules to the real-time circumstances and thus evade exceedance of critical threshold levels at sensitive areas. The forecasting system is based on a Python-based workflow manager with a MySQL database and a Django frontend web tool for user interaction and visualisation of the model results. The core consists of a numerical hydrodynamic model with sediment transport module (Mike21 from DHI). This model is driven by space and time varying wind fields and wave boundary conditions, and turbidity inputs (suspended sediment source terms) based on marine works production rates and soil properties. The resulting threshold analysis allows the operator to indicate potential impact at the sensitive areas and instigate an adaption of the marine work schedule if needed. In order to use this toolbox in real-time situations and facilitate forecasting of impacts of planned dredge works, the following operational online functionalities are implemented: • Automated fetch and preparation of the input data, including 7 day forecast wind and wave fields and real-time measurements, and user defined the turbidity inputs based on scheduled marine works. • Generate automated forecasts and running user configurable scenarios at the same time in parallel. • Export and convert the model results, time series and maps, into a standardized format (netcdf). • Automatic analysis and processing of model results, including the calculation of indicator turbidity values and the exceedance analysis of threshold levels at the different sensitive areas. Data assimilation with the real time on site turbidity measurements is implemented in this threshold analysis. • Pre-programmed generation of animated sediment plumes, specific charts and pdf reports to allow a rapid interpretation of the model results by the operators and facilitating decision making in the operational planning. The performed marine works, resulting from the marine work schedule proposed by the forecasting system, are evaluated by a threshold analysis on the validated turbidity measurements on the sensitive sites. This machine learning loop allows a check of the system in order to evaluate forecast and model uncertainties.

The formation of a large summertime Saharan dust plume: Convective and synoptic-scale analysis

PubMed Central

Roberts, A J; Knippertz, P

2014-01-01

Haboobs are dust storms produced by the spreading of evaporatively cooled air from thunderstorms over dusty surfaces and are a major dust uplift process in the Sahara. In this study observations, reanalysis, and a high-resolution simulation using the Weather Research and Forecasting model are used to analyze the multiscale dynamics which produced a long-lived (over 2 days) Saharan mesoscale convective system (MCS) and an unusually large haboob in June 2010. An upper level trough and wave on the subtropical jet 5 days prior to MCS initiation produce a precipitating tropical cloud plume associated with a disruption of the Saharan heat low and moistening of the central Sahara. The restrengthening Saharan heat low and a Mediterranean cold surge produce a convergent region over the Hoggar and Aïr Mountains, where small convective systems help further increase boundary layer moisture. Emerging from this region the MCS has intermittent triggering of new cells, but later favorable deep layer shear produces a mesoscale convective complex. The unusually large size of the resulting dust plume (over 1000 km long) is linked to the longevity and vigor of the MCS, an enhanced pressure gradient due to lee cyclogenesis near the Atlas Mountains, and shallow precipitating clouds along the northern edge of the cold pool. Dust uplift processes identified are (1) strong winds near the cold pool front, (2) enhanced nocturnal low-level jet within the aged cold pool, and (3) a bore formed by the cold pool front on the nocturnal boundary layer. PMID:25844277

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.

Natural glide slab avalanches, Glacier National Park, USA: A unique hazard and forecasting challenge

USGS Publications Warehouse

Reardon, Blase; Fagre, Daniel B.; Dundas, Mark; Lundy, Chris

2006-01-01

In a museum of avalanche phenomena, glide cracks and glide avalanches might be housed in the “strange but true” section. These oddities are uncommon in most snow climates and tend to be isolated to specific terrain features such as bedrock slabs. Many glide cracks never result in avalanches, and when they do, the wide range of time between crack formation and slab failure makes them highly unpredictable. Despite their relative rarity, glide cracks and glide avalanches pose a regular threat and complex forecasting challenge during the annual spring opening of the Going-to-the-Sun Road in Glacier National Park, U.S.A. During the 2006 season, a series of unusual glide cracks delayed snow removal operations by over a week and provided a unique opportunity to record detailed observations of glide avalanches and characterize their occurrence and associated weather conditions. Field observations were from snowpits, crown profiles and where possible, measurements of slab thickness, bed surface slope angle, substrate and other physical characteristics. Weather data were recorded at one SNOTEL site and two automated stations located from 0.6-10 km of observed glide slab avalanches. Nearly half (43%) of the 35 glide slab avalanches recorded were Class D2-2.5, with 15% Class D3-D3.5. The time between glide crack opening and failure ranged from 2 days to over six weeks, and the avalanches occurred in cycles associated with loss of snow water equivalent and spikes in temperature and radiation. We conclude with suggest ions for further study.

Forecasting and prediction of scorpion sting cases in Biskra province, Algeria, using a seasonal autoregressive integrated moving average model.

PubMed

Selmane, Schehrazad; L'Hadj, Mohamed

2016-01-01

The aims of this study were to highlight some epidemiological aspects of scorpion envenomations, to analyse and interpret the available data for Biskra province, Algeria, and to develop a forecasting model for scorpion sting cases in Biskra province, which records the highest number of scorpion stings in Algeria. In addition to analysing the epidemiological profile of scorpion stings that occurred throughout the year 2013, we used the Box-Jenkins approach to fit a seasonal autoregressive integrated moving average (SARIMA) model to the monthly recorded scorpion sting cases in Biskra from 2000 to 2012. The epidemiological analysis revealed that scorpion stings were reported continuously throughout the year, with peaks in the summer months. The most affected age group was 15 to 49 years old, with a male predominance. The most prone human body areas were the upper and lower limbs. The majority of cases (95.9%) were classified as mild envenomations. The time series analysis showed that a (5,1,0)×(0,1,1) 12 SARIMA model offered the best fit to the scorpion sting surveillance data. This model was used to predict scorpion sting cases for the year 2013, and the fitted data showed considerable agreement with the actual data. SARIMA models are useful for monitoring scorpion sting cases, and provide an estimate of the variability to be expected in future scorpion sting cases. This knowledge is helpful in predicting whether an unusual situation is developing or not, and could therefore assist decision-makers in strengthening the province's prevention and control measures and in initiating rapid response measures.

Ferrocene Functionalized Endocrine Modulators as Anticancer Agents

NASA Astrophysics Data System (ADS)

Hillard, Elizabeth A.; Vessières, Anne; Jaouen, Gerard

We present here some of our studies on the synthesis and behaviour of ferrocenyl selective endocrine receptor modulators against cancer cells, particularly breast and prostate cancers. The proliferative/anti-proliferative effects of compounds based on steroidal and non-steroidal endocrine modulators have been extensively explored in vitro. Structure-activity relationship studies of such molecules, particularly the hydroxyferrocifens and ferrocene phenols, have shown the effect of (1) the presence and the length of the N,N-dimethylamino side chain, (2) the presence and position of the phenol group, (3) the role of the ferrocenyl moiety, (4) that of conjugation, (5) phenyl functionalisation and (6) the placement of the phenyl group. Compounds possessing a ferrocene moiety linked to a p-phenol by a conjugated π-system are among the most potent of the series, with IC50 values ranging from 0.090 to 0.6µM on hormone independent breast cancer cells. Based on the SAR data and electrochemical studies, we have proposed an original mechanism to explain the unusual behaviour of these bioorganometallic species and coin the term "kronatropic" to qualify this effect, involving ROS production and bio-oxidation. In addition, the importance of formulation is underlined. We also discuss the behaviour of ferrocenyl androgens and anti-androgens for possible use against prostate cancers. In sum, ferrocene has proven to be a fascinating substituent due to its vast potential for oncology.

Factors influencing frontal cortex development and recovery from early frontal injury.

PubMed

Halliwell, Celeste; Comeau, Wendy; Gibb, Robbin; Frost, Douglas O; Kolb, Bryan

2009-01-01

Neocortical development represents more than a simple unfolding of a genetic blueprint but rather represents a complex dance of genetic and environmental events that interact to adapt the brain to fit a particular environmental context. Although most cortical regions are sensitive to a wide range of experiential factors during development and later in life, the prefrontal cortex appears to be unusually sensitive to perinatal experiences and relatively immune to many adulthood experiences relative to other neocortical regions. One way to examine experience-dependent prefrontal development is to conduct studies in which experiential perturbations are related neuronal morphology. This review of the research reveals both pre- and post-natal factors have important effects on prefrontal development and behaviour. Such factors include psychoactive drugs, including both illicit drugs and prescription drugs, stress, gonadal hormones and sensory and motor stimulation. A second method of study is to examine both the effects of perinatal prefrontal injury on the development of the remaining cerebral mantle and correlated behaviours as well as the effects of post-injury rehabilitation programmes on the anatomical and behavioural measures. Prefrontal injury alters cerebral development in a developmental-stage dependent manner with perinatal injuries having far more deleterious effects than similar injuries later in infancy. The outcome of perinatal injuries can be modified, however, by rehabilitation with many of the factors shown to influence prefrontal development in the otherwise normal brain.

Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

PubMed Central

Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

2014-01-01

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques. PMID:25157950

Predicting physical time series using dynamic ridge polynomial neural networks.

PubMed

Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

2014-01-01

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques.

Oil supply between OPEC and non-OPEC based on game theory

NASA Astrophysics Data System (ADS)

Chang, Yuwen; Yi, Jiexin; Yan, Wei; Yang, Xinshe; Zhang, Song; Gao, Yifan; Wang, Xi

2014-10-01

The competing strategies between OPEC (Organization of the Petroleum Exporting Countries) and non-OPEC producers make the oil supply market a complex system, and thus, it is very difficult to model and to make predictions. In this paper, we combine the macro-model based on game theory and micro-model to propose a new approach for forecasting oil supply. We take into account the microscopic behaviour in the clearing market and also use the game relationships to adjust oil supplies in our approach. For the supply model, we analyse and consider the different behaviour of non-OPEC and OPEC producers. According to our analysis, limiting the oil supply, and thus maintaining oil price, is the best strategy for OPEC in the low-price scenario, while the rising supply is the best strategy in the high-price scenario. No matter what the oil price is, the dominant strategy for non-OPEC producers is to increase their oil supply. In the high-price scenario, OPEC will try to deplete non-OPEC's share in the oil supply market, which is to OPEC's advantage.

Retrospective stress-forecasting of earthquakes

NASA Astrophysics Data System (ADS)

Gao, Yuan; Crampin, Stuart

2015-04-01

Observations of changes in azimuthally varying shear-wave splitting (SWS) above swarms of small earthquakes monitor stress-induced changes to the stress-aligned vertical microcracks pervading the upper crust, lower crust, and uppermost ~400km of the mantle. (The microcracks are intergranular films of hydrolysed melt in the mantle.) Earthquakes release stress, and an appropriate amount of stress for the relevant magnitude must accumulate before each event. Iceland is on an extension of the Mid-Atlantic Ridge, where two transform zones, uniquely run onshore. These onshore transform zones provide semi-continuous swarms of small earthquakes, which are the only place worldwide where SWS can be routinely monitored. Elsewhere SWS must be monitored above temporally-active occasional swarms of small earthquakes, or in infrequent SKS and other teleseismic reflections from the mantle. Observations of changes in SWS time-delays are attributed to stress-induced changes in crack aspect-ratios allowing stress-accumulation and stress-relaxation to be identified. Monitoring SWS in SW Iceland in 1988, stress-accumulation before an impending earthquake was recognised and emails were exchanged between the University of Edinburgh (EU) and the Iceland Meteorological Office (IMO). On 10th November 1988, EU emailed IMO that a M5 earthquake could occur soon on a seismically-active fault plane where seismicity was still continuing following a M5.1 earthquake six-months earlier. Three-days later, IMO emailed EU that a M5 earthquake had just occurred on the specified fault-plane. We suggest this is a successful earthquake stress-forecast, where we refer to the procedure as stress-forecasting earthquakes as opposed to predicting or forecasting to emphasise the different formalism. Lack of funds has prevented us monitoring SWS on Iceland seismograms, however, we have identified similar characteristic behaviour of SWS time-delays above swarms of small earthquakes which have enabled us to retrospectively stress-forecasting ~17 earthquakes ranging in magnitude from a M1.7 swarm event in N Iceland, to the 1999 M7.7 Chi-Chi Earthquake in Taiwan, and the 2004 Mw9.2 Sumatra-Andaman Earthquake (SAE). Before SAE, the changes in SWS were observed at seismic stations in Iceland at a distance of ~10,500km the width of the Eurasian Plate, from Indonesia demonstrating the 'butterfly wings' sensitivity of the New Geophysics of a critically microcracked Earth. At that time, the sensitivity of the phenomena had not been recognised, and the SAE was not stress-forecast. These results have been published at various times in various formats in various journals. This presentation displays all the results in a normalised format that allows the similarities to be recognised, confirming that observations of SWS time-delays can stress-forecast the times, magnitudes, and in some circumstances fault-breaks, of impending earthquakes. Papers referring to these developments can be found in geos.ed.ac.uk/home/scrampin/opinion. Also see abstracts in EGU2015 Sessions: Crampin & Gao (SM1.1), Liu & Crampin (NH2.5), and Crampin & Gao (GD.1).

Exploring heterogeneous market hypothesis using realized volatility

NASA Astrophysics Data System (ADS)

Chin, Wen Cheong; Isa, Zaidi; Mohd Nor, Abu Hassan Shaari

2013-04-01

This study investigates the heterogeneous market hypothesis using high frequency data. The cascaded heterogeneous trading activities with different time durations are modelled by the heterogeneous autoregressive framework. The empirical study indicated the presence of long memory behaviour and predictability elements in the financial time series which supported heterogeneous market hypothesis. Besides the common sum-of-square intraday realized volatility, we also advocated two power variation realized volatilities in forecast evaluation and risk measurement in order to overcome the possible abrupt jumps during the credit crisis. Finally, the empirical results are used in determining the market risk using the value-at-risk approach. The findings of this study have implications for informationally market efficiency analysis, portfolio strategies and risk managements.

Time series behaviour of the number of Air Asia passengers: A distributional approach

NASA Astrophysics Data System (ADS)

Asrah, Norhaidah Mohd; Djauhari, Maman Abdurachman

2013-09-01

The common practice to time series analysis is by fitting a model and then further analysis is conducted on the residuals. However, if we know the distributional behavior of time series, the analyses in model identification, parameter estimation, and model checking are more straightforward. In this paper, we show that the number of Air Asia passengers can be represented as a geometric Brownian motion process. Therefore, instead of using the standard approach in model fitting, we use an appropriate transformation to come up with a stationary, normally distributed and even independent time series. An example in forecasting the number of Air Asia passengers will be given to illustrate the advantages of the method.

Forecasting volcanic eruptions: the control of elastic-brittle deformation

NASA Astrophysics Data System (ADS)

Kilburn, Christopher; Robertson, Robert; Wall, Richard; Steele, Alexander

2016-04-01

At volcanoes reawakening after long repose, patterns of unrest normally reflect the elastic-brittle deformation of crust above a magma reservoir. Local fault movements, detected as volcano-tectonic (VT) earthquakes, increase in number with surface deformation, at first approximately exponentially and then linearly. The trends describe how crustal behaviour evolves from quasi-elastic deformation under an increasing stress to inelastic deformation under a constant stress. They have been quantified and verified against experiments for deformation in compression [1]. We have extended the analysis to extensional deformation. The results agree well with field data for crust being stretched by a pressurizing magmatic system [2]. They also provide new criteria for enhancing the definitions of alert levels and preferred times to eruption. The VT-deformation sequence is a field proxy for changes in deformation with applied stress. The transition from quasi-elastic to inelastic behaviour is characterised in extension by the ratio of differential failure stress SF to tensile strength σT. Unrest data from at least basaltic to andesitic stratovolcanoes, as well as large calderas, yield preferred values for SF/σT ≤ 4, coinciding with the range for tensile failure expected from established theoretical constraints (from Mohr-Coulomb-Griffiths failure). We thus associate the transition with the approach to tensile rupture at the wall of a pressurized magma reservoir. In particular, values of about 2 are consistent with the rupture of a cylindrical reservoir, such as a closed conduit within a volcanic edifice, whereas values of about 3 suggest an approximately spherical reservoir, such as may exist at deeper levels. The onset of inelastic behaviour reflects the emergence of self-accelerating crack growth under a constant stress. Applied to forecasting eruptions, it provides a new and objective criterion for raising alert levels during an emergency; it yields the classic linear decrease in inverse-rate with time for VT seismicity, which can be extrapolated to an expected eruption time shortly after the inverse rate becomes zero [3]; and, for extension, it identifies preferred inverse-rate gradients of 0.001-0.01, which can be used to distinguish between physically-meaningful and spurious inverse-rate trends. [1] Kilburn CRJ (2012) J Geophys Res, doi: 10.1029/2011JB008703; [2] Robertson R, Kilburn CRJ (2016) Earth Planet Sci Lett, doi: 10.1016/j.epsl.2016.01.003; [3] Voight B (1988) Nature. 332: 125-130.

A survey for variable young stars with small telescopes: First results from HOYS-CAPS

NASA Astrophysics Data System (ADS)

Froebrich, D.; Campbell-White, J.; Scholz, A.; Eislöffel, J.; Zegmott, T.; Billington, S. J.; Donohoe, J.; Makin, S. V.; Hibbert, R.; Newport, R. J.; Pickard, R.; Quinn, N.; Rodda, T.; Piehler, G.; Shelley, M.; Parkinson, S.; Wiersema, K.; Walton, I.

2018-05-01

Variability in Young Stellar Objects (YSOs) is one of their primary characteristics. Long-term, multi-filter, high-cadence monitoring of large YSO samples is the key to understand the partly unusual light-curves that many of these objects show. Here we introduce and present the first results of the HOYS-CAPScitizen science project which aims to perform such monitoring for nearby (d < 1 kpc) and young (age < 10 Myr) clusters and star forming regions, visible from the northern hemisphere, with small telescopes. We have identified and characterised 466 variable (413 confirmed young) stars in 8 young, nearby clusters. All sources vary by at least 0.2 mag in V, have been observed at least 15 times in V, R and I in the same night over a period of about 2 yrs and have a Stetson index of larger than 1. This is one of the largest samples of variable YSOs observed over such a time-span and cadence in multiple filters. About two thirds of our sample are classical T-Tauri stars, while the rest are objects with depleted or transition disks. Objects characterised as bursters show by far the highest variability. Dippers and objects whose variability is dominated by occultations from normal interstellar dust or dust with larger grains (or opaque material) have smaller amplitudes. We have established a hierarchical clustering algorithm based on the light-curve properties which allows the identification of the YSOs with the most unusual behaviour, and to group sources with similar properties. We discuss in detail the light-curves of the unusual objects V2492 Cyg, V350 Cep and 2MASS J21383981+5708470.

Peralkaline Rhyolite Achneliths with Evidence of Post-Emplacement Vesiculation at Aluto Volcano, Main Ethiopian Rift: What can these unusual pyroclasts tell us?

NASA Astrophysics Data System (ADS)

Calder, E.; Clarke, B. A.; Cortes, J. A.; Butler, I. B.; Yirgu, G.

2016-12-01

In peralkaline rhyolitic melts, Na+ and K+ combined with halogens act to disrupt silicate polymers reducing melt viscosity in comparison to other melts of equivalent silica content. As a result, such magmas are often associated with somewhat unusual deposits for which the associated eruptive behaviours are relatively poorly understood. We have discovered unusual globule-shaped clasts within an unconsolidated pyroclastic succession associated with a pumice cone at Aluto volcano in the Main Ethiopian Rift. The clasts are lapilli to ash sized, often have a droplet-like morphology and are characterised by a distinctive obsidian skin indicative of having been shaped by surface tension. We adopt Walker's term achneliths for these clasts. These achneliths however, unlike their mafic counterparts, are highly vesicular ( 78 vol %), and the glassy skin often shows a bread-crusted texture. Importantly, there is strong evidence for post-depositional, in-situ, inflation, including expanding against other clasts and in some cases fusing together. The unconsolidated nature of the deposit at Aluto means that these peralkaline achneliths are easily separated and investigated in 3D, providing an unprecedented opportunity to study their features in detail through the use of µCT, SEM and EPMA. Textural observations and preliminary 3D vesicle size distribution data suggest that surface tension is an important factor in shaping these clasts, and that vesiculation and degassing occurs over a prolonged period post-emplacement. MELTS model calculations on the EPMA analyses assuming dry conditions, suggest maximum liquidus temperatures of 1030 °C and minimum viscosities of 6 Log(poise). These observations have important implications for understanding the nature of late stage degassing, fragmentation and eruption style in peralkaline rhyolite systems as well as incipient welding in peralkaline pyroclastic units.

Large PAMAM Dendron Induces Formation of Unusual P4332 Mesophase in Monoolein/Water system.

PubMed

Kumar, Manoj; Patil, Naganath G; Ambade, Ashootosh V; Kumaraswamy, Guruswamy

2018-05-18

Compact macromolecular dendrons have been shown to induce the formation of discontinuous inverse micellar assemblies with Fd3m symmetry in monoolein/water systems. Here, we demonstrate that a large PAMAM dendron (G5: fifth generation) induces the formation a very unusual mesophase with P4332 symmetry. This mesophase had previously been observed in monoolein/water systems only on addition of cytochrome C. The P4332 mesophase can be considered an intermediate phase between the bicontinuous Ia3d and discontinuous micellar mesophases. In this unusual phase, every third rod junction of the Ia3d mesophase is replaced with a spherical micelle. We present a detailed investigation of the phase behaviour of monoolein/water as a function of G5 concentration and temperature. Addition of 1% G5 in 85/15 monoolein/water system induces a transition from the L to Ia3d phase. Further increase in G5 concentration to above 2% induces the formation of the P4332 phase. Thus, incorporation of G5 yields a qualitatively different phase diagram when compared with incorporation of lower generation PAMAM dendrons (G2 - G4) in monoolein/water, where the reverse micellar Fd3m phase forms. PAMAM dendrons of all generations, G2 - G5, bear terminal amine groups that interact with the monoolein head group. The compact molecular architecture of the dendrons and these attractive interactions induce bending of the monoolein bilayer structure. For smaller dendrons, G2 - G4, this results in the formation of the Fd3m phase. However, the large size of the G5 dendron precludes this and a rare intermediate phase between the Ia3d and discontinuous micellar phase, the P4332 mesophase forms instead.

Rapid X-ray variability properties during the unusual very hard state in neutron-star low-mass X-ray binaries

NASA Astrophysics Data System (ADS)

Wijnands, R.; Parikh, A. S.; Altamirano, D.; Homan, J.; Degenaar, N.

2017-11-01

Here, we study the rapid X-ray variability (using XMM-Newton observations) of three neutron-star low-mass X-ray binaries (1RXS J180408.9-342058, EXO 1745-248 and IGR J18245-2452) during their recently proposed very hard spectral state. All our systems exhibit a strong to very strong noise component in their power density spectra (rms amplitudes ranging from 34 per cent to 102 per cent) with very low characteristic frequencies (as low as 0.01 Hz). These properties are more extreme than what is commonly observed in the canonical hard state of neutron-star low-mass X-ray binaries observed at X-ray luminosities similar to those we observe from our sources. This suggests that indeed the very hard state is a spectral-timing state distinct from the hard state, although we argue that the variability behaviour of IGR J18245-2452 is very extreme and possibly this source was in a very unusual state. We also compare our results with the rapid X-ray variability of the accreting millisecond X-ray pulsars IGR J00291+5934 and Swift J0911.9-6452 (also using XMM-Newton data) for which previously similar variability phenomena were observed. Although their energy spectra (as observed using the Swift X-ray telescope) were not necessarily as hard (i.e. for Swift J0911.9-6452) as for our other three sources, we conclude that likely both sources were also in very similar state during their XMM-Newton observations. This suggests that different sources that are found in this new state might exhibit different spectral hardness and one has to study both the spectral and the rapid variability to identify this unusual state.

Warming has a greater effect than elevated CO2 on predator-prey interactions in coral reef fish.

PubMed

Allan, Bridie J M; Domenici, Paolo; Watson, Sue Ann; Munday, Philip L; McCormick, Mark I

2017-06-28

Ocean acidification and warming, driven by anthropogenic CO 2 emissions, are considered to be among the greatest threats facing marine organisms. While each stressor in isolation has been studied extensively, there has been less focus on their combined effects, which could impact key ecological processes. We tested the independent and combined effects of short-term exposure to elevated CO 2 and temperature on the predator-prey interactions of a common pair of coral reef fishes ( Pomacentrus wardi and its predator, Pseudochromis fuscus ). We found that predator success increased following independent exposure to high temperature and elevated CO 2 Overall, high temperature had an overwhelming effect on the escape behaviour of the prey compared with the combined exposure to elevated CO 2 and high temperature or the independent effect of elevated CO 2 Exposure to high temperatures led to an increase in attack and predation rates. By contrast, we observed little influence of elevated CO 2 on the behaviour of the predator, suggesting that the attack behaviour of P. fuscus was robust to this environmental change. This is the first study to address how the kinematics and swimming performance at the basis of predator-prey interactions may change in response to concurrent exposure to elevated CO 2 and high temperatures and represents an important step to forecasting the responses of interacting species to climate change. © 2017 The Author(s).

Applying lessons from social psychology to transform the culture of error disclosure.

PubMed

Han, Jason; LaMarra, Denise; Vapiwala, Neha

2017-10-01

The ability to carry out prompt and effective error disclosure has been described in the literature as an essential skill among physicians that can lead to improved patient satisfaction, staff well-being and hospital outcomes. However, few studies have addressed the social psychology principles that may influence physician behaviour. The authors provide an overview of recent administrative measures designed to encourage physicians to disclose error, but note that deliberate practice, buttressed with lessons from social psychology, is needed to implement further productive behavioural changes. Two main cognitive biases that may hinder error disclosure are identified, namely: fundamental attribution error, and forecasting error. Strategies to overcome these maladaptive cognitive patterns are discussed. The authors note that interactions with standardised patients (SPs) can be used to simulate hospital encounters and help teach important behavioural considerations. Virtual reality is introduced as an immersive, realistic and easily scalable technology that can supplement traditional curricula. Lastly, the authors highlight the importance of establishing a professional standard of competence, potentially by incorporating difficult patient encounters, including disclosure of error, into medical licensing examinations that assess clinical skills. Existing curricula that cover physician error disclosure may benefit from reviewing the social psychology literature. These lessons, incorporated into SP programmes and emerging technological platforms, may improve training and evaluative methods for all medical trainees. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Saharan Air and Atlantic Tropical Cyclone Suppression From a Global Modeling Perspective

NASA Technical Reports Server (NTRS)

Reale, O.; Lau, W. K. M.; daSilva, A.; Kim, K.-M.

2007-01-01

During summer 2006, the NASA African Monsoon Multidisciplinary Analysis (NAMMA) organized a field campaign in Africa called Special Observation Period (SOP-3), in which scientists in the field were involved in a number of surface network and aircraft measurements. One of the scientific goals of the campaign was to understand the nature and causes for tropical cyclogenesis originating out of African Easterly Waves (AEWs, westward propagating atmospheric disturbances sometimes associated with precursors of hurricanes), and the role that the Saharan Air Layer (SAL, a hot and dry air layer advecting large amounts of dust) can play in the formation or suppression of tropical cyclones. During the NAMMA campaign a high-resolution global model, the NASA GEOS-5, was operationally run by the NASA Global Modeling and Assimilation Office (GMAO) in support to the mission. The daily GEOS-5 forecasts were found to be very useful by decision-making scientists in the field as an aid to discriminate between developing and non-developing AEWs and plan the flight tracks. In the post-event analyses which were performed mostly by the Goddard Laboratory for Atmospheres, two events were highlighted: a non-developing AEW which appeared to have been suppressed by Saharan air, compared to a developing AEW which was the precursor of hurricane Helene. Both events were successfully predicted by the GEOS-5 during the real-time forecasts provided in support to the mission. In this work it is found that very steep moisture gradients and a strong thermal dipole, with relatively warm air in the mid-troposphere and cool air below, are associated with SAL in both the GEOS-5 forecasts and the NCEP analyses, even at -great distance- from the Sahara. The presence of these unusual thermodynamic features over the Atlantic Ocean, at several thousands of kilometers from the African coastline, is suggestive that SAL mixing is very minimal and that the model's capability of retaining the different properties of air masses during transport are important to represent effectively the role of dry air intrusions in the tropical circulation.

Regional model studies of the atmospheric dispersion of fine volcanic ash after the eruption of Eyjafjallajoekull

NASA Astrophysics Data System (ADS)

Langmann, B.; Hort, M. K.

2010-12-01

During the eruption of Eyjafjallajoekull on Iceland in April/May 2010 air traffic over Europe was repeatedly interrupted because of volcanic ash in the atmosphere. This completely unusual situation in Europe leads to the demand of improved crisis management, e.g. European wide regulations of volcanic ash thresholds and improved forecasts of theses thresholds. However, the quality of the forecast of fine volcanic ash concentrations in the atmosphere depends to a great extent on a realistic description of the erupted mass flux of fine ash particles, which is rather uncertain. Numerous aerosol measurements (ground based and satellite remote sensing, and in situ measurements) all over Europe have tracked the volcanic ash clouds during the eruption of Eyjafjallajoekull offering the possibility for an interdisciplinary effort between volcanologists and aerosol researchers to analyse the release and dispersion of fine volcanic ash in order to better understand the needs for realistic volcanic ash forecasts. This contribution describes the uncertainties related to the amount of fine volcanic ash released from Eyjafjallajoekull and its influence on the dispersion of volcanic ash over Europe by numerical modeling. We use the three-dimensional Eulerian atmosphere-chemistry/aerosol model REMOTE (Langmann et al., 2008) to simulate the distribution of volcanic ash as well as its deposition after the eruptions of Eyjafjallajoekull during April and May 2010. The model has been used before to simulate the fate of the volcanic ash after the volcanic eruptions of Kasatochi in 2008 (Langmann et al., 2010) and Mt. Pinatubo in 1991. Comparing our model results with available measurements for the Eyjafjallajoekull eruption we find a quite good agreement with available ash concentrations data measured over Europe as well as with the results from other models. Langmann, B., K. Zakšek and M. Hort, Atmospheric distribution and removal of volcanic ash after the eruption of Kasatochi volcano: A regional model study, J. Geophys. Res., 115, D00L06, doi:10.1029/2009JD013298, 2010. Langmann, B., S. Varghese, E. Marmer, E. Vignati, J. Wilson, P. Stier and C. O’Dowd, Aerosol distribution over Europe: A model evaluation study with detailed aerosol microphysics, Atmos. Chem. Phys. 8, 1591-1607, 2008.

The energy density distribution of an ideal gas and Bernoulli’s equations

NASA Astrophysics Data System (ADS)

Santos, Leonardo S. F.

2018-05-01

This work discusses the energy density distribution in an ideal gas and the consequences of Bernoulli’s equation and the corresponding relation for compressible fluids. The aim of this work is to study how Bernoulli’s equation determines the energy flow in a fluid, although Bernoulli’s equation does not describe the energy density itself. The model from molecular dynamic considerations that describes an ideal gas at rest with uniform density is modified to explore the gas in motion with non-uniform density and gravitational effects. The difference between the component of the speed of a particle that is parallel to the gas speed and the gas speed itself is called ‘parallel random speed’. The pressure from the ‘parallel random speed’ is denominated as parallel pressure. The modified model predicts that the energy density is the sum of kinetic and potential gravitational energy densities plus two terms with static and parallel pressures. The application of Bernoulli’s equation and the corresponding relation for compressible fluids in the energy density expression has resulted in two new formulations. For incompressible and compressible gas, the energy density expressions are written as a function of stagnation, static and parallel pressures, without any dependence on kinetic or gravitational potential energy densities. These expressions of the energy density are the main contributions of this work. When the parallel pressure was uniform, the energy density distribution for incompressible approximation and compressible gas did not converge to zero for the limit of null static pressure. This result is rather unusual because the temperature tends to zero for null pressure. When the gas was considered incompressible and the parallel pressure was equal to static pressure, the energy density maintained this unusual behaviour with small pressures. If the parallel pressure was equal to static pressure, the energy density converged to zero for the limit of the null pressure only if the gas was compressible. Only the last situation describes an intuitive behaviour for an ideal gas.

Skill Assessment of An Hybrid Technique To Estimate Quantitative Precipitation Forecast For Galicia (nw Spain)

NASA Astrophysics Data System (ADS)

Lage, A.; Taboada, J. J.

Precipitation is the most obvious of the weather elements in its effects on normal life. Numerical weather prediction (NWP) is generally used to produce quantitative precip- itation forecast (QPF) beyond the 1-3 h time frame. These models often fail to predict small-scale variations of rain because of spin-up problems and their coarse spatial and temporal resolution (Antolik, 2000). Moreover, there are some uncertainties about the behaviour of the NWP models in extreme situations (de Bruijn and Brandsma, 2000). Hybrid techniques, combining the benefits of NWP and statistical approaches in a flexible way, are very useful to achieve a good QPF. In this work, a new technique of QPF for Galicia (NW of Spain) is presented. This region has a percentage of rainy days per year greater than 50% with quantities that may cause floods, with human and economical damages. The technique is composed of a NWP model (ARPS) and a statistical downscaling process based on an automated classification scheme of at- mospheric circulation patterns for the Iberian Peninsula (J. Ribalaygua and R. Boren, 1995). Results show that QPF for Galicia is improved using this hybrid technique. [1] Antolik, M.S. 2000 "An Overview of the National Weather Service's centralized statistical quantitative precipitation forecasts". Journal of Hydrology, 239, pp:306- 337. [2] de Bruijn, E.I.F and T. Brandsma "Rainfall prediction for a flooding event in Ireland caused by the remnants of Hurricane Charley". Journal of Hydrology, 239, pp:148-161. [3] Ribalaygua, J. and Boren R. "Clasificación de patrones espaciales de precipitación diaria sobre la España Peninsular". Informes N 3 y 4 del Servicio de Análisis e Investigación del Clima. Instituto Nacional de Meteorología. Madrid. 53 pp.

Fire danger assessment using ECMWF weather prediction system

NASA Astrophysics Data System (ADS)

Di Giuseppe, Francesca; Pappemberger, Florian; Wetterhall, Fredrik

2015-04-01

Weather plays a major role in the birth, growth and death of a wildfire wherever there is availability of combustible vegetation and suitable terrain topography. Prolonged dry periods creates favourable conditions for ignitions, wind can then increase the fire spread, while higher relative humidity, and precipitation (rain or snow) may decrease or extinguish it altogether. The European Forest Fire Information System (EFFIS), started in 2011 under the lead of the European Joint Research Centre (JRC) to monitor and forecast fire danger and fire behaviour in Europe. In 2012 a collaboration with the European Centre for Medium range Weather Forecast (ECMWF) was established to explore the potential of using state of the art weather forecast systems as driving forcing for the calculations of fire risk indices. From this collaboration in 2013 the EC-fire system was born. It implements the three most commonly used fire danger rating systems (NFDRS, FWI and MARK-5) and it is both initialised and forced by gridded atmospheric fields provided either by ECMWF re-analysis or ECMWF ensemble prediction systems. For consistency invariant fields (i.e fuel maps, vegetation cover, topogarphy) and real-time weather information are all provided on the same grid. Similarly global climatological vegetation stage conditions for each day of the year are provided by remote satellite observations. These climatological static maps substitute the traditional man judgement in an effort to create an automated procedure that can work in places where local observations are not available. The system has been in operation for the last year providing an ensemble of daily forecasts for fire indices with lead-times up to 10 days over Europe and Globally. An important part of the system is provided by its (re)-analysis dataset obtained by using the (re)-analysis forcings as drivers to calculate the fire risk indices. This is a crucial part of the whole chain since these fields are used to establish the initial conditions from which the forecast is subsequently run. The reanalysis dataset goes back to year 1980 (the starting year of ERA-Interim integrations) and is updated in quasi real time. In addition of providing the staring point for the operational forecasts it is a very useful dataset for the scope of calibration and verification of the system. Assuming reanalysis fields are good proxies for observations then, by comparison with fire events which really occurred, this dataset can be used to assess the potential predictability of fire risk indices. In this work we will introduce the EC-fire system. Then the reanalysis dataset will be used to identify regions of high fire risk predictability and where the system might be in need of further refinement.

A Behaviour Monitoring System (BMS) for Ambient Assisted Living

PubMed Central

Eisa, Samih

2017-01-01

Unusual changes in the regular daily mobility routine of an elderly person at home can be an indicator or early symptom of developing health problems. Sensor technology can be utilised to complement the traditional healthcare systems to gain a more detailed view of the daily mobility of a person at home when performing everyday tasks. We hypothesise that data collected from low-cost sensors such as presence and occupancy sensors can be analysed to provide insights on the daily mobility habits of the elderly living alone at home and to detect routine changes. We validate this hypothesis by designing a system that automatically learns the daily room-to-room transitions and permanence habits in each room at each time of the day and generates alarm notifications when deviations are detected. We present an algorithm to process the sensors’ data streams and compute sensor-driven features that describe the daily mobility routine of the elderly as part of the developed Behaviour Monitoring System (BMS). We are able to achieve low detection delay with confirmation time that is high enough to convey the detection of a set of common abnormal situations. We illustrate and evaluate BMS with synthetic data, generated by a developed data generator that was designed to mimic different user’s mobility profiles at home, and also with a real-life dataset collected from prior research work. Results indicate BMS detects several mobility changes that can be symptoms of common health problems. The proposed system is a useful approach for learning the mobility habits at the home environment, with the potential to detect behaviour changes that occur due to health problems, and therefore, motivating progress toward behaviour monitoring and elder’s care. PMID:28837105

Measurement Marker Recognition In A Time Sequence Of Infrared Images For Biomedical Applications

NASA Astrophysics Data System (ADS)

Fiorini, A. R.; Fumero, R.; Marchesi, R.

1986-03-01

In thermographic measurements, quantitative surface temperature evaluation is often uncertain. The main reason is in the lack of available reference points in transient conditions. Reflective markers were used for automatic marker recognition and pixel coordinate computations. An algorithm selects marker icons to match marker references where particular luminance conditions are satisfied. Automatic marker recognition allows luminance compensation and temperature calibration of recorded infrared images. A biomedical application is presented: the dynamic behaviour of the surface temperature distributions is investigated in order to study the performance of two different pumping systems for extracorporeal circulation. Sequences of images are compared and results are discussed. Finally, the algorithm allows to monitor the experimental environment and to alert for the presence of unusual experimental conditions.

The Relationship Between Subthreshold Autistic Traits, Ambiguous Figure Perception and Divergent Thinking.

PubMed

Best, Catherine; Arora, Shruti; Porter, Fiona; Doherty, Martin

2015-12-01

This research investigates the paradox of creativity in autism. That is, whether people with subclinical autistic traits have cognitive styles conducive to creativity or whether they are disadvantaged by the implied cognitive and behavioural rigidity of the autism phenotype. The relationship between divergent thinking (a cognitive component of creativity), perception of ambiguous figures, and self-reported autistic traits was evaluated in 312 individuals in a non-clinical sample. High levels of autistic traits were significantly associated with lower fluency scores on the divergent thinking tasks. However autistic traits were associated with high numbers of unusual responses on the divergent thinking tasks. Generation of novel ideas is a prerequisite for creative problem solving and may be an adaptive advantage associated with autistic traits.

Coulomb engineering of the bandgap and excitons in two-dimensional materials

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

Raja, Archana; Chaves, Andrey; Yu, Jaeeun

Here, the ability to control the size of the electronic bandgap is an integral part of solid-state technology. Atomically thin two-dimensional crystals offer a new approach for tuning the energies of the electronic states based on the unusual strength of the Coulomb interaction in these materials and its environmental sensitivity. Here, we show that by engineering the surrounding dielectric environment, one can tune the electronic bandgap and the exciton binding energy in monolayers of WS 2 and WSe 2 by hundreds of meV. We exploit this behaviour to present an in-plane dielectric heterostructure with a spatially dependent bandgap, as anmore » initial step towards the creation of diverse lateral junctions with nanoscale resolution.« less

Coulomb engineering of the bandgap and excitons in two-dimensional materials

DOE PAGES

Raja, Archana; Chaves, Andrey; Yu, Jaeeun; ...

2017-05-04

Here, the ability to control the size of the electronic bandgap is an integral part of solid-state technology. Atomically thin two-dimensional crystals offer a new approach for tuning the energies of the electronic states based on the unusual strength of the Coulomb interaction in these materials and its environmental sensitivity. Here, we show that by engineering the surrounding dielectric environment, one can tune the electronic bandgap and the exciton binding energy in monolayers of WS 2 and WSe 2 by hundreds of meV. We exploit this behaviour to present an in-plane dielectric heterostructure with a spatially dependent bandgap, as anmore » initial step towards the creation of diverse lateral junctions with nanoscale resolution.« less

Elastohydrodynamics of a free cylinder near a soft wall

NASA Astrophysics Data System (ADS)

Mahadevan, L.; Salez, Thomas

2015-11-01

We consider the motion of a fluid-immersed negatively buoyant particle in the vicinity of a thin compressible elastic wall. We use scaling arguments to establish different regimes of settling, sliding, rolling and complement these estimates using thin-film lubrication dynamics to determine an asymptotic theory for the sedimentation, sliding, and spinning motions of a cylinder. Numerical integration of the resulting equations confirms our scaling relations and further yields a range of behaviours such as spontaneously oscillations when sliding, lift via a Magnus-like effect, a spin-induced reversal effect, and an unusual sedimentation singularity. Our description also allows us to address a sedimentation-sliding transition that can lead to the particle coasting over very long distances, similar to certain geophysical phenomena.

Coulomb engineering of the bandgap and excitons in two-dimensional materials

PubMed Central

Raja, Archana; Chaves, Andrey; Yu, Jaeeun; Arefe, Ghidewon; Hill, Heather M.; Rigosi, Albert F.; Berkelbach, Timothy C.; Nagler, Philipp; Schüller, Christian; Korn, Tobias; Nuckolls, Colin; Hone, James; Brus, Louis E.; Heinz, Tony F.; Reichman, David R.; Chernikov, Alexey

2017-01-01

The ability to control the size of the electronic bandgap is an integral part of solid-state technology. Atomically thin two-dimensional crystals offer a new approach for tuning the energies of the electronic states based on the unusual strength of the Coulomb interaction in these materials and its environmental sensitivity. Here, we show that by engineering the surrounding dielectric environment, one can tune the electronic bandgap and the exciton binding energy in monolayers of WS2 and WSe2 by hundreds of meV. We exploit this behaviour to present an in-plane dielectric heterostructure with a spatially dependent bandgap, as an initial step towards the creation of diverse lateral junctions with nanoscale resolution. PMID:28469178

Adaptive responses and disruptive effects: how major wildfire influences kinship-based social interactions in a forest marsupial.

PubMed

Banks, Sam C; Blyton, Michaela D J; Blair, David; McBurney, Lachlan; Lindenmayer, David B

2012-02-01

Environmental disturbance is predicted to play a key role in the evolution of animal social behaviour. This is because disturbance affects key factors underlying social systems, such as demography, resource availability and genetic structure. However, because natural disturbances are unpredictable there is little information on their effects on social behaviour in wild populations. Here, we investigated how a major wildfire affected cooperation (sharing of hollow trees) by a hollow-dependent marsupial. We based two alternative social predictions on the impacts of fire on population density, genetic structure and resources. We predicted an adaptive social response from previous work showing that kin selection in den-sharing develops as competition for den resources increases. Thus, kin selection should occur in burnt areas because the fire caused loss of the majority of hollow-bearing trees, but no detectable mortality. Alternatively, fire may have a disruptive social effect, whereby postfire home range-shifts 'neutralize' fine-scale genetic structure, thereby removing opportunities for kin selection between neighbours. Both predictions occurred: the disruptive social effect in burnt habitat and the adaptive social response in adjacent unburnt habitat. The latter followed a massive demographic influx to unburnt 'refuge' habitat that increased competition for dens, leading to a density-related kin selection response. Our results show remarkable short-term plasticity of animal social behaviour and demonstrate how the social effects of disturbance extend into undisturbed habitat owing to landscape-scale demographic shifts. We predicted long-term changes in kinship-based cooperative behaviour resulting from the genetic and resource impacts of forecast changes to fire regimes in these forests. © 2011 Blackwell Publishing Ltd.

Solar Cycle 24 and the Solar Dynamo

NASA Technical Reports Server (NTRS)

Pesnell, W. D.; Schatten, K.

2007-01-01

We will discuss the polar field precursor method for solar activity prediction, which predicts cycle 24 will be significantly lower than recent activity cycles, and some new ideas rejuvenating Babcock's shallow surface dynamo. The polar field precursor method is based on Babcock and Leighton's dynamo models wherein the polar field at solar minimum plays a major role in generating the next cycle's toroidal field and sunspots. Thus, by examining the polar fields of the Sun near solar minimum, a forecast for the next cycle's activity is obtained. With the current low value for the Sun's polar fields, this method predicts solar cycle 24 will be one of the lowest in recent times, with smoothed F10.7 radio flux values peaking near 135 plus or minus 35 (2 sigma), in the 2012-2013 timeframe (equivalent to smoothed Rz near 80 plus or minus 35 [2 sigma]). One may have to consider solar activity as far back as the early 20th century to find a cycle of comparable magnitude. We discuss unusual behavior in the Sun's polar fields that support this prediction. Normally, the solar precursor method is consistent with the geomagnetic precursor method, wherein geomagnetic variations are thought to be a good measure of the Sun's polar field strength. Because of the unusual polar field, the Earth does not appear to be currently bathed in the Sun's extended polar field (the interplanetary field), hence negating the primal cause behind the geomagnetic precursor technique. We also discuss how percolation may support Babcock's original shallow solar dynamo. In this process ephemeral regions from the solar magnetic carpet, guided by shallow surface fields, may collect to form pores and sunspots.

Applying temporal abstraction and case-based reasoning to predict approaching influenza waves.

PubMed

Schmidt, Rainer; Gierl, Lothar

2002-01-01

The goal of the TeCoMed project is to send early warnings against forthcoming waves or even epidemics of infectious diseases, especially of influenza, to interested practitioners, pharmacists etc. in the German federal state Mecklenburg-Western Pomerania. The forecast of these waves is based on written confirmations of unfitness for work of the main German health insurance company. Since influenza waves are difficult to predict because of their cyclic but not regular behaviour, statistical methods based on the computation of mean values are not helpful. Instead, we have developed a prognostic model that makes use of similar former courses. Our method combines Case-based Reasoning with Temporal Abstraction to decide whether early warning is appropriate.

Forecasting and prediction of scorpion sting cases in Biskra province, Algeria, using a seasonal autoregressive integrated moving average model

PubMed Central

2016-01-01

OBJECTIVES The aims of this study were to highlight some epidemiological aspects of scorpion envenomations, to analyse and interpret the available data for Biskra province, Algeria, and to develop a forecasting model for scorpion sting cases in Biskra province, which records the highest number of scorpion stings in Algeria. METHODS In addition to analysing the epidemiological profile of scorpion stings that occurred throughout the year 2013, we used the Box-Jenkins approach to fit a seasonal autoregressive integrated moving average (SARIMA) model to the monthly recorded scorpion sting cases in Biskra from 2000 to 2012. RESULTS The epidemiological analysis revealed that scorpion stings were reported continuously throughout the year, with peaks in the summer months. The most affected age group was 15 to 49 years old, with a male predominance. The most prone human body areas were the upper and lower limbs. The majority of cases (95.9%) were classified as mild envenomations. The time series analysis showed that a (5,1,0)×(0,1,1)12 SARIMA model offered the best fit to the scorpion sting surveillance data. This model was used to predict scorpion sting cases for the year 2013, and the fitted data showed considerable agreement with the actual data. CONCLUSIONS SARIMA models are useful for monitoring scorpion sting cases, and provide an estimate of the variability to be expected in future scorpion sting cases. This knowledge is helpful in predicting whether an unusual situation is developing or not, and could therefore assist decision-makers in strengthening the province’s prevention and control measures and in initiating rapid response measures. PMID:27866407

Male brush-turkeys attempt sexual coercion in unusual circumstances.

PubMed

Wells, David A; Jones, Darryl N; Bulger, David; Brown, Culum

2014-07-01

Sexual coercion by males is generally understood to have three forms: forced copulation, harassment and intimidation. We studied Australian brush-turkeys, Alectura lathami, to determine whether some male behaviours towards females at incubation mounds could be classified as aggressive, whether males were attempting sexual coercion and, if so, whether the coercion was successful. We found that some male behaviours towards females were significantly more likely to be followed by the cessation of female mound activity, and hence could be classified as aggressive, while others were significantly more likely to be followed by the commencement of female mound activity, and hence could be classified as enticing. Copulation was preceded by higher rates of male enticement and by higher rates of certain types of male aggression. It therefore seemed that males were attempting sexual coercion. There was little evidence, however, that this combination of coercion and enticement was successful in obtaining copulations. While forced copulation did occur, it was infrequent, and no evidence could be found for intimidation. We conclude that harassment is the primary form of sexual coercion by male brush-turkeys. Although sexual coercion is understood to be a sub-optimal tactic, brush-turkey sexual coercion was employed as a primary tactic by dominant males who owned incubation mounds. One possible explanation for this apparent paradox is that aggression is the default solution for social conflicts in this species, and hence can be interpreted as a behavioural syndrome. Copyright © 2014 Elsevier B.V. All rights reserved.

Why are there so many explanations for primate brain evolution?

PubMed Central

2017-01-01

The question as to why primates have evolved unusually large brains has received much attention, with many alternative proposals all supported by evidence. We review the main hypotheses, the assumptions they make and the evidence for and against them. Taking as our starting point the fact that every hypothesis has sound empirical evidence to support it, we argue that the hypotheses are best interpreted in terms of a framework of evolutionary causes (selection factors), consequences (evolutionary windows of opportunity) and constraints (usually physiological limitations requiring resolution if large brains are to evolve). Explanations for brain evolution in birds and mammals generally, and primates in particular, have to be seen against the backdrop of the challenges involved with the evolution of coordinated, cohesive, bonded social groups that require novel social behaviours for their resolution, together with the specialized cognition and neural substrates that underpin this. A crucial, but frequently overlooked, issue is that fact that the evolution of large brains required energetic, physiological and time budget constraints to be overcome. In some cases, this was reflected in the evolution of ‘smart foraging’ and technical intelligence, but in many cases required the evolution of behavioural competences (such as coalition formation) that required novel cognitive skills. These may all have been supported by a domain-general form of cognition that can be used in many different contexts. This article is part of the themed issue ‘Physiological determinants of social behaviour in animals’. PMID:28673920

Kinship and altruism: a cross-cultural experimental study.

PubMed

Madsen, Elainie A; Tunney, Richard J; Fieldman, George; Plotkin, Henry C; Dunbar, Robin I M; Richardson, Jean-Marie; McFarland, David

2007-05-01

Humans are characterized by an unusual level of prosociality. Despite this, considerable indirect evidence suggests that biological kinship plays an important role in altruistic behaviour. All previous reports of the influence of kin selection on human altruism have, however, used correlational (rather than experimental) designs, or imposed only a hypothetical or negligible time cost on participants. Since these research designs fail either to control for confounding variables or to meet the criteria required as a test of Hamilton's rule for kin selection (that the altruist pays a true cost), they fail to establish unequivocally whether kin selection plays a role. We show that individuals from two different cultures behave in accordance with Hamilton's rule by acting more altruistically (imposing a higher physical cost upon themselves) towards more closely related individuals. Three possible sources of confound were ruled out: generational effects, sexual attraction and reciprocity. Performance on the task however did not exhibit a perfect linear relationship with relatedness, which might reflect either the intrusion of other variables (e.g. cultural differences in the way kinship is costed) or that our behavioural measure is insufficiently sensitive to fine-tuned differences in the way individuals view their social world. These findings provide the first unequivocal experimental evidence that kinship plays a role in moderating altruistic behaviour. Kinship thus represents a baseline against which individuals pitch other criteria (including reciprocity, prosociality, obligation and a moral sense) when deciding how to behave towards others.

Monitoring of Engineering Buildings Behaviour Within the Disaster Management System

NASA Astrophysics Data System (ADS)

Oku Topal, G.; Gülal, E.

2017-11-01

The Disaster management aims to prevent events that result in disaster or to reduce their losses. Monitoring of engineering buildings, identification of unusual movements and taking the necessary precautions are very crucial for determination of the disaster risk so possible prevention could be taken to reduce big loss. Improving technology, increasing population due to increased construction and these areas largest economy lead to offer damage detection strategies. Structural Health Monitoring (SHM) is the most effective of these strategies. SHM research is very important to maintain all this structuring safely. The purpose of structural monitoring is determining in advance of possible accidents and taking necessary precaution. In this paper, determining the behaviour of construction using Global Positioning System (GPS) is investigated. For this purpose shaking table tests were performed. Shaking table was moved at different amplitude and frequency aiming to determine these movement with a GPS measuring system. The obtained data were evaluated by analysis of time series and Fast Fourier Transformation techniques and the frequency and amplitude values are calculated. By examining the results of the tests made, it will be determined whether the GPS measurement method can accurately detect the movements of the engineering structures.

Chemical camouflage--a frog's strategy to co-exist with aggressive ants.

PubMed

Rödel, Mark-Oliver; Brede, Christian; Hirschfeld, Mareike; Schmitt, Thomas; Favreau, Philippe; Stöcklin, Reto; Wunder, Cora; Mebs, Dietrich

2013-01-01

Whereas interspecific associations receive considerable attention in evolutionary, behavioural and ecological literature, the proximate bases for these associations are usually unknown. This in particular applies to associations between vertebrates with invertebrates. The West-African savanna frog Phrynomantis microps lives in the underground nest of ponerine ants (Paltothyreus tarsatus). The ants usually react highly aggressively when disturbed by fiercely stinging, but the frog is not attacked and lives unharmed among the ants. Herein we examined the proximate mechanisms for this unusual association. Experiments with termites and mealworms covered with the skin secretion of the frog revealed that specific chemical compounds seem to prevent the ants from stinging. By HPLC-fractionation of an aqueous solution of the frogs' skin secretion, two peptides of 1,029 and 1,143 Da were isolated and found to inhibit the aggressive behaviour of the ants. By de novo sequencing using tandem mass spectrometry, the amino acid sequence of both peptides consisting of a chain of 9 and 11 residues, respectively, was elucidated. Both peptides were synthesized and tested, and exhibited the same inhibitory properties as the original frog secretions. These novel peptides most likely act as an appeasement allomone and may serve as models for taming insect aggression.

Unusual behaviour of (Np,Pu)B2C

NASA Astrophysics Data System (ADS)

Klimczuk, Tomasz; Boulet, Pascal; Griveau, Jean-Christophe; Colineau, Eric; Bauer, Ernst; Falmbigl, Matthias; Rogl, Peter; Wastin, Franck

2015-02-01

Two transuranium metal boron carbides, NpB2C and PuB2C have been synthesized by argon arc melting. The crystal structures of the {Np,Pu}B2C compounds were determined from single-crystal X-ray data to be isotypic with the ThB2C-type (space group ?, a = 0.6532(2) nm; c = 1.0769(3) nm for NpB2C and a = 0.6509(2) nm; c = 1.0818(3) nm for PuB2C; Z = 9). Physical properties have been derived from polycrystalline bulk material in the temperature range from 2 to 300 K and in magnetic fields up to 9 T. Magnetic susceptibility and heat capacity data indicate the occurrence of antiferromagnetic ordering for NpB2C with a Neel temperature TN = 68 K. PuB2C is a Pauli paramagnet most likely due to a strong hybridization of s(p,d) electrons with the Pu-5f states. A pseudo-gap, as concluded from the Sommerfeld value and the electronic transport, is thought to be a consequence of the hybridization. The magnetic behaviour of {Np,Pu}B2C is consistent with the criterion of Hill.

The meta-Gaussian Bayesian Processor of forecasts and associated preliminary experiments

NASA Astrophysics Data System (ADS)

Chen, Fajing; Jiao, Meiyan; Chen, Jing

2013-04-01

Public weather services are trending toward providing users with probabilistic weather forecasts, in place of traditional deterministic forecasts. Probabilistic forecasting techniques are continually being improved to optimize available forecasting information. The Bayesian Processor of Forecast (BPF), a new statistical method for probabilistic forecast, can transform a deterministic forecast into a probabilistic forecast according to the historical statistical relationship between observations and forecasts generated by that forecasting system. This technique accounts for the typical forecasting performance of a deterministic forecasting system in quantifying the forecast uncertainty. The meta-Gaussian likelihood model is suitable for a variety of stochastic dependence structures with monotone likelihood ratios. The meta-Gaussian BPF adopting this kind of likelihood model can therefore be applied across many fields, including meteorology and hydrology. The Bayes theorem with two continuous random variables and the normal-linear BPF are briefly introduced. The meta-Gaussian BPF for a continuous predictand using a single predictor is then presented and discussed. The performance of the meta-Gaussian BPF is tested in a preliminary experiment. Control forecasts of daily surface temperature at 0000 UTC at Changsha and Wuhan stations are used as the deterministic forecast data. These control forecasts are taken from ensemble predictions with a 96-h lead time generated by the National Meteorological Center of the China Meteorological Administration, the European Centre for Medium-Range Weather Forecasts, and the US National Centers for Environmental Prediction during January 2008. The results of the experiment show that the meta-Gaussian BPF can transform a deterministic control forecast of surface temperature from any one of the three ensemble predictions into a useful probabilistic forecast of surface temperature. These probabilistic forecasts quantify the uncertainty of the control forecast; accordingly, the performance of the probabilistic forecasts differs based on the source of the underlying deterministic control forecasts.

Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

NASA Astrophysics Data System (ADS)

Zhao, T.; Cai, X.; Yang, D.

2010-12-01

Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover, streamflow variability and reservoir capacity can change the magnitude of the effects of forecast uncertainty, but not the relative merit of DSF, DPSF, and ESF. Schematic diagram of the increase in forecast uncertainty with forecast lead-time and the dynamic updating property of real-time streamflow forecast

Optimization of landfill leachate management in the aftercare period.

PubMed

Wang, Yu; Pelkonen, Markku; Kaila, Juha

2012-08-01

The management of sanitary landfills after closure is an important engineering, economic and sustainability issue and is referred to as the greatest unresolved landfill challenge. Most sanitary landfills are operated according to the dry tomb principle, resulting in aftercare periods of hundreds of years. To study landfill body behaviour, long-term leachate emissions were studied with anaerobic landfill simulators, and a forecast model was developed targeting the behaviour of NH(4)-N, COD and chlorides as a function of temperature and the L/S-ratio (liquid-to-solid). It was found that NH(4)-N is the decisive factor in leachate management, requiring the highest L/S-ratio (around 6) to meet the direct discharge limit values. Various scenarios were constructed to find optimal leachate management strategies both in large (waste height H = 25 m) and medium-sized landfills (H = 10 m) with corresponding temperature ranges. The results show that by minimizing the aftercare period length with leachate pre-treatment and recirculation, both sustainability and economic benefits can be achieved. The results provide new views on how to manage the long-term leachate aftercare problem. In the case of large landfills, further efforts are needed to reach stabilization within a reasonable time frame.

An Integrated Crustal Dynamics Simulator

NASA Astrophysics Data System (ADS)

Xing, H. L.; Mora, P.

2007-12-01

Numerical modelling offers an outstanding opportunity to gain an understanding of the crustal dynamics and complex crustal system behaviour. This presentation provides our long-term and ongoing effort on finite element based computational model and software development to simulate the interacting fault system for earthquake forecasting. A R-minimum strategy based finite-element computational model and software tool, PANDAS, for modelling 3-dimensional nonlinear frictional contact behaviour between multiple deformable bodies with the arbitrarily-shaped contact element strategy has been developed by the authors, which builds up a virtual laboratory to simulate interacting fault systems including crustal boundary conditions and various nonlinearities (e.g. from frictional contact, materials, geometry and thermal coupling). It has been successfully applied to large scale computing of the complex nonlinear phenomena in the non-continuum media involving the nonlinear frictional instability, multiple material properties and complex geometries on supercomputers, such as the South Australia (SA) interacting fault system, South California fault model and Sumatra subduction model. It has been also extended and to simulate the hot fractured rock (HFR) geothermal reservoir system in collaboration of Geodynamics Ltd which is constructing the first geothermal reservoir system in Australia and to model the tsunami generation induced by earthquakes. Both are supported by Australian Research Council.

Design and validation of a Cannabis Use Intention Questionnaire (CUIQ) for adolescents.

PubMed

Lloret Irles, Daniel; Morell-Gomis, Ramón; Laguía, Ana; Moriano, Juan A

2018-01-01

In Spain, one in four 14 to 18-year-old adolescents has used cannabis during the last twelve months. Demand for treatment has increased in European countries. These facts have prompted the development of preventive interventions that require screening tools in order to identify the vulnerable population and to properly asses the efficacy of such interventions. The Theory of Planned Behaviour (TPB), widely used to forecast behavioural intention, has also demonstrated a good predictive capacity in addictions. The aim of this study is to design and validate a Cannabis Use Intention Questionnaire (CUIQ) based on TPB. 1,011 teenagers answered a set of tests to assess attitude towards use, subjective norms, self-efficacy towards non-use, and intention to use cannabis. CUIQ had good psychometric properties. Structural Equation Modelling results confirm the predictive model on intention to use cannabis in the Spanish adolescent sample, classified as users and non-users, explaining 40% of variance of intention to consume. CUIQ is aimed at providing a better understanding of the psychological processes that lead to cannabis use and allowing the evaluation of programmes. This can be particularly useful for improving the design and implementation of selective prevention programmes.

Estimate of the Reliability in Geological Forecasts for Tunnels: Toward a Structured Approach

NASA Astrophysics Data System (ADS)

Perello, Paolo

2011-11-01

In tunnelling, a reliable geological model often allows providing an effective design and facing the construction phase without unpleasant surprises. A geological model can be considered reliable when it is a valid support to correctly foresee the rock mass behaviour, therefore preventing unexpected events during the excavation. The higher the model reliability, the lower the probability of unforeseen rock mass behaviour. Unfortunately, owing to different reasons, geological models are affected by uncertainties and a fully reliable knowledge of the rock mass is, in most cases, impossible. Therefore, estimating to which degree a geological model is reliable, becomes a primary requirement in order to save time and money and to adopt the appropriate construction strategy. The definition of the geological model reliability is often achieved by engineering geologists through an unstructured analytical process and variable criteria. This paper focusses on geological models for projects of linear underground structures and represents an effort to analyse and include in a conceptual framework the factors influencing such models. An empirical parametric procedure is then developed with the aim of obtaining an index called "geological model rating (GMR)", which can be used to provide a more standardised definition of a geological model reliability.

Smart City Mobility Application--Gradient Boosting Trees for Mobility Prediction and Analysis Based on Crowdsourced Data.

PubMed

Semanjski, Ivana; Gautama, Sidharta

2015-07-03

Mobility management represents one of the most important parts of the smart city concept. The way we travel, at what time of the day, for what purposes and with what transportation modes, have a pertinent impact on the overall quality of life in cities. To manage this process, detailed and comprehensive information on individuals' behaviour is needed as well as effective feedback/communication channels. In this article, we explore the applicability of crowdsourced data for this purpose. We apply a gradient boosting trees algorithm to model individuals' mobility decision making processes (particularly concerning what transportation mode they are likely to use). To accomplish this we rely on data collected from three sources: a dedicated smartphone application, a geographic information systems-based web interface and weather forecast data collected over a period of six months. The applicability of the developed model is seen as a potential platform for personalized mobility management in smart cities and a communication tool between the city (to steer the users towards more sustainable behaviour by additionally weighting preferred suggestions) and users (who can give feedback on the acceptability of the provided suggestions, by accepting or rejecting them, providing an additional input to the learning process).

Weather forecasting expert system study

NASA Technical Reports Server (NTRS)

1985-01-01

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

Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

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

Hoff, Thomas Hoff; Kankiewicz, Adam

Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California Independent System Operator’s (ISO) load forecasts by integrating behind-the-meter (BTM) PV forecasts. The three, new, state-of-the-art solar irradiance forecasting models included: the infrared (IR) satellite-based cloud motion vector (CMV) model; the WRF-SolarCA model and variants; and the Optimized Deep Machine Learning (ODML)-training model. The first two forecasting models targeted known weaknesses in current operational solar forecasts. They were benchmarked against existing operational numerical weather prediction (NWP)more » forecasts, visible satellite CMV forecasts, and measured PV plant power production. IR CMV, WRF-SolarCA, and ODML-training forecasting models all improved the forecast to a significant degree. Improvements varied depending on time of day, cloudiness index, and geographic location. The fourth objective was to demonstrate that the California ISO’s load forecasts could be improved by integrating BTM PV forecasts. This objective represented the project’s most exciting and applicable gains. Operational BTM forecasts consisting of 200,000+ individual rooftop PV forecasts were delivered into the California ISO’s real-time automated load forecasting (ALFS) environment. They were then evaluated side-by-side with operational load forecasts with no BTM-treatment. Overall, ALFS-BTM day-ahead (DA) forecasts performed better than baseline ALFS forecasts when compared to actual load data. Specifically, ALFS-BTM DA forecasts were observed to have the largest reduction of error during the afternoon on cloudy days. Shorter term 30 minute-ahead ALFS-BTM forecasts were shown to have less error under all sky conditions, especially during the morning time periods when traditional load forecasts often experience their largest uncertainties. This work culminated in a GO decision being made by the California ISO to include zonal BTM forecasts into its operational load forecasting system. The California ISO’s Manager of Short Term Forecasting, Jim Blatchford, summarized the research performed in this project with the following quote: “The behind-the-meter (BTM) California ISO region forecasting research performed by Clean Power Research and sponsored by the Department of Energy’s SUNRISE program was an opportunity to verify value and demonstrate improved load forecast capability. In 2016, the California ISO will be incorporating the BTM forecast into the Hour Ahead and Day Ahead load models to look for improvements in the overall load forecast accuracy as BTM PV capacity continues to grow.”« less

Influence of sea-ice coverage, sea-surface temperatures and latent heat release on baroclinic instability of an Arctic cyclone

NASA Astrophysics Data System (ADS)

Semenov, A.; Zhang, X.

2012-12-01

Arctic sea ice has shrunk drastically and Arctic storm activity has intensified over last decades. To improve understanding air-ice-sea interactions in the context of storm activity, we conducted a modeling study of a selected intense storm that invaded and was persistent for prolonged time in the central Arctic Ocean during March 16-22, 2011. A series of control and sensitivity simulations were carried out by employing the Weather Research and Forecasting (WRF) model, which was configured using two nested domains at a resolution of 10 km for the inner domain and 30 km for the outer domain. The control simulations well captured the cyclone genesis, regeneration, track and intensity. Diagnostic analysis and a comparison between the and sensitivity experiments suggest that the strong intensity, regeneration, and long-lasting duration of the cyclone were driven by unusually sustained baroclinic instability, which was resulted due to (1) anomalously reduced sea-ice coverage and strong advection of heat, moisture and vorticity from the North Atlantic; and (2) a release of latent heat due to condensation.

A window of opportunity for climate-change adaptation: Easing tree mortality by reducing forest basal area

USGS Publications Warehouse

Bradford, John B.; Bell, David M.

2017-01-01

Increasing aridity as a result of climate change is expected to exacerbate tree mortality. Reducing forest basal area – the cross-sectional area of tree stems within a given ground area – can decrease tree competition, which may reduce drought-induced tree mortality. However, neither the magnitude of expected mortality increases, nor the potential effectiveness of basal area reduction, has been quantified in dryland forests such as those of the drought-prone Southwest US. We used thousands of repeatedly measured forest plots to show that unusually warm and dry conditions are related to high tree mortality rates and that mortality is positively related to basal area. Those relationships suggest that while increasing high temperature extremes forecasted by climate models may lead to elevated tree mortality during the 21st century, future tree mortality might be partly ameliorated by reducing stand basal area. This adaptive forest management strategy may provide a window of opportunity for forest managers and policy makers to guide forest transitions to species and/or genotypes more suited to future climates.

Driving Roles of Tropospheric and Stratospheric Thermal Anomalies in Intensification and Persistence of the Arctic Superstorm in 2012

NASA Astrophysics Data System (ADS)

Tao, Wei; Zhang, Jing; Fu, Yunfei; Zhang, Xiangdong

2017-10-01

Intense synoptic-scale storms have been more frequently observed over the Arctic during recent years. Specifically, a superstorm hit the Arctic Ocean in August 2012 and preceded a new record low Arctic sea ice extent. In this study, the major physical processes responsible for the storm's intensification and persistence are explored through a series of numerical modeling experiments with the Weather Research and Forecasting model. It is found that thermal anomalies in troposphere as well as lower stratosphere jointly lead to the development of this superstorm. Thermal contrast between the unusually warm Siberia and the relatively cold Arctic Ocean results in strong troposphere baroclinicity and upper level jet, which contribute to the storm intensification initially. On the other hand, Tropopause Polar Vortex (TPV) associated with the thermal anomaly in lower stratosphere further intensifies the upper level jet and accordingly contributes to a drastic intensification of the storm. Stacking with the enhanced surface low, TPV intensifies further, which sustains the storm to linger over the Arctic Ocean for an extended period.

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

Rice, C Keith; Uselton, Robert B.; Shen, Bo

A residential-sized dual air-source integrated heat pump (AS-IHP) concept is under development in partnership between ORNL and a manufacturer. The concept design consists of a two-stage air-source heat pump (ASHP) coupled on the air distribution side with a separate novel water heating/dehumidification (WH/DH) module. The motivation for this unusual equipment combination is the forecast trend for home sensible loads to be reduced more than latent loads. Integration of water heating with a space dehumidification cycle addresses humidity control while performing double-duty. This approach can be applied to retrofit/upgrade applications as well as new construction. A WH/DH module capable of ~1.47more » L/h water removal and ~2 kW water heating capacity was assembled by the manufacturer. A heat pump system model was used to guide the controls design; lab testing was conducted and used to calibrate the models. Performance maps were generated and used in a TRNSYS sub-hourly simulation to predict annual performance in a well-insulated house. Annual HVAC/WH energy savings of ~35% are predicted in cold and hot-humid U.S. climates compared to a minimum efficiency baseline.« less

Optimising seasonal streamflow forecast lead time for operational decision making in Australia

NASA Astrophysics Data System (ADS)

Schepen, Andrew; Zhao, Tongtiegang; Wang, Q. J.; Zhou, Senlin; Feikema, Paul

2016-10-01

Statistical seasonal forecasts of 3-month streamflow totals are released in Australia by the Bureau of Meteorology and updated on a monthly basis. The forecasts are often released in the second week of the forecast period, due to the onerous forecast production process. The current service relies on models built using data for complete calendar months, meaning the forecast production process cannot begin until the first day of the forecast period. Somehow, the bureau needs to transition to a service that provides forecasts before the beginning of the forecast period; timelier forecast release will become critical as sub-seasonal (monthly) forecasts are developed. Increasing the forecast lead time to one month ahead is not considered a viable option for Australian catchments that typically lack any predictability associated with snowmelt. The bureau's forecasts are built around Bayesian joint probability models that have antecedent streamflow, rainfall and climate indices as predictors. In this study, we adapt the modelling approach so that forecasts have any number of days of lead time. Daily streamflow and sea surface temperatures are used to develop predictors based on 28-day sliding windows. Forecasts are produced for 23 forecast locations with 0-14- and 21-day lead time. The forecasts are assessed in terms of continuous ranked probability score (CRPS) skill score and reliability metrics. CRPS skill scores, on average, reduce monotonically with increase in days of lead time, although both positive and negative differences are observed. Considering only skilful forecast locations, CRPS skill scores at 7-day lead time are reduced on average by 4 percentage points, with differences largely contained within +5 to -15 percentage points. A flexible forecasting system that allows for any number of days of lead time could benefit Australian seasonal streamflow forecast users by allowing more time for forecasts to be disseminated, comprehended and made use of prior to the commencement of a forecast season. The system would allow for forecasts to be updated if necessary.

Evaluation of ensemble forecast uncertainty using a new proper score: application to medium-range and seasonal forecasts

NASA Astrophysics Data System (ADS)

Christensen, Hannah; Moroz, Irene; Palmer, Tim

2015-04-01

Forecast verification is important across scientific disciplines as it provides a framework for evaluating the performance of a forecasting system. In the atmospheric sciences, probabilistic skill scores are often used for verification as they provide a way of unambiguously ranking the performance of different probabilistic forecasts. In order to be useful, a skill score must be proper -- it must encourage honesty in the forecaster, and reward forecasts which are reliable and which have good resolution. A new score, the Error-spread Score (ES), is proposed which is particularly suitable for evaluation of ensemble forecasts. It is formulated with respect to the moments of the forecast. The ES is confirmed to be a proper score, and is therefore sensitive to both resolution and reliability. The ES is tested on forecasts made using the Lorenz '96 system, and found to be useful for summarising the skill of the forecasts. The European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system (EPS) is evaluated using the ES. Its performance is compared to a perfect statistical probabilistic forecast -- the ECMWF high resolution deterministic forecast dressed with the observed error distribution. This generates a forecast that is perfectly reliable if considered over all time, but which does not vary from day to day with the predictability of the atmospheric flow. The ES distinguishes between the dynamically reliable EPS forecasts and the statically reliable dressed deterministic forecasts. Other skill scores are tested and found to be comparatively insensitive to this desirable forecast quality. The ES is used to evaluate seasonal range ensemble forecasts made with the ECMWF System 4. The ensemble forecasts are found to be skilful when compared with climatological or persistence forecasts, though this skill is dependent on region and time of year.

Value of long-term streamflow forecast to reservoir operations for water supply in snow-dominated catchments

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

Anghileri, Daniela; Voisin, Nathalie; Castelletti, Andrea F.

In this study, we develop a forecast-based adaptive control framework for Oroville reservoir, California, to assess the value of seasonal and inter-annual forecasts for reservoir operation.We use an Ensemble Streamflow Prediction (ESP) approach to generate retrospective, one-year-long streamflow forecasts based on the Variable Infiltration Capacity hydrology model. The optimal sequence of daily release decisions from the reservoir is then determined by Model Predictive Control, a flexible and adaptive optimization scheme.We assess the forecast value by comparing system performance based on the ESP forecasts with that based on climatology and a perfect forecast. In addition, we evaluate system performance based onmore » a synthetic forecast, which is designed to isolate the contribution of seasonal and inter-annual forecast skill to the overall value of the ESP forecasts.Using the same ESP forecasts, we generalize our results by evaluating forecast value as a function of forecast skill, reservoir features, and demand. Our results show that perfect forecasts are valuable when the water demand is high and the reservoir is sufficiently large to allow for annual carry-over. Conversely, ESP forecast value is highest when the reservoir can shift water on a seasonal basis.On average, for the system evaluated here, the overall ESP value is 35% less than the perfect forecast value. The inter-annual component of the ESP forecast contributes 20-60% of the total forecast value. Improvements in the seasonal component of the ESP forecast would increase the overall ESP forecast value between 15 and 20%.« less

Improved Anvil Forecasting

NASA Technical Reports Server (NTRS)

Lambert, Winifred C.

2000-01-01

This report describes the outcome of Phase 1 of the AMU's Improved Anvil Forecasting task. Forecasters in the 45th Weather Squadron and the Spaceflight Meteorology Group have found that anvil forecasting is a difficult task when predicting LCC and FR violations. The purpose of this task is to determine the technical feasibility of creating an anvil-forecasting tool. Work on this study was separated into three steps: literature search, forecaster discussions, and determination of technical feasibility. The literature search revealed no existing anvil-forecasting techniques. However, there appears to be growing interest in anvils in recent years. If this interest continues to grow, more information will be available to aid in developing a reliable anvil-forecasting tool. The forecaster discussion step revealed an array of methods on how better forecasting techniques could be developed. The forecasters have ideas based on sound meteorological principles and personal experience in forecasting and analyzing anvils. Based on the information gathered in the discussions with the forecasters, the conclusion of this report is that it is technically feasible at this time to develop an anvil forecasting technique that will significantly contribute to the confidence in anvil forecasts.

Bird Migration Under Climate Change - A Mechanistic Approach Using Remote Sensing

NASA Technical Reports Server (NTRS)

Smith, James A.; Blattner, Tim; Messmer, Peter

2010-01-01

The broad-scale reductions and shifts that may be expected under climate change in the availability and quality of stopover habitat for long-distance migrants is an area of increasing concern for conservation biologists. Researchers generally have taken two broad approaches to the modeling of migration behaviour to understand the impact of these changes on migratory bird populations. These include models based on causal processes and their response to environmental stimulation, "mechanistic models", or models that primarily are based on observed animal distribution patterns and the correlation of these patterns with environmental variables, i.e. "data driven" models. Investigators have applied the latter technique to forecast changes in migration patterns with changes in the environment, for example, as might be expected under climate change, by forecasting how the underlying environmental data layers upon which the relationships are built will change over time. The learned geostatstical correlations are then applied to the modified data layers.. However, this is problematic. Even if the projections of how the underlying data layers will change are correct, it is not evident that the statistical relationships will remain the same, i.e. that the animal organism may not adapt its' behaviour to the changing conditions. Mechanistic models that explicitly take into account the physical, biological, and behaviour responses of an organism as well as the underlying changes in the landscape offer an alternative to address these shortcomings. The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies enable the application of the mechanistic models to predict how continental bird migration patterns may change in response to environmental change. In earlier work, we simulated the impact of effects of wetland loss and inter-annual variability on the fitness of migratory shorebirds in the central fly ways of North America. We demonstrated the phenotypic plasticity of a migratory population of Pectoral sandpipers consisting of an ensemble of 10,000 individual birds in response to changes in stopover locations using an individual based migration model driven by remotely sensed land surface data, climate data and biological field data. With the advent of new computing capabilities enabled hy recent GPU-GP computing paradigms and commodity hardware, it now is possible to simulate both larger ensemble populations and to incorporate more realistic mechanistic factors into migration models. Here, we take our first steps use these tools to study the impact of long-term drought variability on shorebird survival.

Family violence: guidelines for recognition and management

PubMed Central

Ghent, William R.; Da Sylva, Normand P.; Farren, Margo E.

1985-01-01

Chronic and intermittent abuse of one family member by another is common. Victims may be children who are sexually or physically abused, wives or live-in partners, or older relatives. Physicians are often the first points of contact for patients who have been abused, but the abuse is frequently concealed by the victims. Physicians should be alert to signs of battering such as bruises in various stages of healing, unusual behaviour in children and interpersonal difficulties in the family. There are a number of options in prevention and treatment, including referral to social service and legal authorities, calling on other resources in the family and helping the individual develop coping skills. This review also lists a large number of social agencies in Canada that are willing to help victims of abuse. PMID:3971273

A case study of the long-term retention of 137Cs after inhalation of high temperature reactor fuel element ash.

PubMed

Froning, M; Kozielewski, T; Schläger, M; Hill, P

2004-01-01

In 1987, a worker was internally contaminated with 137Cs as a result of an accident during the handling of high temperature reactor fuel element ash. In the long-term follow-up monitoring an unusual retention behaviour was found. The observed time dependence of caesium retention does not agree with the standard models of ICRP Publication 30. The present case can be better explained by assuming an intake of a mixture of type F and type S compounds. However, experimental data can be best described by a four-exponential retention function with two long-lived components, which was used as an ad hoc model for dose calculation. The resulting dose is compared with doses calculated on the basis of ICRP Publication 66.

Flare forecasting at the Met Office Space Weather Operations Centre

NASA Astrophysics Data System (ADS)

Murray, S. A.; Bingham, S.; Sharpe, M.; Jackson, D. R.

2017-04-01

The Met Office Space Weather Operations Centre produces 24/7/365 space weather guidance, alerts, and forecasts to a wide range of government and commercial end-users across the United Kingdom. Solar flare forecasts are one of its products, which are issued multiple times a day in two forms: forecasts for each active region on the solar disk over the next 24 h and full-disk forecasts for the next 4 days. Here the forecasting process is described in detail, as well as first verification of archived forecasts using methods commonly used in operational weather prediction. Real-time verification available for operational flare forecasting use is also described. The influence of human forecasters is highlighted, with human-edited forecasts outperforming original model results and forecasting skill decreasing over longer forecast lead times.

Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

NASA Astrophysics Data System (ADS)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be either an intermediate forecast between the extremes of the ensemble spread or a manually selected forecast based on a meteorologists advice. 2. Downstream catchments with low influence of weather forecast In downstream catchments with strong human impact on discharge (e.g. by reservoir operation) and large influence of upstream gauge observation quality on forecast quality, the 'overall error' may in most cases be larger than the combination of the 'model error' and an ensemble spread. Therefore, the overall forecast uncertainty bounds are calculated differently: a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. Here, additionally the corresponding inflow hydrograph from all upstream catchments must be used. b) As for an upstream catchment, the uncertainty range is determined by combination of 'model error' and the ensemble member forecasts c) In addition, the 'overall error' is superimposed on the 'lead forecast'. For reasons of consistency, the lead forecast must be based on the same meteorological forecast in the downstream and all upstream catchments. d) From the resulting two uncertainty ranges (one from the ensemble forecast and 'model error', one from the 'lead forecast' and 'overall error'), the envelope is taken as the most prudent uncertainty range. In sum, the uncertainty associated with each forecast run is calculated and communicated to the public in the form of 10% and 90% percentiles. As in part I of this study, the methodology as well as the useful- or uselessness of the resulting uncertainty ranges will be presented and discussed by typical examples.

The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

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

Finley, Cathy

2014-04-30

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements inmore » wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.« less

Renal cell carcinoma in children and young adults: analysis of clinicopathological, immunohistochemical and molecular characteristics with an emphasis on the spectrum of Xp11.2 translocation-associated and unusual clear cell subtypes.

PubMed

Wu, A; Kunju, L P; Cheng, L; Shah, R B

2008-11-01

Recent studies suggest that paediatric renal cell carcinoma (RCC) may represent a distinct group of tumours; however, its biological behaviour and classification remain poorly understood. The aim was to analyse 13 RCCs from patients < or =23 years of age to determine their clinicopathological, immunohistochemical and molecular characteristics. The histological spectrum included: Xp11.2 translocation-associated (6/13 patients, 46%), clear cell (5/13 patients, 38%), papillary (1/13 patients) and unclassified (1/13 patients) types. The Xp11.2 translocation-associated RCCs had a wide morphological spectrum, with high nuclear grade cells with abundant cytoplasm ranging from clear to granular and architecture ranging from solid to papillary. These tumours lacked cytokeratin expression and were confirmed by nuclear reactivity for TFE3 protein. Most of these translocation-associated tumours presented at high stage and had an unfavourable outcome. Three clear cell RCCs had unusual features that have not been previously characterized, including solid and cystic architecture, cells with abundant eosinophilic cytoplasm yet low nuclear grade and focal cytoplasmic inclusions, resembling oncocytoma. Deletion of subtelomeric 3p25 was observed in two of these RCCs. Xp11.2 translocation-associated RCC represents a predominant and aggressive subtype in the paediatric age group. Increased awareness of this subtype is important due to its heterogeneous morphology.

Stable isotope study of a new chondrichthyan fauna (Kimmeridgian, Porrentruy, Swiss Jura): an unusual freshwater-influenced isotopic composition for the hybodont shark Asteracanthus

NASA Astrophysics Data System (ADS)

Leuzinger, L.; Kocsis, L.; Billon-Bruyat, J.-P.; Spezzaferri, S.; Vennemann, T.

2015-12-01

Chondrichthyan teeth (sharks, rays, and chimaeras) are mineralized in isotopic equilibrium with the surrounding water, and parameters such as water temperature and salinity can be inferred from the oxygen isotopic composition (δ18Op) of their bioapatite. We analysed a new chondrichthyan assemblage, as well as teeth from bony fish (Pycnodontiformes). All specimens are from Kimmeridgian coastal marine deposits of the Swiss Jura (vicinity of Porrentruy, Ajoie district, NW Switzerland). While the overall faunal composition and the isotopic composition of bony fish are generally consistent with marine conditions, unusually low δ18Op values were measured for the hybodont shark Asteracanthus. These values are also lower compared to previously published data from older European Jurassic localities. Additional analyses on material from Solothurn (Kimmeridgian, NW Switzerland) also have comparable, low-18O isotopic compositions for Asteracanthus. The data are hence interpreted to represent a so far unique, freshwater-influenced isotopic composition for this shark that is classically considered a marine genus. While reproduction in freshwater or brackish realms is established for other hybodonts, a similar behaviour for Asteracanthus is proposed here. Regular excursions into lower salinity waters can be linked to the age of the deposits and correspond to an ecological adaptation, most likely driven by the Kimmeridgian transgression and by the competition of the hybodont shark Asteracanthus with the rapidly diversifying neoselachians (modern sharks).

Liquid crystal 'blue phases' with a wide temperature range.

PubMed

Coles, Harry J; Pivnenko, Mikhail N

2005-08-18

Liquid crystal 'blue phases' are highly fluid self-assembled three-dimensional cubic defect structures that exist over narrow temperature ranges in highly chiral liquid crystals. The characteristic period of these defects is of the order of the wavelength of visible light, and they give rise to vivid specular reflections that are controllable with external fields. Blue phases may be considered as examples of tuneable photonic crystals with many potential applications. The disadvantage of these materials, as predicted theoretically and proved experimentally, is that they have limited thermal stability: they exist over a small temperature range (0.5-2 degrees C) between isotropic and chiral nematic (N*) thermotropic phases, which limits their practical applicability. Here we report a generic family of liquid crystals that demonstrate an unusually broad body-centred cubic phase (BP I*) from 60 degrees C down to 16 degrees C. We prove this with optical texture analysis, selective reflection spectroscopy, Kössel diagrams and differential scanning calorimetry, and show, using a simple polarizer-free electro-optic cell, that the reflected colour is switched reversibly in applied electric fields over a wide colour range in typically 10 ms. We propose that the unusual behaviour of these blue phase materials is due to their dimeric molecular structure and their very high flexoelectric coefficients. This in turn sets out new theoretical challenges and potentially opens up new photonic applications.

Unusually high frequency natural VLF radio emissions observed during daytime in Northern Finland

NASA Astrophysics Data System (ADS)

Manninen, Jyrki; Turunen, Tauno; Kleimenova, Natalia; Rycroft, Michael; Gromova, Liudmila; Sirviö, Iina

2016-12-01

Geomagnetic field variations and electromagnetic waves of different frequencies are ever present in the Earth’s environment in which the Earth’s fauna and flora have evolved and live. These waves are a very useful tool for studying and exploring the physics of plasma processes occurring in the magnetosphere and ionosphere. Here we present ground-based observations of natural electromagnetic emissions of magnetospheric origin at very low frequency (VLF, 3-30 kHz), which are neither heard nor seen in their spectrograms because they are hidden by strong impulsive signals (sferics) originating in lightning discharges. After filtering out the sferics, peculiar emissions are revealed in these digital recordings, made in Northern Finland, at unusually high frequencies in the VLF band. These recently revealed emissions, which are observed for several hours almost every day in winter, contain short (˜1-3 min) burst-like structures at frequencies above 4-6 kHz, even up to 15 kHz; fine structure on the 1 s time scale is also prevalent. It seems that these whistler mode emissions are generated deep inside the magnetosphere, but the detailed nature, generation region and propagation behaviour of these newly discovered high latitude VLF emissions remain unknown; however, further research on them may shed new light on wave-particle interactions occurring in the Earth’s radiation belts.

Stable isotope study of a new chondrichthyan fauna (Kimmeridgian, Porrentruy, Swiss Jura): an unusual freshwater-influenced isotopic composition for the hybodont shark Asteracanthus

NASA Astrophysics Data System (ADS)

Leuzinger, L.; Kocsis, L.; Billon-Bruyat, J.-P.; Spezzaferri, S.; Vennemann, T.

2015-08-01

Chondrichthyan teeth (sharks, rays and chimaeras) are mineralised in isotopic equilibrium with the surrounding water, and parameters such as water temperature and salinity can be inferred from the oxygen isotopic composition (δ18Op) of their bioapatite. We analysed a new chondrichthyan assemblage, as well as teeth from bony fish (Pycnodontiformes). All specimens are from Kimmeridgian coastal marine deposits of the Swiss Jura (vicinity of Porrentruy, Ajoie district, NW Switzerland). While the overall faunal composition and the isotopic composition of bony fish are consistent with marine conditions, unusually low δ18Op values were measured for the hybodont shark Asteracanthus. These values are also lower compared to previously published data from older European Jurassic localities. Additional analyses on material from Solothurn (Kimmeridgian, NW Switzerland) also have comparable, low-18O isotopic compositions for Asteracanthus. The data are hence interpreted to represent a so far unique, freshwater-influenced isotopic composition for this shark that is classically considered as a marine genus. While reproduction in freshwater or brackish realms is established for other hybodonts, a similar behaviour for Asteracanthus is proposed here. Regular excursions into lower salinity waters can be linked to the age of the deposits and correspond to an ecological adaptation, most likely driven by the Kimmeridgian transgression and by the competition of the primitive shark Asteracanthus with the rapidly diversifying neoselachians (modern sharks).

The properties of electromagnetic responses and optical modulation in terahertz metamaterials

NASA Astrophysics Data System (ADS)

Chen, Wei; Shi, Yulei; Wang, Wei; Zhou, Qingli; Zhang, Cunlin

2016-11-01

Metamaterials with subwavelength structural features show unique electromagnetic responses that are unattainable with natural materials. Recently, the research on these artificial materials has been pushed forward to the terahertz (THz) region because of potential applications in biological fingerprinting, security imaging, and high frequency magnetic and electric resonant devices. Furthermore, active control of their properties could further facilitate and open up new applications in terms of modulation and switching. In our work, we will first present our studies of dipole arrays at terahertz frequencies. Then in experimental and theoretical studies of terahertz subwavelength L-shaped structure, we proposed an unusual-mode current resonance responsible for low-frequency characteristic dip in transmission spectra. Comparing spectral properties of our designed simplified structures with that of split-ring resonators, we attribute this unusual mode to the resonance coupling and splitting under the broken symmetry of the structure. Finally, we use optical pump-terahertz probe method to investigate the spectral and dynamic behaviour of optical modulation in the split-ring resonators. We have observed the blue-shift and band broadening in the spectral changes of transmission under optical excitation at different delay times. The calculated surface currents using finite difference time domain simulation are presented to characterize these resonances, and the blue-shift can be explained by the changed refractive index and conductivity in the photoexcited semiconductor substrate.

Medium-range reference evapotranspiration forecasts for the contiguous United States based on multi-model numerical weather predictions

NASA Astrophysics Data System (ADS)

Medina, Hanoi; Tian, Di; Srivastava, Puneet; Pelosi, Anna; Chirico, Giovanni B.

2018-07-01

Reference evapotranspiration (ET0) plays a fundamental role in agronomic, forestry, and water resources management. Estimating and forecasting ET0 have long been recognized as a major challenge for researchers and practitioners in these communities. This work explored the potential of multiple leading numerical weather predictions (NWPs) for estimating and forecasting summer ET0 at 101 U.S. Regional Climate Reference Network stations over nine climate regions across the contiguous United States (CONUS). Three leading global NWP model forecasts from THORPEX Interactive Grand Global Ensemble (TIGGE) dataset were used in this study, including the single model ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (EC), the National Centers for Environmental Prediction Global Forecast System (NCEP), and the United Kingdom Meteorological Office forecasts (MO), as well as multi-model ensemble forecasts from the combinations of these NWP models. A regression calibration was employed to bias correct the ET0 forecasts. Impact of individual forecast variables on ET0 forecasts were also evaluated. The results showed that the EC forecasts provided the least error and highest skill and reliability, followed by the MO and NCEP forecasts. The multi-model ensembles constructed from the combination of EC and MO forecasts provided slightly better performance than the single model EC forecasts. The regression process greatly improved ET0 forecast performances, particularly for the regions involving stations near the coast, or with a complex orography. The performance of EC forecasts was only slightly influenced by the size of the ensemble members, particularly at short lead times. Even with less ensemble members, EC still performed better than the other two NWPs. Errors in the radiation forecasts, followed by those in the wind, had the most detrimental effects on the ET0 forecast performances.

Uses and Applications of Climate Forecasts for Power Utilities.

NASA Astrophysics Data System (ADS)

Changnon, Stanley A.; Changnon, Joyce M.; Changnon, David

1995-05-01

The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-depth structured interviews were conducted with 56 decision makers in six utilities to assess existing and potential uses of climate forecasts. Only 3 of the 56 use forecasts. Eighty percent of those sampled envisioned applications of climate forecasts, given certain changes and additional information. Primary applications exist in power trading, load forecasting, fuel acquisition, and systems planning, with slight differences in interests between utilities. Utility staff understand probability-based forecasts but desire climatological information related to forecasted outcomes, including analogs similar to the forecasts, and explanations of the forecasts. Desired lead times vary from a week to three months, along with forecasts of up to four seasons ahead. The new NOAA forecasts initiated in 1995 provide the lead times and longer-term forecasts desired. Major hindrances to use of forecasts are hard-to-understand formats, lack of corporate acceptance, and lack of access to expertise. Recent changes in government regulations altered the utility industry, leading to a more competitive world wherein information about future weather conditions assumes much more value. Outreach efforts by government forecast agencies appear valuable to help achieve the appropriate and enhanced use of climate forecasts by the utility industry. An opportunity for service exists also for the private weather sector.

Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

2017-08-01

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

The Perfect Fire? Aging Stands in the Alaskan Boreal Forest Encounter Global Warming

NASA Astrophysics Data System (ADS)

Mann, D.; Rupp, S.; Duffy, P.

2008-12-01

The ecological responses of the boreal forest to climate change have global significance because of the large amount of carbon stored in its soils and biomass. Fire, mostly ignited by lightning, is the keystone disturbance agent in this forest. It triggers cycles of forest succession in its wake, and burning is the main avenue for carbon release back to the atmosphere. We studied the interactions between climate, fires, forest succession, and the age distributions of forest stands in a 60-million hectare region of Interior Alaska over the past 150 years. First we developed a statistical model relating climate to area burned over the period of record (1950-2005). Next we combined this model with climate reconstructions to extend the estimates of area burned back to A.D. 1860. We checked the resultant fire history against stand-age data from 5000 living trees sampled in the study region. Then we fed the history of area burned into a computer model that simulates forest succession on real landscapes. Results show striking changes in the means and variances of stand ages over the last 150 years in response to interactions between climate change and the successional dynamics of the boreal forest. Average stand age increased steadily between 1880 and 1940 and has fluctuated at high levels since then, indicating a historically unusual abundance of flammable stands. This accumulation of old stands has created the potential for unusually large fires. Some support for this conclusion comes from the unprecedented large sizes of the areas burned in 2004 and 2005. Further support comes when we add to the analysis the forecasts made by global climate models for Alaska over the next twenty years. Bracketing estimates for climate warming and precipitation change suggest that warmer, drier summers combined with aging forest stands will cause a series of unusually large fires, the like of which have not occurred in the region for >150 years. We infer that the enhanced burning of the Alaska boreal forest over the next 20 years will increase the release of trace gases from this region. We speculate that the forest will be transformed from being conifer dominated to one dominated by deciduous tree species, which could have sweeping effects on the region's other biota, its hydrology, and the role of the boreal forest in the global carbon cycle.

An overview of health forecasting.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D

2013-01-01

Health forecasting is a novel area of forecasting, and a valuable tool for predicting future health events or situations such as demands for health services and healthcare needs. It facilitates preventive medicine and health care intervention strategies, by pre-informing health service providers to take appropriate mitigating actions to minimize risks and manage demand. Health forecasting requires reliable data, information and appropriate analytical tools for the prediction of specific health conditions or situations. There is no single approach to health forecasting, and so various methods have often been adopted to forecast aggregate or specific health conditions. Meanwhile, there are no defined health forecasting horizons (time frames) to match the choices of health forecasting methods/approaches that are often applied. The key principles of health forecasting have not also been adequately described to guide the process. This paper provides a brief introduction and theoretical analysis of health forecasting. It describes the key issues that are important for health forecasting, including: definitions, principles of health forecasting, and the properties of health data, which influence the choices of health forecasting methods. Other matters related to the value of health forecasting, and the general challenges associated with developing and using health forecasting services are discussed. This overview is a stimulus for further discussions on standardizing health forecasting approaches and methods that will facilitate health care and health services delivery.

Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States.

PubMed

Yamana, Teresa K; Kandula, Sasikiran; Shaman, Jeffrey

2017-11-01

Recent research has produced a number of methods for forecasting seasonal influenza outbreaks. However, differences among the predicted outcomes of competing forecast methods can limit their use in decision-making. Here, we present a method for reconciling these differences using Bayesian model averaging. We generated retrospective forecasts of peak timing, peak incidence, and total incidence for seasonal influenza outbreaks in 48 states and 95 cities using 21 distinct forecast methods, and combined these individual forecasts to create weighted-average superensemble forecasts. We compared the relative performance of these individual and superensemble forecast methods by geographic location, timing of forecast, and influenza season. We find that, overall, the superensemble forecasts are more accurate than any individual forecast method and less prone to producing a poor forecast. Furthermore, we find that these advantages increase when the superensemble weights are stratified according to the characteristics of the forecast or geographic location. These findings indicate that different competing influenza prediction systems can be combined into a single more accurate forecast product for operational delivery in real time.

Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States

PubMed Central

Kandula, Sasikiran; Shaman, Jeffrey

2017-01-01

Recent research has produced a number of methods for forecasting seasonal influenza outbreaks. However, differences among the predicted outcomes of competing forecast methods can limit their use in decision-making. Here, we present a method for reconciling these differences using Bayesian model averaging. We generated retrospective forecasts of peak timing, peak incidence, and total incidence for seasonal influenza outbreaks in 48 states and 95 cities using 21 distinct forecast methods, and combined these individual forecasts to create weighted-average superensemble forecasts. We compared the relative performance of these individual and superensemble forecast methods by geographic location, timing of forecast, and influenza season. We find that, overall, the superensemble forecasts are more accurate than any individual forecast method and less prone to producing a poor forecast. Furthermore, we find that these advantages increase when the superensemble weights are stratified according to the characteristics of the forecast or geographic location. These findings indicate that different competing influenza prediction systems can be combined into a single more accurate forecast product for operational delivery in real time. PMID:29107987

Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts - A Hydrologic Model Output Statistics (HMOS) approach

NASA Astrophysics Data System (ADS)

Regonda, Satish Kumar; Seo, Dong-Jun; Lawrence, Bill; Brown, James D.; Demargne, Julie

2013-08-01

We present a statistical procedure for generating short-term ensemble streamflow forecasts from single-valued, or deterministic, streamflow forecasts produced operationally by the U.S. National Weather Service (NWS) River Forecast Centers (RFCs). The resulting ensemble streamflow forecast provides an estimate of the predictive uncertainty associated with the single-valued forecast to support risk-based decision making by the forecasters and by the users of the forecast products, such as emergency managers. Forced by single-valued quantitative precipitation and temperature forecasts (QPF, QTF), the single-valued streamflow forecasts are produced at a 6-h time step nominally out to 5 days into the future. The single-valued streamflow forecasts reflect various run-time modifications, or "manual data assimilation", applied by the human forecasters in an attempt to reduce error from various sources in the end-to-end forecast process. The proposed procedure generates ensemble traces of streamflow from a parsimonious approximation of the conditional multivariate probability distribution of future streamflow given the single-valued streamflow forecast, QPF, and the most recent streamflow observation. For parameter estimation and evaluation, we used a multiyear archive of the single-valued river stage forecast produced operationally by the NWS Arkansas-Red River Basin River Forecast Center (ABRFC) in Tulsa, Oklahoma. As a by-product of parameter estimation, the procedure provides a categorical assessment of the effective lead time of the operational hydrologic forecasts for different QPF and forecast flow conditions. To evaluate the procedure, we carried out hindcasting experiments in dependent and cross-validation modes. The results indicate that the short-term streamflow ensemble hindcasts generated from the procedure are generally reliable within the effective lead time of the single-valued forecasts and well capture the skill of the single-valued forecasts. For smaller basins, however, the effective lead time is significantly reduced by short basin memory and reduced skill in the single-valued QPF.

Public understanding of cyclone warning in India: Can wind be predicted?

PubMed

Dash, Biswanath

2015-11-01

In spite of meteorological warning, many human lives are lost every year to cyclone mainly because vulnerable populations were not evacuated on time to a safe shelter as per recommendation. It raises several questions, most prominently what explains people's behaviour in the face of such danger from a cyclonic storm? How do people view meteorological advisories issued for cyclone and what role they play in defining the threat? What shapes public response during such situation? This article based on an ethnographic study carried out in coastal state of Odisha, India, argues that local public recognising inherent limitations of meteorological warning, fall back on their own system of observation and forecasting. Not only are the contents of cyclone warning understood, its limitations are accommodated and explained. © The Author(s) 2014.

U.S. High Seas Marine Text Forecasts by Area

Science.gov Websites

Flooding Tsunamis 406 EPIRB's U.S. High Seas Marine Text Forecasts by Area OPC N.Atlantic High Seas Forecast NHC N.Atlantic High Seas Forecast OPC N.Pacific High Seas Forecast HFO N.Pacific High Seas Forecast NHC N.Pacific High Seas Forecast HFO S.Pacific High Seas Forecast U.S. High Seas Marine Text

A Diagnostics Tool to detect ensemble forecast system anomaly and guide operational decisions

NASA Astrophysics Data System (ADS)

Park, G. H.; Srivastava, A.; Shrestha, E.; Thiemann, M.; Day, G. N.; Draijer, S.

2017-12-01

The hydrologic community is moving toward using ensemble forecasts to take uncertainty into account during the decision-making process. The New York City Department of Environmental Protection (DEP) implements several types of ensemble forecasts in their decision-making process: ensemble products for a statistical model (Hirsch and enhanced Hirsch); the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) forecasts based on the classical Ensemble Streamflow Prediction (ESP) technique; and the new NWS Hydrologic Ensemble Forecasting Service (HEFS) forecasts. To remove structural error and apply the forecasts to additional forecast points, the DEP post processes both the AHPS and the HEFS forecasts. These ensemble forecasts provide mass quantities of complex data, and drawing conclusions from these forecasts is time-consuming and difficult. The complexity of these forecasts also makes it difficult to identify system failures resulting from poor data, missing forecasts, and server breakdowns. To address these issues, we developed a diagnostic tool that summarizes ensemble forecasts and provides additional information such as historical forecast statistics, forecast skill, and model forcing statistics. This additional information highlights the key information that enables operators to evaluate the forecast in real-time, dynamically interact with the data, and review additional statistics, if needed, to make better decisions. We used Bokeh, a Python interactive visualization library, and a multi-database management system to create this interactive tool. This tool compiles and stores data into HTML pages that allows operators to readily analyze the data with built-in user interaction features. This paper will present a brief description of the ensemble forecasts, forecast verification results, and the intended applications for the diagnostic tool.

Intermediate-term forecasting of aftershocks from an early aftershock sequence: Bayesian and ensemble forecasting approaches

NASA Astrophysics Data System (ADS)

Omi, Takahiro; Ogata, Yosihiko; Hirata, Yoshito; Aihara, Kazuyuki

2015-04-01

Because aftershock occurrences can cause significant seismic risks for a considerable time after the main shock, prospective forecasting of the intermediate-term aftershock activity as soon as possible is important. The epidemic-type aftershock sequence (ETAS) model with the maximum likelihood estimate effectively reproduces general aftershock activity including secondary or higher-order aftershocks and can be employed for the forecasting. However, because we cannot always expect the accurate parameter estimation from incomplete early aftershock data where many events are missing, such forecasting using only a single estimated parameter set (plug-in forecasting) can frequently perform poorly. Therefore, we here propose Bayesian forecasting that combines the forecasts by the ETAS model with various probable parameter sets given the data. By conducting forecasting tests of 1 month period aftershocks based on the first 1 day data after the main shock as an example of the early intermediate-term forecasting, we show that the Bayesian forecasting performs better than the plug-in forecasting on average in terms of the log-likelihood score. Furthermore, to improve forecasting of large aftershocks, we apply a nonparametric (NP) model using magnitude data during the learning period and compare its forecasting performance with that of the Gutenberg-Richter (G-R) formula. We show that the NP forecast performs better than the G-R formula in some cases but worse in other cases. Therefore, robust forecasting can be obtained by employing an ensemble forecast that combines the two complementary forecasts. Our proposed method is useful for a stable unbiased intermediate-term assessment of aftershock probabilities.

Quantifying model uncertainty in seasonal Arctic sea-ice forecasts

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, Edward; Barthélemy, Antoine; Chevallier, Matthieu; Cullather, Richard; Fučkar, Neven; Massonnet, François; Posey, Pamela; Wang, Wanqiu; Zhang, Jinlun; Ardilouze, Constantin; Bitz, Cecilia; Vernieres, Guillaume; Wallcraft, Alan; Wang, Muyin

2017-04-01

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or post-processing techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

Enhanced SAR data processing for land instability forecast.

NASA Astrophysics Data System (ADS)

Argentiero, Ilenia; Pellicani, Roberta; Spilotro, Giuseppe; Parisi, Alessandro; Bovenga, Fabio; Pasquariello, Guido; Refice, Alberto; Nutricato, Raffaele; Nitti, Davide Oscar; Chiaradia, Maria Teresa

2017-04-01

Monitoring represents the main tool for carrying out evaluation procedures and criteria for spatial and temporal landslide forecast. The forecast of landslide behaviour depends on the possibility to identify either evidences of activity (displacement, velocity, volume of unstable mass, direction of displacement, and their temporal variation) or triggering parameters (rainfalls). Generally, traditional geotechnical landslide monitoring technologies permit to define, if correctly positioned and with adequate accuracy, the critical value of displacement and/or acceleration into landslide body. In most cases, they do not allow real time warning signs to be generated, due to environmental induced errors, and the information is related to few points on unstable area. Remote-sensing monitoring instruments are capable of inspecting an unstable slope with high spatial and temporal frequency, but allow solely measurements of superficial displacements and deformations. Among these latest technologies, the satellite Persistent Scatterer SAR Interferometry (PSInSAR) is very useful to investigate the unstable area both in terms of space and time. Indeed, this technique allows to analyse wide areas, individuate critical unstable areas, not identifiable by means detailed in situ surveys, and study the phenomenon evolution in a long time-scale. Although this technique usually adopts, as first approximation, a linear model to describe the displacement of the detected targets, also non-linear models can be used. However, the satellite revisit time, which defines the time sampling of the detected displacement signal, limits the maximum measurable velocity and acceleration. This makes it difficult to assess in the short time any acceleration indicating a loss of equilibrium and, therefore, a probable reactivation of the landslide. The recent Sentinel-1 mission from the European Space Agency (ESA), provides a spatial resolution comparable to the previous ESA missions, but a nominal revisit time reduced to 6 days. By offering regular global-scale coverage, better temporal resolution and freely available imagery, Sentinel-1 improves the performance of PSInSAR for ground displacement investigations. In particular, the short revisit time allows a better time series analysis by improving the temporal sampling and the chances to catch pre-failure signals characterised by high rate and non-linear behaviour signals. Moreover, it allows collecting large data stacks in a short time period, thus improving the PSInSAR performance in emergency (post-event) scenarios. In the present work, we propose to match satellite data with numerical analysis techniques appropriate to evidence unsteady kinematics and, thanks to the high resolution of satellite data and improved temporal sampling, to detect early stages of land instability phenomena. The test area is situated in a small town in the Southern Apennine, Basilicata region, affected by old and new huge landslides, now close to a lived outskirt.

Model-free aftershock forecasts constructed from similar sequences in the past

NASA Astrophysics Data System (ADS)

van der Elst, N.; Page, M. T.

2017-12-01

The basic premise behind aftershock forecasting is that sequences in the future will be similar to those in the past. Forecast models typically use empirically tuned parametric distributions to approximate past sequences, and project those distributions into the future to make a forecast. While parametric models do a good job of describing average outcomes, they are not explicitly designed to capture the full range of variability between sequences, and can suffer from over-tuning of the parameters. In particular, parametric forecasts may produce a high rate of "surprises" - sequences that land outside the forecast range. Here we present a non-parametric forecast method that cuts out the parametric "middleman" between training data and forecast. The method is based on finding past sequences that are similar to the target sequence, and evaluating their outcomes. We quantify similarity as the Poisson probability that the observed event count in a past sequence reflects the same underlying intensity as the observed event count in the target sequence. Event counts are defined in terms of differential magnitude relative to the mainshock. The forecast is then constructed from the distribution of past sequences outcomes, weighted by their similarity. We compare the similarity forecast with the Reasenberg and Jones (RJ95) method, for a set of 2807 global aftershock sequences of M≥6 mainshocks. We implement a sequence-specific RJ95 forecast using a global average prior and Bayesian updating, but do not propagate epistemic uncertainty. The RJ95 forecast is somewhat more precise than the similarity forecast: 90% of observed sequences fall within a factor of two of the median RJ95 forecast value, whereas the fraction is 85% for the similarity forecast. However, the surprise rate is much higher for the RJ95 forecast; 10% of observed sequences fall in the upper 2.5% of the (Poissonian) forecast range. The surprise rate is less than 3% for the similarity forecast. The similarity forecast may be useful to emergency managers and non-specialists when confidence or expertise in parametric forecasting may be lacking. The method makes over-tuning impossible, and minimizes the rate of surprises. At the least, this forecast constitutes a useful benchmark for more precisely tuned parametric forecasts.

Imaging of near-Earth space plasma.

PubMed

Mitchell, Cathryn N

2002-12-15

This paper describes the technique of imaging the ionosphere using tomographic principles. It reports on current developments and speculates on the future of this research area. Recent developments in computing and ionospheric measurement, together with the sharing of data via the internet, now allow us to envisage a time when high-resolution, real-time images and 'movies' of the ionosphere will be possible for radio communications planning. There is great potential to use such images for improving our understanding of the physical processes controlling the behaviour of the ionosphere. While real-time images and movies of the electron concentration are now almost possible, forecasting of ionospheric morphology is still in its early stages. It has become clear that the ionosphere cannot be considered as a system in isolation, and consequently new research projects to link together models of the solar-terrestrial system, including the Sun, solar wind, magnetosphere, ionosphere and thermosphere, are now being proposed. The prospect is now on the horizon of assimilating data from the entire solar-terrestrial system to produce a real-time computer model and 'space weather' forecast. The role of tomography in imaging beyond the ionosphere to include the whole near-Earth space-plasma realm is yet to be realized, and provides a challenging prospect for the future. Finally, exciting possibilities exist in applying such methods to image the atmospheres and ionospheres of other planets.

Modeling aquifer behaviour under climate change and high consumption: Case study of the Sfax region, southeast Tunisia

NASA Astrophysics Data System (ADS)

Boughariou, Emna; Allouche, Nabila; Jmal, Ikram; Mokadem, Naziha; Ayed, Bachaer; Hajji, Soumaya; Khanfir, Hafedh; Bouri, Salem

2018-05-01

The water resources are exhausted by the increasing demand related to the population growth. They are also affected by climate circumstances, especially in arid and semi-arid regions. These areas are already undergoing noticeable shortages and low annual precipitation rate. This paper presents a numerical model of the Sfax shallow aquifer system that was developed by coupling the geographical information system tool ArcGIS 9.3 and ground water modeling system GMS6.5's interface, ground water flow modeling MODFLOW 2000. Being in coastal city and having an arid climate with high consumption rates, this aquifer is undergoing a hydraulic stress situation. Therefore, the groundwater piezometric variations were calibrated for the period 2003-2013 and simulated based on two scenarios; first the constant and growing consumption and second the rainfall forecast as a result of climate change scenario released by the Tunisian Ministry of Agriculture and Water Resources and the German International Cooperation Agency "GIZ" using HadCM3 as a general circulation model. The piezometric simulations globally forecast a decrease that is about 0.5 m in 2020 and 1 m in 2050 locally the decrease is more pronounced in "Chaffar" and "Djbeniana" regions and that is more evident for the increasing consumption scenario. The two scenarios announce a quantitative degradation of the groundwater by the year 2050 with an alarming marine intrusion in "Djbeniana" region.

Large-Eddy Simulations of Atmospheric Flows Over Complex Terrain Using the Immersed-Boundary Method in the Weather Research and Forecasting Model

NASA Astrophysics Data System (ADS)

Ma, Yulong; Liu, Heping

2017-12-01

Atmospheric flow over complex terrain, particularly recirculation flows, greatly influences wind-turbine siting, forest-fire behaviour, and trace-gas and pollutant dispersion. However, there is a large uncertainty in the simulation of flow over complex topography, which is attributable to the type of turbulence model, the subgrid-scale (SGS) turbulence parametrization, terrain-following coordinates, and numerical errors in finite-difference methods. Here, we upgrade the large-eddy simulation module within the Weather Research and Forecasting model by incorporating the immersed-boundary method into the module to improve simulations of the flow and recirculation over complex terrain. Simulations over the Bolund Hill indicate improved mean absolute speed-up errors with respect to previous studies, as well an improved simulation of the recirculation zone behind the escarpment of the hill. With regard to the SGS parametrization, the Lagrangian-averaged scale-dependent Smagorinsky model performs better than the classic Smagorinsky model in reproducing both velocity and turbulent kinetic energy. A finer grid resolution also improves the strength of the recirculation in flow simulations, with a higher horizontal grid resolution improving simulations just behind the escarpment, and a higher vertical grid resolution improving results on the lee side of the hill. Our modelling approach has broad applications for the simulation of atmospheric flows over complex topography.

A study for systematic errors of the GLA forecast model in tropical regions

NASA Technical Reports Server (NTRS)

Chen, Tsing-Chang; Baker, Wayman E.; Pfaendtner, James; Corrigan, Martin

1988-01-01

From the sensitivity studies performed with the Goddard Laboratory for Atmospheres (GLA) analysis/forecast system, it was revealed that the forecast errors in the tropics affect the ability to forecast midlatitude weather in some cases. Apparently, the forecast errors occurring in the tropics can propagate to midlatitudes. Therefore, the systematic error analysis of the GLA forecast system becomes a necessary step in improving the model's forecast performance. The major effort of this study is to examine the possible impact of the hydrological-cycle forecast error on dynamical fields in the GLA forecast system.

Multi-Year Revenue and Expenditure Forecasting for Small Municipal Governments.

DTIC Science & Technology

1981-03-01

Management Audit Econometric Revenue Forecast Gap and Impact Analysis Deterministic Expenditure Forecast Municipal Forecasting Municipal Budget Formlto...together with a multi-year revenue and expenditure forecasting model for the City of Monterey, California. The Monterey model includes an econometric ...65 5 D. FORECAST BASED ON THE ECONOMETRIC MODEL ------- 67 E. FORECAST BASED ON EXPERT JUDGMENT AND TREND ANALYSIS

Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

NASA Technical Reports Server (NTRS)

Wang, Yao; Sridhar, Banavar

2010-01-01

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

Tubulin perturbation leads to unexpected cell wall modifications and affects stomatal behaviour in Populus

DOE PAGES

Swamy, Prashant S.; Hu, Hao; Pattathil, Sivakumar; ...

2015-08-05

Cortical microtubules are integral to plant morphogenesis, cell wall synthesis, and stomatal behaviour, presumably by governing cellulose microfibril orientation. Genetic manipulation of tubulins often leads to abnormal plant development, making it difficult to probe additional roles of cortical microtubules in cell wall biogenesis. Here, it is shown that expressing post-translational C-terminal modification mimics of α-tubulin altered cell wall characteristics and guard cell dynamics in transgenic Populus tremula x alba that otherwise appear normal. 35S promoter-driven transgene expression was high in leaves but unusually low in xylem, suggesting high levels of tubulin transgene expression were not tolerated in wood-forming tissues duringmore » regeneration of transformants. Cellulose, hemicellulose, and lignin contents were unaffected in transgenic wood, but expression of cell wall-modifying enzymes, and extractability of lignin-bound pectin and xylan polysaccharides were increased in developing xylem. The results suggest that pectin and xylan polysaccharides deposited early during cell wall biogenesis are more sensitive to subtle tubulin perturbation than cellulose and matrix polysaccharides deposited later. Tubulin perturbation also affected guard cell behaviour, delaying drought-induced stomatal closure as well as light-induced stomatal opening in leaves. Pectins have been shown to confer cell wall flexibility critical for reversible stomatal movement, and results presented here are consistent with microtubule involvement in this process. In conclusion, taken together, the data show the value of growth-compatible tubulin perturbations for discerning microtubule functions, and add to the growing body of evidence for microtubule involvement in non-cellulosic polysaccharide assembly during cell wall biogenesis.« less

A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments

NASA Astrophysics Data System (ADS)

Schepen, Andrew; Zhao, Tongtiegang; Wang, Quan J.; Robertson, David E.

2018-03-01

Rainfall forecasts are an integral part of hydrological forecasting systems at sub-seasonal to seasonal timescales. In seasonal forecasting, global climate models (GCMs) are now the go-to source for rainfall forecasts. For hydrological applications however, GCM forecasts are often biased and unreliable in uncertainty spread, and calibration is therefore required before use. There are sophisticated statistical techniques for calibrating monthly and seasonal aggregations of the forecasts. However, calibration of seasonal forecasts at the daily time step typically uses very simple statistical methods or climate analogue methods. These methods generally lack the sophistication to achieve unbiased, reliable and coherent forecasts of daily amounts and seasonal accumulated totals. In this study, we propose and evaluate a Rainfall Post-Processing method for Seasonal forecasts (RPP-S), which is based on the Bayesian joint probability modelling approach for calibrating daily forecasts and the Schaake Shuffle for connecting the daily ensemble members of different lead times. We apply the method to post-process ACCESS-S forecasts for 12 perennial and ephemeral catchments across Australia and for 12 initialisation dates. RPP-S significantly reduces bias in raw forecasts and improves both skill and reliability. RPP-S forecasts are also more skilful and reliable than forecasts derived from ACCESS-S forecasts that have been post-processed using quantile mapping, especially for monthly and seasonal accumulations. Several opportunities to improve the robustness and skill of RPP-S are identified. The new RPP-S post-processed forecasts will be used in ensemble sub-seasonal to seasonal streamflow applications.

Bayesian analyses of seasonal runoff forecasts

NASA Astrophysics Data System (ADS)

Krzysztofowicz, R.; Reese, S.

1991-12-01

Forecasts of seasonal snowmelt runoff volume provide indispensable information for rational decision making by water project operators, irrigation district managers, and farmers in the western United States. Bayesian statistical models and communication frames have been researched in order to enhance the forecast information disseminated to the users, and to characterize forecast skill from the decision maker's point of view. Four products are presented: (i) a Bayesian Processor of Forecasts, which provides a statistical filter for calibrating the forecasts, and a procedure for estimating the posterior probability distribution of the seasonal runoff; (ii) the Bayesian Correlation Score, a new measure of forecast skill, which is related monotonically to the ex ante economic value of forecasts for decision making; (iii) a statistical predictor of monthly cumulative runoffs within the snowmelt season, conditional on the total seasonal runoff forecast; and (iv) a framing of the forecast message that conveys the uncertainty associated with the forecast estimates to the users. All analyses are illustrated with numerical examples of forecasts for six gauging stations from the period 1971 1988.

Heterogeneity: The key to forecasting material failure?

NASA Astrophysics Data System (ADS)

Vasseur, J.; Wadsworth, F. B.; Lavallée, Y.; Dingwell, D. B.

2014-12-01

Empirical mechanistic models have been applied to the description of the stress and strain rate upon failure for heterogeneous materials. The behaviour of porous rocks and their analogous two-phase viscoelastic suspensions are particularly well-described by such models. Nevertheless, failure cannot yet be predicted forcing a reliance on other empirical prediction tools such as the Failure Forecast Method (FFM). Measurable, accelerating rates of physical signals (e.g., seismicity and deformation) preceding failure are often used as proxies for damage accumulation in the FFM. Previous studies have already statistically assessed the applicability and performance of the FFM, but none (to the best of our knowledge) has done so in terms of intrinsic material properties. Here we use a rheological standard glass, which has been powdered and then sintered for different times (up to 32 hours) at high temperature (675°C) in order to achieve a sample suite with porosities in the range of 0.10-0.45 gas volume fraction. This sample suite was then subjected to mechanical tests in a uniaxial press at a constant strain rate of 10-3 s-1 and a temperature in the region of the glass transition. A dual acoustic emission (AE) rig has been employed to test the success of the FFM in these materials of systematically varying porosity. The pore-emanating crack model describes well the peak stress at failure in the elastic regime for these materials. We show that the FFM predicts failure within 0-15% error at porosities >0.2. However, when porosities are <0.2, the forecast error associated with predicting the failure time increases to >100%. We interpret these results as a function of the low efficiency with which strain energy can be released in the scenario where there are few or no heterogeneities from which cracks can propagate. These observations shed light on questions surrounding the variable efficacy of the FFM applied to active volcanoes. In particular, they provide a systematic demonstration of the fact that a good understanding of the material properties is required. Thus, we wish to emphasize the need for a better coupling of empirical failure forecasting models with mechanical parameters, such as failure criteria for heterogeneous materials, and point to the implications of this for a broad range of material-based disciplines.

A short-term ensemble wind speed forecasting system for wind power applications

NASA Astrophysics Data System (ADS)

Baidya Roy, S.; Traiteur, J. J.; Callicutt, D.; Smith, M.

2011-12-01

This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 hour ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather Research and Forecasting Single Column Model (WRFSCM) and a persistence model. The ensemble is calibrated against observations for a 2 month period (June-July, 2008) at a potential wind farm site in Illinois using the Bayesian Model Averaging (BMA) technique. The forecasting system is evaluated against observations for August 2008 at the same site. The calibrated ensemble forecasts significantly outperform the forecasts from the uncalibrated ensemble while significantly reducing forecast uncertainty under all environmental stability conditions. The system also generates significantly better forecasts than persistence, autoregressive (AR) and autoregressive moving average (ARMA) models during the morning transition and the diurnal convective regimes. This forecasting system is computationally more efficient than traditional numerical weather prediction models and can generate a calibrated forecast, including model runs and calibration, in approximately 1 minute. Currently, hour-ahead wind speed forecasts are almost exclusively produced using statistical models. However, numerical models have several distinct advantages over statistical models including the potential to provide turbulence forecasts. Hence, there is an urgent need to explore the role of numerical models in short-term wind speed forecasting. This work is a step in that direction and is likely to trigger a debate within the wind speed forecasting community.

Communicating uncertainty in hydrological forecasts: mission impossible?

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

2010-05-01

Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted scenarios, is essential. We believe that the efficient communication of uncertainty in hydro-meteorological forecasts is not a mission impossible. Questions remaining unanswered in probabilistic hydrological forecasting should not neutralize the goal of such a mission, and the suspense kept should instead act as a catalyst for overcoming the remaining challenges.

Bayesian flood forecasting methods: A review

NASA Astrophysics Data System (ADS)

Han, Shasha; Coulibaly, Paulin

2017-08-01

Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been developed and widely applied, but there is still room for improvements. Future research in the context of Bayesian flood forecasting should be on assimilation of various sources of newly available information and improvement of predictive performance assessment methods.

Verification of Space Weather Forecasts using Terrestrial Weather Approaches

NASA Astrophysics Data System (ADS)

Henley, E.; Murray, S.; Pope, E.; Stephenson, D.; Sharpe, M.; Bingham, S.; Jackson, D.

2015-12-01

The Met Office Space Weather Operations Centre (MOSWOC) provides a range of 24/7 operational space weather forecasts, alerts, and warnings, which provide valuable information on space weather that can degrade electricity grids, radio communications, and satellite electronics. Forecasts issued include arrival times of coronal mass ejections (CMEs), and probabilistic forecasts for flares, geomagnetic storm indices, and energetic particle fluxes and fluences. These forecasts are produced twice daily using a combination of output from models such as Enlil, near-real-time observations, and forecaster experience. Verification of forecasts is crucial for users, researchers, and forecasters to understand the strengths and limitations of forecasters, and to assess forecaster added value. To this end, the Met Office (in collaboration with Exeter University) has been adapting verification techniques from terrestrial weather, and has been working closely with the International Space Environment Service (ISES) to standardise verification procedures. We will present the results of part of this work, analysing forecast and observed CME arrival times, assessing skill using 2x2 contingency tables. These MOSWOC forecasts can be objectively compared to those produced by the NASA Community Coordinated Modelling Center - a useful benchmark. This approach cannot be taken for the other forecasts, as they are probabilistic and categorical (e.g., geomagnetic storm forecasts give probabilities of exceeding levels from minor to extreme). We will present appropriate verification techniques being developed to address these forecasts, such as rank probability skill score, and comparing forecasts against climatology and persistence benchmarks. As part of this, we will outline the use of discrete time Markov chains to assess and improve the performance of our geomagnetic storm forecasts. We will also discuss work to adapt a terrestrial verification visualisation system to space weather, to help MOSWOC forecasters view verification results in near real-time; plans to objectively assess flare forecasts under the EU Horizon 2020 FLARECAST project; and summarise ISES efforts to achieve consensus on verification.

A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

NASA Astrophysics Data System (ADS)

Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

2017-04-01

Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of the forecasting chain (i.e., IHC or MF) could potentially lead to the highest increase in seasonal hydrological forecasting performance, after each forecast update.

The confounding recent behaviour of the Quasi-Biennial Oscillation

NASA Astrophysics Data System (ADS)

Osprey, Scott; Butchart, Neal; Knight, Jeff; Scaife, Adam; Hamilton, Kevin; Anstey, James; Schenzinger, Verena; Zhang, Chunxi

2017-04-01

High above the equator winds slowly change from blowing eastward to westward and back again roughly every 28 months in a natural climate rhythm known as the quasibiennial oscillation (QBO). These regular winds have been recorded since the 1950s and emerge from natural processes within the tropics e.g. clouds, convection, rainfall and the wave disturbances arising from these. The latter break down high up in the stratosphere, analogous to waves on a beach. Although a little tricky to capture in climate models, our understanding of the basic processes underpinning this climate rhythm was thought to be relatively complete. However, early in 2016 the stratospheric heart skipped a beat, confounding our present understanding of it. The disruption was seen as a thin and rapidly growing westward wind jet at 25km within a deep background of eastward winds. The position of the thin jet could not be explained by waves percolating up through underlying winds from the turbulent lower atmosphere. Rather clues to the origin of the disruption pointed to agents outside the tropics - large scale waves usually found at mid-latitudes made their way to the tropics, causing the disruption. Clear links are found between the winds occurring in the tropical stratosphere and the sorts of seasonal weather experienced in the tropics (e.g. MJO) and Northern/Southern Europe. Because these tropical stratosphere winds are predictable out to years, weather centres are keen to exploit them for seasonal forecasting. The 2016 disruption was not anticipated by weather centres and this has clear implications for the limiting skill of future seasonal forecasts. The results from this study raise many questions. How will the disrupted QBO impact future seasonal forecasting? Will similar events recur more often in the future, and if so what role did anthropogenic climate change play in the 2016 event? Finally, what conditions ultimately resulted in the disruption? Osprey, S. M. et al. An unexpected disruption of the atmospheric quasi-biennial oscillation. Science. 353, 1424-1427 (2016).

An online mineral dust model within the global/regional NMMB: current progress and plans

NASA Astrophysics Data System (ADS)

Perez, C.; Haustein, K.; Janjic, Z.; Jorba, O.; Baldasano, J. M.; Black, T.; Nickovic, S.

2008-12-01

While mineral dust distribution and effects are important on global scales, they strongly depend on dust emissions that are occurring on small spatial and temporal scales. Indeed, the accuracy of surface wind speed used in dust models is crucial. Due to the high-order power dependency on wind friction velocity and the threshold behaviour of dust emissions, small errors in surface wind speed lead to large dust emission errors. Most global dust models use prescribed wind fields provided by major meteorological centres (e.g., NCEP and ECMWF) and their spatial resolution is currently about 1 degree x 1 degree . Such wind speeds tend to be strongly underestimated over arid and semi-arid areas and do not account for mesoscale systems responsible for a significant fraction of dust emissions regionally and globally. Other significant uncertainties in dust emissions resulting from such approaches are related to the misrepresentation of high subgrid-scale spatial heterogeneity in soil and vegetation boundary conditions, mainly in semi-arid areas. In order to significantly reduce these uncertainties, the Barcelona Supercomputing Center is currently implementing a mineral dust model coupled on-line with the new global/regional NMMB atmospheric model using the ESMF framework under development in NOAA/NCEP/EMC. The NMMB is an evolution of the operational WRF-NMME extending from meso to global scales, and including non-hydrostatic option and improved tracer advection. This model is planned to become the next-generation NCEP mesoscale model for operational weather forecasting in North America. Current implementation is based on the well established regional dust model and forecast system Eta/DREAM (http://www.bsc.es/projects/earthscience/DREAM/). First successful global simulations show the potentials of such an approach and compare well with DREAM regionally. Ongoing developments include improvements in dust size distribution representation, sedimentation, dry deposition, wet scavenging and dust-radiation feedback, as well as the efficient implementation of the model on High Performance Supercomputers for global simulations and forecasts at high resolution.

Forecasting Consumer Adoption of Information Technology and Services--Lessons from Home Video Forecasting.

ERIC Educational Resources Information Center

Klopfenstein, Bruce C.

1989-01-01

Describes research that examined the strengths and weaknesses of technological forecasting methods by analyzing forecasting studies made for home video players. The discussion covers assessments and explications of correct and incorrect forecasting assumptions, and their implications for forecasting the adoption of home information technologies…

Uncertainties in Forecasting Streamflow using Entropy Theory

NASA Astrophysics Data System (ADS)

Cui, H.; Singh, V. P.

2017-12-01

Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

A national-scale seasonal hydrological forecast system: development and evaluation over Britain

NASA Astrophysics Data System (ADS)

Bell, Victoria A.; Davies, Helen N.; Kay, Alison L.; Brookshaw, Anca; Scaife, Adam A.

2017-09-01

Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better) rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (hindcasts) from the GloSea5 model (1996 to 2009) are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean) rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region). Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 %) in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows), whereas for the 3-month ahead lead time, GloSea5 forecasts account for ˜ 70 % of the forecast skill (mostly in areas of high rainfall to the north and west) and only 30 % of the skill arises from hydrological memory (typically groundwater-dominated areas). Given the high spatial heterogeneity in typical patterns of UK rainfall and evaporation, future development of skilful spatially distributed seasonal forecasts could lead to substantial improvements in seasonal flow forecast capability, potentially benefitting practitioners interested in predicting hydrological extremes, not only in the UK but also across Europe.

Improving medium-range and seasonal hydroclimate forecasts in the southeast USA

NASA Astrophysics Data System (ADS)

Tian, Di

Accurate hydro-climate forecasts are important for decision making by water managers, agricultural producers, and other stake holders. Numerical weather prediction models and general circulation models may have potential for improving hydro-climate forecasts at different scales. In this study, forecast analogs of the Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) based on different approaches were evaluated for medium-range reference evapotranspiration (ETo), irrigation scheduling, and urban water demand forecasts in the southeast United States; the Climate Forecast System version 2 (CFSv2) and the North American national multi-model ensemble (NMME) were statistically downscaled for seasonal forecasts of ETo, precipitation (P) and 2-m temperature (T2M) at the regional level. The GFS mean temperature (Tmean), relative humidity, and wind speed (Wind) reforecasts combined with the climatology of Reanalysis 2 solar radiation (Rs) produced higher skill than using the direct GFS output only. Constructed analogs showed slightly higher skill than natural analogs for deterministic forecasts. Both irrigation scheduling driven by the GEFS-based ETo forecasts and GEFS-based ETo forecast skill were generally positive up to one week throughout the year. The GEFS improved ETo forecast skill compared to the GFS. The GEFS-based analog forecasts for the input variables of an operational urban water demand model were skillful when applied in the Tampa Bay area. The modified operational models driven by GEFS analog forecasts showed higher forecast skill than the operational model based on persistence. The results for CFSv2 seasonal forecasts showed maximum temperature (Tmax) and Rs had the greatest influence on ETo. The downscaled Tmax showed the highest predictability, followed by Tmean, Tmin, Rs, and Wind. The CFSv2 model could better predict ETo in cold seasons during El Nino Southern Oscillation (ENSO) events only when the forecast initial condition was in ENSO. Downscaled P and T2M forecasts were produced by directly downscaling the NMME P and T2M output or indirectly using the NMME forecasts of Nino3.4 sea surface temperatures to predict local-scale P and T2M. The indirect method generally showed the highest forecast skill which occurs in cold seasons. The bias-corrected NMME ensemble forecast skill did not outperform the best single model.

Current status of validating operational model forecasts at the DWD site Lindenberg

NASA Astrophysics Data System (ADS)

Beyrich, F.; Heret, C.; Vogel, G.

2009-09-01

Based on long experience in the measurement of atmospheric boundary layer parameters, the Meteorological Observatory Lindenberg / Richard - Aßmann-Observatory is well qualified to validate operational NWP results for this location. The validation activities cover a large range of time periods from single days or months up to several years and include much more quantities than generally used in areal verification techniques. They mainly focus on land surface and boundary layer processes which play an important role in the atmospheric forc-ing from the surface. Versatility and continuity of the database enable a comprehensive evaluation of the model behaviour under different meteorological conditions in order to esti-mate the accuracy of the physical parameterisations and to detect possible deficiencies in the predicted processes. The measurements from the boundary layer field site Falkenberg serve as reference data for various types of validation studies: 1. The operational boundary-layer measurements are used to identify and to document weather situations with large forecast errors which can then be analysed in more de-tail. Results from a case study will be presented where model deficiencies in the cor-rect simulation of the diurnal evolution of near-surface temperature under winter con-ditions over a closed snow cover where diagnosed. 2. Due to the synopsis of the boundary layer quantities based on monthly averaged di-urnal cycles systematic model deficiencies can be detected more clearly. Some dis-tinctive features found in the annual cycle (e.g. near-surface temperatures, turbulent heat fluxes and soil moisture) will be outlined. Further aspects are their different ap-pearance in the COSMO-EU and COSMO-DE models as well as the effects of start-ing time (00 or 12 UTC) on the prediction accuracy. 3. The evaluation of the model behaviour over several years provides additional insight into the impact of changes in the physical parameterisations, data assimilation or nu-merics on the meteorological quantities. The temporal development of the error char-acteristics of some near-surface weather parameters (temperature, dewpoint tem-perature, wind velocity) and of the energy fluxes at the surface will be discussed.

Modeled Forecasts of Dengue Fever in San Juan, Puerto Rico Using NASA Satellite Enhanced Weather Forecasts

NASA Astrophysics Data System (ADS)

Morin, C.; Quattrochi, D. A.; Zavodsky, B.; Case, J.

2015-12-01

Dengue fever (DF) is an important mosquito transmitted disease that is strongly influenced by meteorological and environmental conditions. Recent research has focused on forecasting DF case numbers based on meteorological data. However, these forecasting tools have generally relied on empirical models that require long DF time series to train. Additionally, their accuracy has been tested retrospectively, using past meteorological data. Consequently, the operational utility of the forecasts are still in question because the error associated with weather and climate forecasts are not reflected in the results. Using up-to-date weekly dengue case numbers for model parameterization and weather forecast data as meteorological input, we produced weekly forecasts of DF cases in San Juan, Puerto Rico. Each week, the past weeks' case counts were used to re-parameterize a process-based DF model driven with updated weather forecast data to generate forecasts of DF case numbers. Real-time weather forecast data was produced using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) system enhanced using additional high-resolution NASA satellite data. This methodology was conducted in a weekly iterative process with each DF forecast being evaluated using county-level DF cases reported by the Puerto Rico Department of Health. The one week DF forecasts were accurate especially considering the two sources of model error. First, weather forecasts were sometimes inaccurate and generally produced lower than observed temperatures. Second, the DF model was often overly influenced by the previous weeks DF case numbers, though this phenomenon could be lessened by increasing the number of simulations included in the forecast. Although these results are promising, we would like to develop a methodology to produce longer range forecasts so that public health workers can better prepare for dengue epidemics.

The potential of radar-based ensemble forecasts for flash-flood early warning in the southern Swiss Alps

NASA Astrophysics Data System (ADS)

Liechti, K.; Panziera, L.; Germann, U.; Zappa, M.

2013-10-01

This study explores the limits of radar-based forecasting for hydrological runoff prediction. Two novel radar-based ensemble forecasting chains for flash-flood early warning are investigated in three catchments in the southern Swiss Alps and set in relation to deterministic discharge forecasts for the same catchments. The first radar-based ensemble forecasting chain is driven by NORA (Nowcasting of Orographic Rainfall by means of Analogues), an analogue-based heuristic nowcasting system to predict orographic rainfall for the following eight hours. The second ensemble forecasting system evaluated is REAL-C2, where the numerical weather prediction COSMO-2 is initialised with 25 different initial conditions derived from a four-day nowcast with the radar ensemble REAL. Additionally, three deterministic forecasting chains were analysed. The performance of these five flash-flood forecasting systems was analysed for 1389 h between June 2007 and December 2010 for which NORA forecasts were issued, due to the presence of orographic forcing. A clear preference was found for the ensemble approach. Discharge forecasts perform better when forced by NORA and REAL-C2 rather then by deterministic weather radar data. Moreover, it was observed that using an ensemble of initial conditions at the forecast initialisation, as in REAL-C2, significantly improved the forecast skill. These forecasts also perform better then forecasts forced by ensemble rainfall forecasts (NORA) initialised form a single initial condition of the hydrological model. Thus the best results were obtained with the REAL-C2 forecasting chain. However, for regions where REAL cannot be produced, NORA might be an option for forecasting events triggered by orographic precipitation.

Evaluation of Flood Forecast and Warning in Elbe river basin - Impact of Forecaster's Strategy

NASA Astrophysics Data System (ADS)

Danhelka, Jan; Vlasak, Tomas

2010-05-01

Czech Hydrometeorological Institute (CHMI) is responsible for flood forecasting and warning in the Czech Republic. To meet that issue CHMI operates hydrological forecasting systems and publish flow forecast in selected profiles. Flood forecast and warning is an output of system that links observation (flow and atmosphere), data processing, weather forecast (especially NWP's QPF), hydrological modeling and modeled outputs evaluation and interpretation by forecaster. Forecast users are interested in final output without separating uncertainties of separate steps of described process. Therefore an evaluation of final operational forecasts was done for profiles within Elbe river basin produced by AquaLog forecasting system during period 2002 to 2008. Effects of uncertainties of observation, data processing and especially meteorological forecasts were not accounted separately. Forecast of flood levels exceedance (peak over the threshold) during forecasting period was the main criterion as flow increase forecast is of the highest importance. Other evaluation criteria included peak flow and volume difference. In addition Nash-Sutcliffe was computed separately for each time step (1 to 48 h) of forecasting period to identify its change with the lead time. Textual flood warnings are issued for administrative regions to initiate flood protection actions in danger of flood. Flood warning hit rate was evaluated at regions level and national level. Evaluation found significant differences of model forecast skill between forecasting profiles, particularly less skill was evaluated at small headwater basins due to domination of QPF uncertainty in these basins. The average hit rate was 0.34 (miss rate = 0.33, false alarm rate = 0.32). However its explored spatial difference is likely to be influenced also by different fit of parameters sets (due to different basin characteristics) and importantly by different impact of human factor. Results suggest that the practice of interactive model operation, experience and forecasting strategy differs between responsible forecasting offices. Warning is based on model outputs interpretation by hydrologists-forecaster. Warning hit rate reached 0.60 for threshold set to lowest flood stage of which 0.11 was underestimation of flood degree (miss 0.22, false alarm 0.28). Critical success index of model forecast was 0.34, while the same criteria for warning reached 0.55. We assume that the increase accounts not only to change of scale from single forecasting point to region for warning, but partly also to forecaster's added value. There is no official warning strategy preferred in the Czech Republic (f.e. tolerance towards higher false alarm rate). Therefore forecaster decision and personal strategy is of great importance. Results show quite successful warning for 1st flood level exceedance, over-warning for 2nd flood level, but under-warning for 3rd (highest) flood level. That suggests general forecaster's preference of medium level warning (2nd flood level is legally determined to be the start of the flood and flood protection activities). In conclusion human forecaster's experience and analysis skill increases flood warning performance notably. However society preference should be specifically addressed in the warning strategy definition to support forecaster's decision making.

An Optimization of Inventory Demand Forecasting in University Healthcare Centre

NASA Astrophysics Data System (ADS)

Bon, A. T.; Ng, T. K.

2017-01-01

Healthcare industry becomes an important field for human beings nowadays as it concerns about one’s health. With that, forecasting demand for health services is an important step in managerial decision making for all healthcare organizations. Hence, a case study was conducted in University Health Centre to collect historical demand data of Panadol 650mg for 68 months from January 2009 until August 2014. The aim of the research is to optimize the overall inventory demand through forecasting techniques. Quantitative forecasting or time series forecasting model was used in the case study to forecast future data as a function of past data. Furthermore, the data pattern needs to be identified first before applying the forecasting techniques. Trend is the data pattern and then ten forecasting techniques are applied using Risk Simulator Software. Lastly, the best forecasting techniques will be find out with the least forecasting error. Among the ten forecasting techniques include single moving average, single exponential smoothing, double moving average, double exponential smoothing, regression, Holt-Winter’s additive, Seasonal additive, Holt-Winter’s multiplicative, seasonal multiplicative and Autoregressive Integrated Moving Average (ARIMA). According to the forecasting accuracy measurement, the best forecasting technique is regression analysis.

Air Pollution Forecasts: An Overview

PubMed Central

Bai, Lu; Wang, Jianzhou; Lu, Haiyan

2018-01-01

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

Air Pollution Forecasts: An Overview.

PubMed

Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

2018-04-17

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

Analog-Based Postprocessing of Navigation-Related Hydrological Ensemble Forecasts

NASA Astrophysics Data System (ADS)

Hemri, S.; Klein, B.

2017-11-01

Inland waterway transport benefits from probabilistic forecasts of water levels as they allow to optimize the ship load and, hence, to minimize the transport costs. Probabilistic state-of-the-art hydrologic ensemble forecasts inherit biases and dispersion errors from the atmospheric ensemble forecasts they are driven with. The use of statistical postprocessing techniques like ensemble model output statistics (EMOS) allows for a reduction of these systematic errors by fitting a statistical model based on training data. In this study, training periods for EMOS are selected based on forecast analogs, i.e., historical forecasts that are similar to the forecast to be verified. Due to the strong autocorrelation of water levels, forecast analogs have to be selected based on entire forecast hydrographs in order to guarantee similar hydrograph shapes. Custom-tailored measures of similarity for forecast hydrographs comprise hydrological series distance (SD), the hydrological matching algorithm (HMA), and dynamic time warping (DTW). Verification against observations reveals that EMOS forecasts for water level at three gauges along the river Rhine with training periods selected based on SD, HMA, and DTW compare favorably with reference EMOS forecasts, which are based on either seasonal training periods or on training periods obtained by dividing the hydrological forecast trajectories into runoff regimes.

Forecasting, Forecasting

Treesearch

Michael A. Fosberg

1987-01-01

Future improvements in the meteorological forecasts used in fire management will come from improvements in three areas: observational systems, forecast techniques, and postprocessing of forecasts and better integration of this information into the fire management process.

Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model

PubMed Central

Zhang, Jinlun

2015-01-01

Abstract Arctic sea ice drift forecasts of 6 h–9 days for the summer of 2014 are generated using the Marginal Ice Zone Modeling and Assimilation System (MIZMAS); the model is driven by 6 h atmospheric forecasts from the Climate Forecast System (CFSv2). Forecast ice drift speed is compared to drifting buoys and other observational platforms. Forecast positions are compared with actual positions 24 h–8 days since forecast. Forecast results are further compared to those from the forecasts generated using an ice velocity climatology driven by multiyear integrations of the same model. The results are presented in the context of scheduling the acquisition of high‐resolution images that need to follow buoys or scientific research platforms. RMS errors for ice speed are on the order of 5 km/d for 24–48 h since forecast using the sea ice model compared with 9 km/d using climatology. Predicted buoy position RMS errors are 6.3 km for 24 h and 14 km for 72 h since forecast. Model biases in ice speed and direction can be reduced by adjusting the air drag coefficient and water turning angle, but the adjustments do not affect verification statistics. This suggests that improved atmospheric forecast forcing may further reduce the forecast errors. The model remains skillful for 8 days. Using the forecast model increases the probability of tracking a target drifting in sea ice with a 10 km × 10 km image from 60 to 95% for a 24 h forecast and from 27 to 73% for a 48 h forecast. PMID:27818852

Two-step forecast of geomagnetic storm using coronal mass ejection and solar wind condition

PubMed Central

Kim, R-S; Moon, Y-J; Gopalswamy, N; Park, Y-D; Kim, Y-H

2014-01-01

To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (Bz ≤ −5 nT or Ey ≥ 3 mV/m for t≥ 2 h for moderate storms with minimum Dst less than −50 nT) and a Dst model developed by Temerin and Li (2002, 2006) (TL model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90%) than the forecasts based on the TL model (87%). However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80%) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (∩), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81%) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (∪), all geomagnetic storms are correctly forecasted. PMID:26213515

Two-step forecast of geomagnetic storm using coronal mass ejection and solar wind condition.

PubMed

Kim, R-S; Moon, Y-J; Gopalswamy, N; Park, Y-D; Kim, Y-H

2014-04-01

To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study ( B z  ≤ -5 nT or E y  ≥ 3 mV/m for t ≥ 2 h for moderate storms with minimum Dst less than -50 nT) and a Dst model developed by Temerin and Li (2002, 2006) (TL model). Using 55 CME- Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90%) than the forecasts based on the TL model (87%). However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80%) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (∩), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81%) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (∪), all geomagnetic storms are correctly forecasted.

Acoustic attenuation due to transformation twins in CaCl2: Analogue behaviour for stishovite

NASA Astrophysics Data System (ADS)

Zhang, Zhiying; Schranz, Wilfried; Carpenter, Michael A.

2012-09-01

CaCl2 undergoes a tetragonal (P42/mnm) to orthorhombic (Pnnm) transition as a function of temperature which is essentially the same as occurs in stishovite at high pressures. It can therefore be used as a convenient analogue material for experimental studies. In order to investigate variations in elastic properties associated with the transition and possible anelastic loss behaviour related to the mobility of ferroelastic twin walls in the orthorhombic phase, the transition in polycrystalline CaCl2 has been examined using resonant ultrasound spectroscopy (RUS) at high frequencies (0.1-1.5 MHz) in the temperature interval 7-626 K, and dynamic mechanical analysis (DMA) at low frequencies (0.1-50 Hz) in the temperature interval 378-771 K. RUS data show steep softening of the shear modulus as the transition temperature is approached from above and substantial acoustic dissipation in the stability field of the orthorhombic structure. DMA data show softening of the storage modulus, which continues through to a minimum ˜20 K below the transition point and is followed by stiffening with further lowering of temperature. There is no obvious acoustic dissipation associated with the transition, as measured by tan δ, however. The elastic softening and stiffening matches the pattern expected for a pseudoproper ferroelastic transition as predicted elsewhere. Acoustic loss behaviour at high frequencies fits with the pattern of behaviour expected for a twin wall loss mechanism but with relaxation times in the vicinity of ˜10-6 s. With such short relaxation times, the shear modulus of CaCl2 at frequencies corresponding to seismic frequencies would include relaxations of the twin walls and is therefore likely to be significantly lower than the intrinsic shear modulus. If these characteristics apply also to twin wall mobility in stishovite, the seismic signature of the orthorhombic phase should be an unusually soft shear modulus but with no increase in attenuation.

Go big or die out: Bifurcation and bimodality in submarine sediment flow behaviour

NASA Astrophysics Data System (ADS)

Talling, P.; Paull, C. K.; Lintern, G.; Gwiazda, R.; Cartigny, M.; Hughes Clarke, J. E.; Xu, J.; Clare, M. A.; Parsons, D. R.; Simmons, S.; Maier, K. L.; Gales, J. A.; Hage, S.; McGann, M.; Pope, E.; Rosenberger, K. J.; Stacey, C.; Barry, J.; Lundsten, E. M.; Anderson, K.; O'Reilly, T. C.; Chapplow, N.; Vendettuoli, D.

2017-12-01

Submarine flows of sediment (turbidity currents) flush globally significant volumes of sediment and organic carbon into deep-sea basins. These flows create the largest sediment accumulations on Earth, which hold valuable oil and gas reserves. These flows affect global carbon burial, how deep-sea ecosystems function, and pose a hazard to offshore infrastructure. Only river systems transport such large amounts of sediment across such long distances. However, there are remarkably few direct measurements from active submarine flows, which is a stark contrast to >1 million direct observations from rivers. Here we present unusually detailed information on frequency, power and runout distance of multiple submarine flows at two contrasting locations. The first data set comes from Monterey Canyon, offshore California, which is fed by littoral cells. The second site is a river-fed delta in Bute Inlet, British Columbia. In both cases, the timing and runout distance of submarine flows was documented using instruments on multiple moorings placed along the 50-km long flow pathway. A striking observation is that flow behaviour and runout is strongly bimodal in both locations. Flows tend to either dissipate rapidly, or runout through the entire mooring arrays. We thus test whether i) the character of short or long runout flows can be distinguished at the first mooring and ii) whether long and short runout flows have different triggers. It has been proposed that submarine flows have two modes of behaviour; either eroding and accelerating, or depositing and dissipating. These field data support such a view of bifurcation and bimodality in flow behaviour. However, some short runout flows resemble their longer runout cousins at the first mooring, and there is no clear relationship between flow trigger and runout. Thus, some flows reach a point where their character is no longer dependent on their initial trigger or initial structure, but on factors acting along the flow pathway.

Uranium-Series Isotopic Constraints on Recent Changes in the Eruptive Behaviour of Merapi Volcano, Java, Indonesia

NASA Astrophysics Data System (ADS)

Gertisser, R.; Handley, H. K.; Reagan, M. K.; Berlo, K.; Barclay, J.; Preece, K.; Herd, R.

2011-12-01

Merapi volcano (Central Java) is one of the most active and deadly volcanoes in Indonesia. The 2010 eruption was the volcano's largest eruption since 1872 and erupted much more violently than expected. Prior to 2010, volcanic activity at Merapi was characterised by several months of slow dome growth punctuated by gravitational dome failures, generating small-volume pyroclastic density currents (Merapi-type nuées ardentes). The unforeseen, large-magnitude events in 2010 were different in many respects: pyroclastic density currents travelled > 15 km beyond the summit causing widespread devastation in proximal areas on Merapi's south flank and ash emissions from sustained eruption columns resulted in ash fall tens of kilometres away from the volcano. The 2010 events have proved that Merapi's relatively small dome-forming activity can be interrupted at relatively short notice by larger explosive eruptions, which appear more common in the geological record. We present new geochemical and Uranium-series isotope data for the volcanic products of both the 2006 and 2010 eruptions at Merapi to investigate the driving forces behind this unusual explosive behaviour and their timescales. An improved knowledge of these processes and of changes in the pre-eruptive magma system has important implications for the assessment of hazards and risks from future eruptive activity at Merapi.

Are sex ratio distorting endosymbionts responsible for mating system variation among dance flies (Diptera: Empidinae)?

PubMed Central

Herridge, Elizabeth J.; Ness, Rob W.; Bussière, Luc F.

2017-01-01

Maternally inherited bacterial endosymbionts are common in many arthropod species. Some endosymbionts cause female-biased sex ratio distortion in their hosts that can result in profound changes to a host’s mating behaviour and reproductive biology. Dance flies (Diptera: Empidinae) are well known for their unusual reproductive biology, including species with female-specific ornamentation and female-biased lek-like swarming behaviour. The cause of the repeated evolution of female ornaments in these flies remains unknown, but is probably associated with female-biased sex ratios in individual species. In this study we assessed whether dance flies harbour sex ratio distorting endosymbionts that might have driven these mating system evolutionary changes. We measured the incidence and prevalence of infection by three endosymbionts that are known to cause female-biased sex ratios in other insect hosts (Wolbachia, Rickettsia and Spiroplasma) across 20 species of dance flies. We found evidence of widespread infection by all three symbionts and variation in sex-specific prevalence across the taxa sampled. However, there was no relationship between infection prevalence and adult sex ratio measures and no evidence that female ornaments are associated with high prevalences of sex-biased symbiont infections. We conclude that the current distribution of endosymbiont infections is unlikely to explain the diversity in mating systems among dance fly species. PMID:28609446

Are sex ratio distorting endosymbionts responsible for mating system variation among dance flies (Diptera: Empidinae)?

PubMed

Murray, Rosalind L; Herridge, Elizabeth J; Ness, Rob W; Bussière, Luc F

2017-01-01

Maternally inherited bacterial endosymbionts are common in many arthropod species. Some endosymbionts cause female-biased sex ratio distortion in their hosts that can result in profound changes to a host's mating behaviour and reproductive biology. Dance flies (Diptera: Empidinae) are well known for their unusual reproductive biology, including species with female-specific ornamentation and female-biased lek-like swarming behaviour. The cause of the repeated evolution of female ornaments in these flies remains unknown, but is probably associated with female-biased sex ratios in individual species. In this study we assessed whether dance flies harbour sex ratio distorting endosymbionts that might have driven these mating system evolutionary changes. We measured the incidence and prevalence of infection by three endosymbionts that are known to cause female-biased sex ratios in other insect hosts (Wolbachia, Rickettsia and Spiroplasma) across 20 species of dance flies. We found evidence of widespread infection by all three symbionts and variation in sex-specific prevalence across the taxa sampled. However, there was no relationship between infection prevalence and adult sex ratio measures and no evidence that female ornaments are associated with high prevalences of sex-biased symbiont infections. We conclude that the current distribution of endosymbiont infections is unlikely to explain the diversity in mating systems among dance fly species.

Current at domain walls, roughly speaking: nanoscales studies of disorder roughening and conduction

NASA Astrophysics Data System (ADS)

Paruch, Patrycja

2013-03-01

Domain walls in (multi)ferroic materials are the thin elastic interfaces separating regions with different orientations of magnetisation, electric polarisation, or spontaneous strain. Understanding their behaviour, and controlling domain size and stability, is key for their integration into applications, while fundamentally, domain walls provide an excellent model system in which the rich physics of disordered elastic interfaces can be accesses. In addition, domain walls can present novel properties, quite different from those of their parent materials, making them potentially useful as active components in future nano-devices. Here, we present our atomic force microscopy studies of ferroelectric domain walls in epitaxial Pb(Zr0.2Ti0.8)O3 and BiFeO3 thin films, in which we use piezorespose force microscopy to show unusual domain wall roughening behaviour, with very localised disorder regions in the sample leading to a complex, multi-affine scaling of the domain wall shape. We also show the effects of temperature, environmental conditions, and defects on switching dynamics and domain wall roughness. We combine these observations with parallel conductive-tip atomic force microscopy current measurements, which also show highly localised variations in conduction, and highlight the key role played by oxygen vacancies in the observed domain wall conduction.

Do cultural factors affect causal beliefs? Rational and magical thinking in Britain and Mexico.

PubMed

Subbotsky, Eugene; Quinteros, Graciela

2002-11-01

In two experiments, unusual phenomena (spontaneous destruction of objects in an empty wooden box) were demonstrated to adult participants living in rural communities in Mexico. These were accompanied by actions which had no physical link to the destroyed object but could suggest either scientifically based (the effect of an unknown physical device) or non-scientifically based (the effect of a 'magic spell') causal explanations of the event. The results were compared to the results of the matching two experiments from the earlier study made in Britain. The expectation that scientifically based explanations would prevail in British participants' judgments and behaviours, whereas Mexican participants would be more tolerant toward magical explanations, received only partial support. The prevalence of scientific explanations over magical explanations was evident in British participants' verbal judgments but not in Mexican participants' judgments. In their behavioural responses under the low-risk condition, British participants rejected magical explanations more frequently than did Mexican participants. However, when the risk of disregarding the possible causal effect of magic was increased, participants in both samples showed an equal degree of credulity in the possible effect of magic. The data are interpreted in terms of the relationships between scientific and 'folk' representations of causality and object permanence.

Combinatorial screening of organic electronic materials: thin film stability

NASA Astrophysics Data System (ADS)

Chattopadhyay, Santanu; Carson Meredith, J.

2005-01-01

Dewetting of thin polymeric semiconducting-insulating (and conducting-insulating) bilayers is a serious fundamental problem facing the fabrication of organic electronic devices such as transistors, light-emitting diodes and supercapacitors. This paper describes a high-throughput characterization method that utilizes orthogonal thickness-gradient libraries of the bilayer components poly(3-octylthiophene) (semiconductor) and poly(styrene) (insulator). The technique allows simultaneous observation of hundreds of combinations of thicknesses and has permitted rapid discovery of a previously-unknown VDW instability transition. We observe that the onset of VDW instability in the PS-P3OT bilayer is a complex function of P3OT thickness that cannot be predicted by Hamaker constant models for free energy. At low P3OT thickness, the semiconductor acts to stabilize the PS insulator. But above a P3OT thickness of 175 nm, this behaviour is switched and P3OT destabilizes the PS. These thickness-dependent effects are correlated very well with dramatic transitions in P3OT optical spectra and the P3OT-AFM tip interaction forces. This unusual behaviour places critical limitations on practical device thicknesses and interfacial combinations, and points to the need for a thin-film stability theory that accounts for thickness-dependent molecular-electronic effects.

Rapid humanitarian assessments and rationality: a value-of-information study from Iraq, 2003-04.

PubMed

Benini, Aldo; Conley, Charles

2007-03-01

Rapid assessments are one of the standard informational tools in humanitarian response and are supposed to contribute to rational decision-making.(1) The extent to which the assessment organisation itself behaves rationally, however, is an open question. This can be evaluated against multiple criteria, such as the cost and value of the information it collects and its ability to adapt flexibly design or samples when the survey environment changes unforeseeably. An unusual data constellation from two concurrent recent (2003-04) rapid assessments in northern Iraq permits us to model part of the actual assessment behaviour in terms of geographical, community and prior substantive information attributes. The model correctly predicts the decisions, in 79 per cent of the 2,425 local communities in focus, that data collector teams in the Emergency Mine Action Survey made to visit or not to visit. The analysis demonstrates variably rational behaviour under conditions of insecurity, repeated regrouping and incomplete sampling frames. A pronounced bias towards very small rural settlements is irrational for the overall results, but may be a rational strategy of individual survey workers seeking to prolong their employment. Implications for future assessments are sketched in the areas of tools for urban surveys, greater adaptability, including early feedback from users, and sensibility to value-of-information concepts.

Antelope Predation by Nigerian Forest Baboons: Ecological and Behavioural Correlates.

PubMed

Sommer, Volker; Lowe, Adriana; Jesus, Gonçalo; Alberts, Nienke; Bouquet, Yaëlle; Inglis, David M; Petersdorf, Megan; van Riel, Eelco; Thompson, James; Ross, Caroline

2016-01-01

Baboons are well studied in savannah but less so in more closed habitats. We investigated predation on mammals by olive baboons (Papio anubis) at a geographical and climatic outlier, Gashaka Gumti National Park (Nigeria), the wettest and most forested site so far studied. Despite abundant wildlife, meat eating was rare and selective. Over 16 years, baboons killed 7 bushbuck (Tragelaphus scriptus) and 3 red-flanked duiker (Cephalophus rufilatus), mostly still-lying 'parked' infants. Taking observation time into account, this is 1 predation per group every 3.3 months - far lower than at other sites. Some features of meat eating resemble those elsewhere; predation is opportunistic, adult males monopolize most prey, a targeted killing bite is lacking and begging or active sharing is absent. Carcass owners employ evasive tactics, as meat is often competed over, but satiated owners may tolerate others taking meat. Other features are unusual; this is only the second study site with predation records for bushbuck and the only one for red-flanked duiker. The atypical prey and rarity of eating mammals probably reflects the difficulty of acquiring prey animals when vegetation cover is dense. Our data support the general prediction of the socioecological model that environments shape behavioural patterns, while acknowledging their intraspecific or intrageneric plasticity. © 2016 S. Karger AG, Basel.

Medium-range fire weather forecasts

Treesearch

J.O. Roads; K. Ueyoshi; S.C. Chen; J. Alpert; F. Fujioka

1991-01-01

The forecast skill of theNational Meteorological Center's medium range forecast (MRF) numerical forecasts of fire weather variables is assessed for the period June 1,1988 to May 31,1990. Near-surface virtual temperature, relative humidity, wind speed and a derived fire weather index (FWI) are forecast well by the MRF model. However, forecast relative humidity has...

Probability fire weather forecasts .. show promise in 3-year trial

Treesearch

Paul G. Scowcroft

1970-01-01

Probability fire weather forecasts were compared with categorical and climatological forecasts in a trial in southern California during the 1965-1967 fire seasons. Equations were developed to express the reliability of forecasts and degree of skill shown by the forecaster. Evaluation of 336 daily reports suggests that probability forecasts were more reliable. For...

NASA Products to Enhance Energy Utility Load Forecasting

NASA Technical Reports Server (NTRS)

Lough, G.; Zell, E.; Engel-Cox, J.; Fungard, Y.; Jedlovec, G.; Stackhouse, P.; Homer, R.; Biley, S.

2012-01-01

Existing energy load forecasting tools rely upon historical load and forecasted weather to predict load within energy company service areas. The shortcomings of load forecasts are often the result of weather forecasts that are not at a fine enough spatial or temporal resolution to capture local-scale weather events. This project aims to improve the performance of load forecasting tools through the integration of high-resolution, weather-related NASA Earth Science Data, such as temperature, relative humidity, and wind speed. Three companies are participating in operational testing one natural gas company, and two electric providers. Operational results comparing load forecasts with and without NASA weather forecasts have been generated since March 2010. We have worked with end users at the three companies to refine selection of weather forecast information and optimize load forecast model performance. The project will conclude in 2012 with transitioning documented improvements from the inclusion of NASA forecasts for sustained use by energy utilities nationwide in a variety of load forecasting tools. In addition, Battelle has consulted with energy companies nationwide to document their information needs for long-term planning, in light of climate change and regulatory impacts.

Optimizing Tsunami Forecast Model Accuracy

NASA Astrophysics Data System (ADS)

Whitmore, P.; Nyland, D. L.; Huang, P. Y.

2015-12-01

Recent tsunamis provide a means to determine the accuracy that can be expected of real-time tsunami forecast models. Forecast accuracy using two different tsunami forecast models are compared for seven events since 2006 based on both real-time application and optimized, after-the-fact "forecasts". Lessons learned by comparing the forecast accuracy determined during an event to modified applications of the models after-the-fact provide improved methods for real-time forecasting for future events. Variables such as source definition, data assimilation, and model scaling factors are examined to optimize forecast accuracy. Forecast accuracy is also compared for direct forward modeling based on earthquake source parameters versus accuracy obtained by assimilating sea level data into the forecast model. Results show that including assimilated sea level data into the models increases accuracy by approximately 15% for the events examined.

Seasonal Water Balance Forecasts for Drought Early Warning in Ethiopia

NASA Astrophysics Data System (ADS)

Spirig, Christoph; Bhend, Jonas; Liniger, Mark

2016-04-01

Droughts severely impact Ethiopian agricultural production. Successful early warning for drought conditions in the upcoming harvest season therefore contributes to better managing food shortages arising from adverse climatic conditions. So far, however, meteorological seasonal forecasts have not been used in Ethiopia's national food security early warning system (i.e. the LEAP platform). Here we analyse the forecast quality of seasonal forecasts of total rainfall and of the meteorological water balance as a proxy for plant available water. We analyse forecast skill of June to September rainfall and water balance from dynamical seasonal forecast systems, the ECMWF System4 and EC-EARTH global forecasting systems. Rainfall forecasts outperform forecasts assuming a stationary climate mainly in north-eastern Ethiopia - an area that is particularly vulnerable to droughts. Forecasts of the water balance index seem to be even more skilful and thus more useful than pure rainfall forecasts. The results vary though for different lead times and skill measures employed. We further explore the potential added value of dynamically downscaling the forecasts through several dynamical regional climate models made available through the EU FP7 project EUPORIAS. Preliminary results suggest that dynamically downscaled seasonal forecasts are not significantly better compared with seasonal forecasts from the global models. We conclude that seasonal forecasts of a simple climate index such as the water balance have the potential to benefit drought early warning in Ethiopia, both due to its positive predictive skill and higher usefulness than seasonal mean quantities.

A Decision Support System for effective use of probability forecasts

NASA Astrophysics Data System (ADS)

De Kleermaeker, Simone; Verkade, Jan

2013-04-01

Often, water management decisions are based on hydrological forecasts. These forecasts, however, are affected by inherent uncertainties. It is increasingly common for forecasting agencies to make explicit estimates of these uncertainties and thus produce probabilistic forecasts. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a stricter separation of responsibilities between forecasters and decision maker can be made. However, simply having probabilistic forecasts available is not sufficient to realise the associated benefits. Additional effort is required in areas such as forecast visualisation and communication, decision making in uncertainty and forecast verification. Also, revised separation of responsibilities requires a shift in institutional arrangements and responsibilities. A recent study identified a number of additional issues related to the effective use of probability forecasts. When moving from deterministic to probability forecasting, a dimension is added to an already multi-dimensional problem; this makes it increasingly difficult for forecast users to extract relevant information from a forecast. A second issue is that while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be present. For example, in many cases no estimates of flood damage, of costs of management measures and of damage reduction are available. This paper presents the results of the study, including some suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development of the DSS is outlined.

Evaluation of statistical models for forecast errors from the HBV model

NASA Astrophysics Data System (ADS)

Engeland, Kolbjørn; Renard, Benjamin; Steinsland, Ingelin; Kolberg, Sjur

2010-04-01

SummaryThree statistical models for the forecast errors for inflow into the Langvatn reservoir in Northern Norway have been constructed and tested according to the agreement between (i) the forecast distribution and the observations and (ii) median values of the forecast distribution and the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order auto-regressive model was constructed for the forecast errors. The parameters were conditioned on weather classes. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order auto-regressive model was constructed for the forecast errors. For the third model positive and negative errors were modeled separately. The errors were first NQT-transformed before conditioning the mean error values on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: we wanted (a) the forecast distribution to be reliable; (b) the forecast intervals to be narrow; (c) the median values of the forecast distribution to be close to the observed values. Models 1 and 2 gave almost identical results. The median values improved the forecast with Nash-Sutcliffe R eff increasing from 0.77 for the original forecast to 0.87 for the corrected forecasts. Models 1 and 2 over-estimated the forecast intervals but gave the narrowest intervals. Their main drawback was that the distributions are less reliable than Model 3. For Model 3 the median values did not fit well since the auto-correlation was not accounted for. Since Model 3 did not benefit from the potential variance reduction that lies in bias estimation and removal it gave on average wider forecasts intervals than the two other models. At the same time Model 3 on average slightly under-estimated the forecast intervals, probably explained by the use of average measures to evaluate the fit.

Moving beyond the cost-loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker

NASA Astrophysics Data System (ADS)

Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier Filion, Thomas-Charles

2017-06-01

A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. Numerous studies have shown that ensemble forecasts are of higher quality than deterministic ones. Many studies also conclude that decisions based on ensemble rather than deterministic forecasts lead to better decisions in the context of flood mitigation. Hence, it is believed that ensemble forecasts possess a greater economic and social value for both decision makers and the general population. However, the vast majority of, if not all, existing hydro-economic studies rely on a cost-loss ratio framework that assumes a risk-neutral decision maker. To overcome this important flaw, this study borrows from economics and evaluates the economic value of early warning flood systems using the well-known Constant Absolute Risk Aversion (CARA) utility function, which explicitly accounts for the level of risk aversion of the decision maker. This new framework allows for the full exploitation of the information related to a forecasts' uncertainty, making it especially suited for the economic assessment of ensemble or probabilistic forecasts. Rather than comparing deterministic and ensemble forecasts, this study focuses on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exist many different means of building an ensemble forecasting system for future streamflow. One such possibility is to dress deterministic forecasts using the statistics of past error forecasts. Such dressing methods are popular among operational agencies because of their simplicity and intuitiveness. Another approach is the use of ensemble meteorological forecasts for precipitation and temperature, which are then provided as inputs to one or many hydrological model(s). In this study, three concurrent ensemble streamflow forecasting systems are compared: simple statistically dressed deterministic forecasts, forecasts based on meteorological ensembles, and a variant of the latter that also includes an estimation of state variable uncertainty. This comparison takes place for the Montmorency River, a small flood-prone watershed in southern central Quebec, Canada. The assessment of forecasts is performed for lead times of 1 to 5 days, both in terms of forecasts' quality (relative to the corresponding record of observations) and in terms of economic value, using the new proposed framework based on the CARA utility function. It is found that the economic value of a forecast for a risk-averse decision maker is closely linked to the forecast reliability in predicting the upper tail of the streamflow distribution. Hence, post-processing forecasts to avoid over-forecasting could help improve both the quality and the value of forecasts.

Nonlinear surface waves at ferrite-metamaterial waveguide structure

NASA Astrophysics Data System (ADS)

Hissi, Nour El Houda; Mokhtari, Bouchra; Eddeqaqi, Noureddine Cherkaoui; Shabat, Mohammed Musa; Atangana, Jacques

2016-09-01

A new ferrite slab made of a metamaterial (MTM), surrounded by a nonlinear cover cladding and a ferrite substrate, was shown to support unusual types of electromagnetic surface waves. We impose the boundary conditions to derive the dispersion relation and others necessary to formulate the proposed structure. We analyse the dispersion properties of the nonlinear surface waves and we calculate the associated propagation index and the film-cover interface nonlinearity. In the calculation, several sets of the permeability of the MTM are considered. Results show that the waves behaviour depends on the values of the permeability of the MTM, the thickness of the waveguide and the film-cover interface nonlinearity. It is also shown that the use of the singular solutions to the electric field equation allows to identify several new properties of surface waves which do not exist in conventional waveguide.

Self-assembled pit arrays as templates for the integration of Au nanocrystals in oxide surfaces.

PubMed

Konstantinović, Z; Sandiumenge, F; Santiso, J; Balcells, Ll; Martínez, B

2013-02-07

We report on the fabrication of long-range ordered arrays of Au nanocrystals (sub-50 nm range) on top of manganite (La(2/3)Sr(1/3)MnO(3)) thin films achieving area densities around 2 × 10(10) gold nanocrystals per cm(2), well above the densities achievable by using conventional nanofabrication techniques. The gold-manganite interface exhibits excellent conduction properties. Long-range order is achieved by a guided self-assembling process of Au nanocrystals on self-organized pit-arrays acting as a template for the nucleation of gold nanocrystals. Self-organization of pits on the manganite film surface promoted by the underlying stepped SrTiO(3) substrate is achieved by a fine tuning of the growth kinetic pathway, taking advantage of the unusual misfit strain relaxation behaviour of manganite films.

Realizing three-dimensional artificial spin ice by stacking planar nano-arrays

NASA Astrophysics Data System (ADS)

Chern, Gia-Wei; Reichhardt, Charles; Nisoli, Cristiano

2014-01-01

Artificial spin ice is a frustrated magnetic two-dimensional nano-material, recently employed to study variety of tailor-designed unusual collective behaviours. Recently proposed extensions to three dimensions are based on self-assembly techniques and allow little control over geometry and disorder. We present a viable design for the realization of a three-dimensional artificial spin ice with the same level of precision and control allowed by lithographic nano-fabrication of the popular two-dimensional case. Our geometry is based on layering already available two-dimensional artificial spin ice and leads to an arrangement of ice-rule-frustrated units, which is topologically equivalent to that of the tetrahedra in a pyrochlore lattice. Consequently, we show, it exhibits a genuine ice phase and its excitations are, as in natural spin ice materials, magnetic monopoles interacting via Coulomb law.

Data sets on pensions and health: Data collection and sharing for policy design

PubMed Central

Lee, Jinkook

2015-01-01

A growing number of countries are developing or reforming pension and health policies in response to population ageing and to enhance the welfare of their citizens. The adoption of different policies by different countries has resulted in several natural experiments. These offer unusual opportunities to examine the effects of varying policies on health and retirement, individual and family behaviour, and well-being. Realizing these opportunities requires harmonized data-collection efforts. An increasing number of countries have agreed to provide data harmonized with the Health and Retirement Study in the United States. This article discusses these data sets, including their key parameters of pension and health status, research designs, samples, and response rates. It also discusses the opportunities they offer for cross-national studies and their implications for policy evaluation and development. PMID:26229178

A hybrid approach EMD-HW for short-term forecasting of daily stock market time series data

NASA Astrophysics Data System (ADS)

Awajan, Ahmad Mohd; Ismail, Mohd Tahir

2017-08-01

Recently, forecasting time series has attracted considerable attention in the field of analyzing financial time series data, specifically within the stock market index. Moreover, stock market forecasting is a challenging area of financial time-series forecasting. In this study, a hybrid methodology between Empirical Mode Decomposition with the Holt-Winter method (EMD-HW) is used to improve forecasting performances in financial time series. The strength of this EMD-HW lies in its ability to forecast non-stationary and non-linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy and offers a new forecasting method in time series. The daily stock market time series data of 11 countries is applied to show the forecasting performance of the proposed EMD-HW. Based on the three forecast accuracy measures, the results indicate that EMD-HW forecasting performance is superior to traditional Holt-Winter forecasting method.

Using a Software Tool in Forecasting: a Case Study of Sales Forecasting Taking into Account Data Uncertainty

NASA Astrophysics Data System (ADS)

Fabianová, Jana; Kačmáry, Peter; Molnár, Vieroslav; Michalik, Peter

2016-10-01

Forecasting is one of the logistics activities and a sales forecast is the starting point for the elaboration of business plans. Forecast accuracy affects the business outcomes and ultimately may significantly affect the economic stability of the company. The accuracy of the prediction depends on the suitability of the use of forecasting methods, experience, quality of input data, time period and other factors. The input data are usually not deterministic but they are often of random nature. They are affected by uncertainties of the market environment, and many other factors. Taking into account the input data uncertainty, the forecast error can by reduced. This article deals with the use of the software tool for incorporating data uncertainty into forecasting. Proposals are presented of a forecasting approach and simulation of the impact of uncertain input parameters to the target forecasted value by this case study model. The statistical analysis and risk analysis of the forecast results is carried out including sensitivity analysis and variables impact analysis.

A Local Forecast of Land Surface Wetness Conditions, Drought, and St. Louis Encephalitis Virus Transmission Derived from Seasonal Climate Predictions

NASA Astrophysics Data System (ADS)

Shaman, J.; Stieglitz, M.; Zebiak, S.; Cane, M.; Day, J. F.

2002-12-01

We present an ensemble local hydrologic forecast derived from the seasonal forecasts of the International Research Institute (IRI) for Climate Prediction. Three- month seasonal forecasts were used to resample historical meteorological conditions and generate ensemble forcing datasets for a TOPMODEL-based hydrology model. Eleven retrospective forecasts were run at a Florida and New York site. Forecast skill was assessed for mean area modeled water table depth (WTD), i.e. near surface soil wetness conditions, and compared with WTD simulated with observed data. Hydrology model forecast skill was evident at the Florida site but not at the New York site. At the Florida site, persistence of hydrologic conditions and local skill of the IRI seasonal forecast contributed to the local hydrologic forecast skill. This forecast will permit probabilistic prediction of future hydrologic conditions. At the Florida site, we have also quantified the link between modeled WTD (i.e. drought) and the amplification and transmission of St. Louis Encephalitis virus (SLEV). We derive an empirical relationship between modeled land surface wetness and levels of SLEV transmission associated with human clinical cases. We then combine the seasonal forecasts of local, modeled WTD with this empirical relationship and produce retrospective probabilistic seasonal forecasts of epidemic SLEV transmission in Florida. Epidemic SLEV transmission forecast skill is demonstrated. These findings will permit real-time forecast of drought and resultant SLEV transmission in Florida.

Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

NASA Astrophysics Data System (ADS)

Shafiee-Jood, M.; Cai, X.

2017-12-01

Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

Parametric decadal climate forecast recalibration (DeFoReSt 1.0)

NASA Astrophysics Data System (ADS)

Pasternack, Alexander; Bhend, Jonas; Liniger, Mark A.; Rust, Henning W.; Müller, Wolfgang A.; Ulbrich, Uwe

2018-01-01

Near-term climate predictions such as decadal climate forecasts are increasingly being used to guide adaptation measures. For near-term probabilistic predictions to be useful, systematic errors of the forecasting systems have to be corrected. While methods for the calibration of probabilistic forecasts are readily available, these have to be adapted to the specifics of decadal climate forecasts including the long time horizon of decadal climate forecasts, lead-time-dependent systematic errors (drift) and the errors in the representation of long-term changes and variability. These features are compounded by small ensemble sizes to describe forecast uncertainty and a relatively short period for which typically pairs of reforecasts and observations are available to estimate calibration parameters. We introduce the Decadal Climate Forecast Recalibration Strategy (DeFoReSt), a parametric approach to recalibrate decadal ensemble forecasts that takes the above specifics into account. DeFoReSt optimizes forecast quality as measured by the continuous ranked probability score (CRPS). Using a toy model to generate synthetic forecast observation pairs, we demonstrate the positive effect on forecast quality in situations with pronounced and limited predictability. Finally, we apply DeFoReSt to decadal surface temperature forecasts from the MiKlip prototype system and find consistent, and sometimes considerable, improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.

40 CFR Appendix A to Part 57 - Primary Nonferrous Smelter Order (NSO) Application

Code of Federal Regulations, 2011 CFR

2011-07-01

... Profit and Loss Summary A.4 Historical Capital Investment Summary B.1 Pre-Control Revenue Forecast B.2 Pre-Control Cost Forecast B.3 Pre-Control Forecast Profit and Loss Summary B.4 Constant Controls Revenue Forecast B.5 Constant Controls Cost Forecast B.6 Constant Controls Forecast Profit and Loss...

Proceedings of the Annual Federal Forecasters Conference (2nd, Washington, D.C., September 6-7, 1989).

ERIC Educational Resources Information Center

Sonnenberg, William; And Others

The Second Annual Federal Forecasters Conference, "Forecasting and Public Policy", provided a forum where forecasters from various Federal agencies could meet and discuss aspects of forecasting in the U.S. Government. A total of 140 forecasters from 42 Federal agencies and other organizations attended the conference. Opening remarks by…

The Federal Forecasters Conference-1997. Papers and Proceedings (9th, Washington, D.C., September 11, 1997).

ERIC Educational Resources Information Center

Gerald, Debra E., Ed.

The Ninth Federal Forecasters Conference provided a forum in which forecasters from different federal agencies and other organizations could meet to discuss various aspects of forecasting in the United States. The theme was "Forecasting in an Era of Diminishing Resources." The conference was attended by 150 forecasters. A keynote address by…

Prior exposure influences the behavioural avoidance by an intertidal gastropod, Bembicium auratum, of acidified waters

NASA Astrophysics Data System (ADS)

Amaral, Valter; Cabral, Henrique N.; Bishop, Melanie J.

2014-01-01

Phenotypic plasticity may be critical to the maintenance of viable populations under future environmental change. Here we examined the role of behavioural avoidance of sub-optimal conditions in enabling the intertidal gastropod, Bembicium auratum, to persist in mangrove forests affected by the low pH runoff from acid sulphate soils (ASS). Behaviourally, the gastropod may be able to avoid periods of particularly high acidity by using pneumatophores and/or mangrove trunks to vertically migrate above the water line or by retreating into its shell. We hypothesised that (1) B. auratum would display greater and more rapid vertical migration out of acidified than reference estuarine waters, and (2) responses would be more pronounced in gastropods collected from acidified than reference sites. Gastropods from acidified sites showed significantly higher activity in and more rapid migration out of acidified waters of pH 6.2-7.0, than reference waters or waters of pH < 5.0. Gastropods from reference locations showed a significantly weaker response to acidified water than those from acidified waters, and which did not significantly differ from their response to reference water. At extremely low pHs, <5.0, a higher proportion of both acidified and reference gastropods retreated into their shell than at higher pHs. Both the migration of gastropods out of acidified waters and retraction into their shells serves to reduce exposure time to acidified waters and may reduce the impact of this stressor on their populations. The stronger response to acidification of gastropods from populations previously exposed to this stressor suggests that the response may be learned, inherited or induced over multiple exposures. Our study adds to growing evidence that estuarine organisms may exhibit considerable physiological and behaviour adaptive capacity to acidification. The potential for such adaptive capacity should be incorporated into studies seeking to forecast impacts to marine organisms of environmental change.

GloFAS-Seasonal: Operational Seasonal Ensemble River Flow Forecasts at the Global Scale

NASA Astrophysics Data System (ADS)

Emerton, Rebecca; Zsoter, Ervin; Smith, Paul; Salamon, Peter

2017-04-01

Seasonal hydrological forecasting has potential benefits for many sectors, including agriculture, water resources management and humanitarian aid. At present, no global scale seasonal hydrological forecasting system exists operationally; although smaller scale systems have begun to emerge around the globe over the past decade, a system providing consistent global scale seasonal forecasts would be of great benefit in regions where no other forecasting system exists, and to organisations operating at the global scale, such as disaster relief. We present here a new operational global ensemble seasonal hydrological forecast, currently under development at ECMWF as part of the Global Flood Awareness System (GloFAS). The proposed system, which builds upon the current version of GloFAS, takes the long-range forecasts from the ECMWF System4 ensemble seasonal forecast system (which incorporates the HTESSEL land surface scheme) and uses this runoff as input to the Lisflood routing model, producing a seasonal river flow forecast out to 4 months lead time, for the global river network. The seasonal forecasts will be evaluated using the global river discharge reanalysis, and observations where available, to determine the potential value of the forecasts across the globe. The seasonal forecasts will be presented as a new layer in the GloFAS interface, which will provide a global map of river catchments, indicating whether the catchment-averaged discharge forecast is showing abnormally high or low flows during the 4-month lead time. Each catchment will display the corresponding forecast as an ensemble hydrograph of the weekly-averaged discharge forecast out to 4 months, with percentile thresholds shown for comparison with the discharge climatology. The forecast visualisation is based on a combination of the current medium-range GloFAS forecasts and the operational EFAS (European Flood Awareness System) seasonal outlook, and aims to effectively communicate the nature of a seasonal outlook while providing useful information to users and partners. We demonstrate the first version of an operational GloFAS seasonal outlook, outlining the model set-up and presenting a first look at the seasonal forecasts that will be displayed in the GloFAS interface, and discuss the initial results of the forecast evaluation.

Ensemble flare forecasting: using numerical weather prediction techniques to improve space weather operations

NASA Astrophysics Data System (ADS)

Murray, S.; Guerra, J. A.

2017-12-01

One essential component of operational space weather forecasting is the prediction of solar flares. Early flare forecasting work focused on statistical methods based on historical flaring rates, but more complex machine learning methods have been developed in recent years. A multitude of flare forecasting methods are now available, however it is still unclear which of these methods performs best, and none are substantially better than climatological forecasts. Current operational space weather centres cannot rely on automated methods, and generally use statistical forecasts with a little human intervention. Space weather researchers are increasingly looking towards methods used in terrestrial weather to improve current forecasting techniques. Ensemble forecasting has been used in numerical weather prediction for many years as a way to combine different predictions in order to obtain a more accurate result. It has proved useful in areas such as magnetospheric modelling and coronal mass ejection arrival analysis, however has not yet been implemented in operational flare forecasting. Here we construct ensemble forecasts for major solar flares by linearly combining the full-disk probabilistic forecasts from a group of operational forecasting methods (ASSA, ASAP, MAG4, MOSWOC, NOAA, and Solar Monitor). Forecasts from each method are weighted by a factor that accounts for the method's ability to predict previous events, and several performance metrics (both probabilistic and categorical) are considered. The results provide space weather forecasters with a set of parameters (combination weights, thresholds) that allow them to select the most appropriate values for constructing the 'best' ensemble forecast probability value, according to the performance metric of their choice. In this way different forecasts can be made to fit different end-user needs.

Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility

NASA Astrophysics Data System (ADS)

Tuba, Zoltán; Bottyán, Zsolt

2018-04-01

Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.

The interplinian activity at Somma-Vesuvius in the last 3500 years

USGS Publications Warehouse

Rolandi, G.; Petrosino, P.; Mc, Geehin J.

1998-01-01

Between 1884 B.C. and A.D. 472, eruptive activity at Somma-Vesuvius was dominated by the three plinian eruptions of Avellino (3550 yr B.P.), Pompei (A.D. 79) and A.D. 472 and, as a result, little attention has been given to the intervening interplinian activity. The interplinian events are here reconstructed using new data from twenty stratigraphic sections around the lower flanks of the volcano. Three main eruptions have been identified fro the protohistoric period (3550 yr B.P.-A.D. 79). The first two occurred shortly after the Avellino event and both show a progression from magmatic to phreatomagmatic behaviour. The third eruption (2700 B.P.) consisted of five phreatomagmetic episodes separated by the emplacement of mud flows. Only one event, the explosive erupton of A.D. 203, has been identified for the ancient historic period (A.D. 79-472). In contrast, the A.D. 472 eruption was followed during the medievel period (A.D. 472-1631) by comparatively vigorous interplinian activity, including four strombolian-phreatomagmatic events and extensive lava effusion, which formed a summit cone (destroyed in A.D. 1631) similar to that on Vesuvius today. Such regular alternations of plinian and interplinian events are evident only since 3550 yr B.P. and provide important constraints for forecasting future behaviour at Somma-Vesuvius.

Long-term effects of warming and ocean acidification are modified by seasonal variation in species responses and environmental conditions

PubMed Central

Godbold, Jasmin A.; Solan, Martin

2013-01-01

Warming of sea surface temperatures and alteration of ocean chemistry associated with anthropogenic increases in atmospheric carbon dioxide will have profound consequences for a broad range of species, but the potential for seasonal variation to modify species and ecosystem responses to these stressors has received little attention. Here, using the longest experiment to date (542 days), we investigate how the interactive effects of warming and ocean acidification affect the growth, behaviour and associated levels of ecosystem functioning (nutrient release) for a functionally important non-calcifying intertidal polychaete (Alitta virens) under seasonally changing conditions. We find that the effects of warming, ocean acidification and their interactions are not detectable in the short term, but manifest over time through changes in growth, bioturbation and bioirrigation behaviour that, in turn, affect nutrient generation. These changes are intimately linked to species responses to seasonal variations in environmental conditions (temperature and photoperiod) that, depending upon timing, can either exacerbate or buffer the long-term directional effects of climatic forcing. Taken together, our observations caution against over emphasizing the conclusions from short-term experiments and highlight the necessity to consider the temporal expression of complex system dynamics established over appropriate timescales when forecasting the likely ecological consequences of climatic forcing. PMID:23980249

How conduit models can be used to interpret volcano monitoring data

NASA Astrophysics Data System (ADS)

Thomas, M. E.; Neuberg, J. W.; Karl, S.; Collinson, A.; Pascal, K.

2012-04-01

During the last decade there have been major advances in the field of volcano monitoring, but to be able to take full advantage of these advances it is vital to link the monitoring data with the physical processes that give rise to the recorded signals. To obtain a better understanding of these physical processes it is necessary to understand the conditions of the system at depth. This can be achieved through numerical modelling. We present the results of conduit models representative of a silicic volcanic system and demonstrate how processes identified and interpreted from these models may manifest in the recorded monitoring data. Links are drawn to seismicity, deformation, and gas emissions. A key point is how these data compliment each other, and through utilising conduit models we are able to interpret how these different data may be recorded in response to a particular process. This is an invaluable tool as it is far easier to draw firm conclusions on what is happening at a volcano if there are several different data sets that suggest the same processes are occurring. Some of these interpretations appear useful in forecasting potentially catastrophic changes in eruptive behaviour, such as a dome collapse leading to violent explosive behaviour, and the role of monitoring data in this capacity will also be addressed.

Conjectured the Behaviour of a Recycled Metal Matrix Composite (MMC⁻AlR) Developed through Hot Press Forging by Means of 3D FEM Simulation.

PubMed

Ahmad, Azlan; Lajis, Mohd Amri; Shamsudin, Shazarel; Yusuf, Nur Kamilah

2018-06-06

Melting aluminium waste to produce a secondary bulk material is such an energy-intensive recycling technique that it also indirectly threatens the environment. Hot press forging is introduced as an alternative. Mixing the waste with another substance is a proven practice that enhances the material integrity. To cope with the technology revolution, a finite element is utilised to predict the behaviour without a practical trial. Utilising commercial software, DEFORM 3D, the conjectures were demonstrated scientifically. The flow stress of the material was modified to suit the material used in the actual experiment. It is acknowledged that the stress⁻strain had gradually increased in each step. Due to the confined forming space, the temperature decreased by ~0.5% because the heat could not simply vacate the area. A reduction of ~10% of the flesh observed in the simulation is roughly the same as in the actual experiment. Above all, the simulation abides by the standards and follows what has been done previously. Through the finite element utilisation, this study forecasted the performance of the recycled composite. The results presented may facilitate improvement of the recycling issue and conserve the environment for a better future.

WPC Maximum Heat Index Forecasts

Science.gov Websites

Forecasts for Western US CLICK ON MAPS FOR MAXIMUM HEAT INDEX AND PROBABILITY FORECASTS FROM SUN MAY 27 2018 02 CLICK to view SAT JUN 02 forecast SUN JUN 03 CLICK to view SUN JUN 03 forecast SUN JUN 03 CLICK to view SUN JUN 03 forecast SUN JUN 03 CLICK to view SUN JUN 03 forecast SUN JUN 03 CLICK to view SUN JUN

EnrollForecast for Excel: K-12 Enrollment Forecasting Program. Software & User's Guide. [Computer Diskette].

ERIC Educational Resources Information Center

Smith, Curtis A.

"EnrollForecast for Excel" will generate a 5-year forecast of K-12 student enrollment. It will also work for any combination of grades between kindergarten and twelth. The forecasts can be printed as either a table or a graph. The user must provide birth history (only if forecasting kindergarten) and enrollment history information. The user also…

On the reliability of seasonal climate forecasts.

PubMed

Weisheimer, A; Palmer, T N

2014-07-06

Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1-5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that 'goodness' should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a '5' should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of 'goodness' rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching '5' across all regions and variables in 30 years time.

Software forecasting as it is really done: A study of JPL software engineers

NASA Technical Reports Server (NTRS)

Griesel, Martha Ann; Hihn, Jairus M.; Bruno, Kristin J.; Fouser, Thomas J.; Tausworthe, Robert C.

1993-01-01

This paper presents a summary of the results to date of a Jet Propulsion Laboratory internally funded research task to study the costing process and parameters used by internally recognized software cost estimating experts. Protocol Analysis and Markov process modeling were used to capture software engineer's forecasting mental models. While there is significant variation between the mental models that were studied, it was nevertheless possible to identify a core set of cost forecasting activities, and it was also found that the mental models cluster around three forecasting techniques. Further partitioning of the mental models revealed clustering of activities, that is very suggestive of a forecasting lifecycle. The different forecasting methods identified were based on the use of multiple-decomposition steps or multiple forecasting steps. The multiple forecasting steps involved either forecasting software size or an additional effort forecast. Virtually no subject used risk reduction steps in combination. The results of the analysis include: the identification of a core set of well defined costing activities, a proposed software forecasting life cycle, and the identification of several basic software forecasting mental models. The paper concludes with a discussion of the implications of the results for current individual and institutional practices.

Utilizing Climate Forecasts for Improving Water and Power Systems Coordination

NASA Astrophysics Data System (ADS)

Arumugam, S.; Queiroz, A.; Patskoski, J.; Mahinthakumar, K.; DeCarolis, J.

2016-12-01

Climate forecasts, typically monthly-to-seasonal precipitation forecasts, are commonly used to develop streamflow forecasts for improving reservoir management. Irrespective of their high skill in forecasting, temperature forecasts in developing power demand forecasts are not often considered along with streamflow forecasts for improving water and power systems coordination. In this study, we consider a prototype system to analyze the utility of climate forecasts, both precipitation and temperature, for improving water and power systems coordination. The prototype system, a unit-commitment model that schedules power generation from various sources, is considered and its performance is compared with an energy system model having an equivalent reservoir representation. Different skill sets of streamflow forecasts and power demand forecasts are forced on both water and power systems representations for understanding the level of model complexity required for utilizing monthly-to-seasonal climate forecasts to improve coordination between these two systems. The analyses also identify various decision-making strategies - forward purchasing of fuel stocks, scheduled maintenance of various power systems and tradeoff on water appropriation between hydropower and other uses - in the context of various water and power systems configurations. Potential application of such analyses for integrating large power systems with multiple river basins is also discussed.

Verification of temperature, precipitation, and streamflow forecasts from the NOAA/NWS Hydrologic Ensemble Forecast Service (HEFS): 1. Experimental design and forcing verification

NASA Astrophysics Data System (ADS)

Brown, James D.; Wu, Limin; He, Minxue; Regonda, Satish; Lee, Haksu; Seo, Dong-Jun

2014-11-01

Retrospective forecasts of precipitation, temperature, and streamflow were generated with the Hydrologic Ensemble Forecast Service (HEFS) of the U.S. National Weather Service (NWS) for a 20-year period between 1979 and 1999. The hindcasts were produced for two basins in each of four River Forecast Centers (RFCs), namely the Arkansas-Red Basin RFC, the Colorado Basin RFC, the California-Nevada RFC, and the Middle Atlantic RFC. Precipitation and temperature forecasts were produced with the HEFS Meteorological Ensemble Forecast Processor (MEFP). Inputs to the MEFP comprised ;raw; precipitation and temperature forecasts from the frozen (circa 1997) version of the NWS Global Forecast System (GFS) and a climatological ensemble, which involved resampling historical observations in a moving window around the forecast valid date (;resampled climatology;). In both cases, the forecast horizon was 1-14 days. This paper outlines the hindcasting and verification strategy, and then focuses on the quality of the temperature and precipitation forecasts from the MEFP. A companion paper focuses on the quality of the streamflow forecasts from the HEFS. In general, the precipitation forecasts are more skillful than resampled climatology during the first week, but comprise little or no skill during the second week. In contrast, the temperature forecasts improve upon resampled climatology at all forecast lead times. However, there are notable differences among RFCs and for different seasons, aggregation periods and magnitudes of the observed and forecast variables, both for precipitation and temperature. For example, the MEFP-GFS precipitation forecasts show the highest correlations and greatest skill in the California Nevada RFC, particularly during the wet season (November-April). While generally reliable, the MEFP forecasts typically underestimate the largest observed precipitation amounts (a Type-II conditional bias). As a statistical technique, the MEFP cannot detect, and thus appropriately correct for, conditions that are undetected by the GFS. The calibration of the MEFP to provide reliable and skillful forecasts of a range of precipitation amounts (not only large amounts) is a secondary factor responsible for these Type-II conditional biases. Interpretation of the verification results leads to guidance on the expected performance and limitations of the MEFP, together with recommendations on future enhancements.

Assessing the skill of seasonal precipitation and streamflow forecasts in sixteen French catchments

NASA Astrophysics Data System (ADS)

Crochemore, Louise; Ramos, Maria-Helena; Pappenberger, Florian

2015-04-01

Meteorological centres make sustained efforts to provide seasonal forecasts that are increasingly skilful. Streamflow forecasting is one of the many applications than can benefit from these efforts. Seasonal flow forecasts generated using seasonal ensemble precipitation forecasts as input to a hydrological model can help to take anticipatory measures for water supply reservoir operation or drought risk management. The objective of the study is to assess the skill of seasonal precipitation and streamflow forecasts in France. First, we evaluated the skill of ECMWF SYS4 seasonal precipitation forecasts for streamflow forecasting in sixteen French catchments. Daily flow forecasts were produced using raw seasonal precipitation forecasts as input to the GR6J hydrological model. Ensemble forecasts are issued every month with 15 or 51 members according to the month of the year and evaluated for up to 90 days ahead. In a second step, we applied eight variants of bias correction approaches to the precipitation forecasts prior to generating the flow forecasts. The approaches were based on the linear scaling and the distribution mapping methods. The skill of the ensemble forecasts was assessed in accuracy (MAE), reliability (PIT Diagram) and overall performance (CRPS). The results show that, in most catchments, raw seasonal precipitation and streamflow forecasts are more skilful in terms of accuracy and overall performance than a reference prediction based on historic observed precipitation and watershed initial conditions at the time of forecast. Reliability is the only attribute that is not significantly improved. The skill of the forecasts is, in general, improved when applying bias correction. Two bias correction methods showed the best performance for the studied catchments: the simple linear scaling of monthly values and the empirical distribution mapping of daily values. L. Crochemore is funded by the Interreg IVB DROP Project (Benefit of governance in DROught adaPtation).

Risky Business: Development, Communication and Use of Hydroclimatic Forecasts

NASA Astrophysics Data System (ADS)

Lall, U.

2012-12-01

Inter-seasonal and longer hydroclimatic forecasts have been made increasingly in the last two decades following the increase in ENSO activity since the early 1980s and the success in seasonal ENSO forecasting. Yet, the number of examples of systematic use of these forecasts and their incorporation into water systems operation continue to be few. This may be due in part to the limited skill in such forecasts over much of the world, but is also likely due to the limited evolution of methods and opportunities to "safely" use uncertain forecasts. There has been a trend to rely more on "physically based" rather than "physically informed" empirical forecasts, and this may in part explain the limited success in developing usable products in more locations. Given the limited skill, forecasters have tended to "dumb" down their forecasts - either formally or subjectively shrinking the forecasts towards climatology, or reducing them to tercile forecasts that serve to obscure the potential information in the forecast. Consequently, the potential utility of such forecasts for decision making is compromised. Water system operating rules are often designed to be robust in the face of historical climate variability, and consequently are adapted to the potential conditions that a forecast seeks to inform. In such situations, there is understandable reluctance by managers to use the forecasts as presented, except in special cases where an alternate course of action is pragmatically appealing in any case. In this talk, I review opportunities to present targeted forecasts for use with decision systems that directly address climate risk and the risk induced by unbiased yet uncertain forecasts, focusing especially on extreme events and water allocation in a competitive environment. Examples from Brazil and India covering surface and ground water conjunctive use strategies that could potentially be insured and lead to improvements over the traditional system operation and resource allocation are provided.

A quality assessment of the MARS crop yield forecasting system for the European Union

NASA Astrophysics Data System (ADS)

van der Velde, Marijn; Bareuth, Bettina

2015-04-01

Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

Understanding Farmers’ Forecast Use from Their Beliefs, Values, Social Norms, and Perceived Obstacles

NASA Astrophysics Data System (ADS)

Hu, Qi; Pytlik Zillig, Lisa M.; Lynne, Gary D.; Tomkins, Alan J.; Waltman, William J.; Hayes, Michael J.; Hubbard, Kenneth G.; Artikov, Ikrom; Hoffman, Stacey J.; Wilhite, Donald A.

2006-09-01

Although the accuracy of weather and climate forecasts is continuously improving and new information retrieved from climate data is adding to the understanding of climate variation, use of the forecasts and climate information by farmers in farming decisions has changed little. This lack of change may result from knowledge barriers and psychological, social, and economic factors that undermine farmer motivation to use forecasts and climate information. According to the theory of planned behavior (TPB), the motivation to use forecasts may arise from personal attitudes, social norms, and perceived control or ability to use forecasts in specific decisions. These attributes are examined using data from a survey designed around the TPB and conducted among farming communities in the region of eastern Nebraska and the western U.S. Corn Belt. There were three major findings: 1) the utility and value of the forecasts for farming decisions as perceived by farmers are, on average, around 3.0 on a 0 7 scale, indicating much room to improve attitudes toward the forecast value. 2) The use of forecasts by farmers to influence decisions is likely affected by several social groups that can provide “expert viewpoints” on forecast use. 3) A major obstacle, next to forecast accuracy, is the perceived identity and reliability of the forecast makers. Given the rapidly increasing number of forecasts in this growing service business, the ambiguous identity of forecast providers may have left farmers confused and may have prevented them from developing both trust in forecasts and skills to use them. These findings shed light on productive avenues for increasing the influence of forecasts, which may lead to greater farming productivity. In addition, this study establishes a set of reference points that can be used for comparisons with future studies to quantify changes in forecast use and influence.

How Hydroclimate Influences the Effectiveness of Particle Filter Data Assimilation of Streamflow in Initializing Short- to Medium-range Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Clark, E.; Wood, A.; Nijssen, B.; Clark, M. P.

2017-12-01

Short- to medium-range (1- to 7-day) streamflow forecasts are important for flood control operations and in issuing potentially life-save flood warnings. In the U.S., the National Weather Service River Forecast Centers (RFCs) issue such forecasts in real time, depending heavily on a manual data assimilation (DA) approach. Forecasters adjust model inputs, states, parameters and outputs based on experience and consideration of a range of supporting real-time information. Achieving high-quality forecasts from new automated, centralized forecast systems will depend critically on the adequacy of automated DA approaches to make analogous corrections to the forecasting system. Such approaches would further enable systematic evaluation of real-time flood forecasting methods and strategies. Toward this goal, we have implemented a real-time Sequential Importance Resampling particle filter (SIR-PF) approach to assimilate observed streamflow into simulated initial hydrologic conditions (states) for initializing ensemble flood forecasts. Assimilating streamflow alone in SIR-PF improves simulated streamflow and soil moisture during the model spin up period prior to a forecast, with consequent benefits for forecasts. Nevertheless, it only consistently limits error in simulated snow water equivalent during the snowmelt season and in basins where precipitation falls primarily as snow. We examine how the simulated initial conditions with and without SIR-PF propagate into 1- to 7-day ensemble streamflow forecasts. Forecasts are evaluated in terms of reliability and skill over a 10-year period from 2005-2015. The focus of this analysis is on how interactions between hydroclimate and SIR-PF performance impact forecast skill. To this end, we examine forecasts for 5 hydroclimatically diverse basins in the western U.S. Some of these basins receive most of their precipitation as snow, others as rain. Some freeze throughout the mid-winter while others experience significant mid-winter melt events. We describe the methodology and present seasonal and inter-basin variations in DA-enhanced forecast skill.

Accuracy of forecasts in strategic intelligence

PubMed Central

Mandel, David R.; Barnes, Alan

2014-01-01

The accuracy of 1,514 strategic intelligence forecasts abstracted from intelligence reports was assessed. The results show that both discrimination and calibration of forecasts was very good. Discrimination was better for senior (versus junior) analysts and for easier (versus harder) forecasts. Miscalibration was mainly due to underconfidence such that analysts assigned more uncertainty than needed given their high level of discrimination. Underconfidence was more pronounced for harder (versus easier) forecasts and for forecasts deemed more (versus less) important for policy decision making. Despite the observed underconfidence, there was a paucity of forecasts in the least informative 0.4–0.6 probability range. Recalibrating the forecasts substantially reduced underconfidence. The findings offer cause for tempered optimism about the accuracy of strategic intelligence forecasts and indicate that intelligence producers aim to promote informativeness while avoiding overstatement. PMID:25024176

Seasonal forecast of St. Louis encephalitis virus transmission, Florida.

PubMed

Shaman, Jeffrey; Day, Jonathan F; Stieglitz, Marc; Zebiak, Stephen; Cane, Mark

2004-05-01

Disease transmission forecasts can help minimize human and domestic animal health risks by indicating where disease control and prevention efforts should be focused. For disease systems in which weather-related variables affect pathogen proliferation, dispersal, or transmission, the potential for disease forecasting exists. We present a seasonal forecast of St. Louis encephalitis virus transmission in Indian River County, Florida. We derive an empiric relationship between modeled land surface wetness and levels of SLEV transmission in humans. We then use these data to forecast SLEV transmission with a seasonal lead. Forecast skill is demonstrated, and a real-time seasonal forecast of epidemic SLEV transmission is presented. This study demonstrates how weather and climate forecast skill-verification analyses may be applied to test the predictability of an empiric disease forecast model.

Seasonal Forecast of St. Louis Encephalitis Virus Transmission, Florida

PubMed Central

Day, Jonathan F.; Stieglitz, Marc; Zebiak, Stephen; Cane, Mark

2004-01-01

Disease transmission forecasts can help minimize human and domestic animal health risks by indicating where disease control and prevention efforts should be focused. For disease systems in which weather-related variables affect pathogen proliferation, dispersal, or transmission, the potential for disease forecasting exists. We present a seasonal forecast of St. Louis encephalitis virus transmission in Indian River County, Florida. We derive an empirical relationship between modeled land surface wetness and levels of SLEV transmission in humans. We then use these data to forecast SLEV transmission with a seasonal lead. Forecast skill is demonstrated, and a real-time seasonal forecast of epidemic SLEV transmission is presented. This study demonstrates how weather and climate forecast skill verification analyses may be applied to test the predictability of an empirical disease forecast model. PMID:15200812

Comparative Analysis of NOAA REFM and SNB3GEO Tools for the Forecast of the Fluxes of High-Energy Electrons at GEO

NASA Technical Reports Server (NTRS)

Balikhin, M. A.; Rodriguez, J. V.; Boynton, R. J.; Walker, S. N.; Aryan, Homayon; Sibeck, D. G.; Billings, S. A.

2016-01-01

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field B(sub z) observations at L1. The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast.

Comparative analysis of NOAA REFM and SNB3GEO tools for the forecast of the fluxes of high-energy electrons at GEO.

PubMed

Balikhin, M A; Rodriguez, J V; Boynton, R J; Walker, S N; Aryan, H; Sibeck, D G; Billings, S A

2016-01-01

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB 3 GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB 3 GEO forecasts use solar wind density and interplanetary magnetic field B z observations at L1.The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB 3 GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB 3 GEO forecast.

Climate-mediated dance of the plankton

NASA Astrophysics Data System (ADS)

Behrenfeld, Michael J.

2014-10-01

Climate change will unquestionably influence global ocean plankton because it directly impacts both the availability of growth-limiting resources and the ecological processes governing biomass distributions and annual cycles. Forecasting this change demands recognition of the vital, yet counterintuitive, attributes of the plankton world. The biomass of photosynthetic phytoplankton, for example, is not proportional to their division rate. Perhaps more surprising, physical processes (such as deep vertical mixing) can actually trigger an accumulation in phytoplankton while simultaneously decreasing their division rates. These behaviours emerge because changes in phytoplankton division rates are paralleled by proportional changes in grazing, viral attack and other loss rates. Here I discuss this trophic dance between predators and prey, how it dictates when phytoplankton biomass remains constant or achieves massive blooms, and how it can determine even the sign of change in ocean ecosystems under a warming climate.

Using Temperature Forecasts to Improve Seasonal Streamflow Forecasts in the Colorado and Rio Grande Basins

NASA Astrophysics Data System (ADS)

Lehner, F.; Wood, A.; Llewellyn, D.; Blatchford, D. B.; Goodbody, A. G.; Pappenberger, F.

2017-12-01

Recent studies have documented the influence of increasing temperature on streamflow across the American West, including snow-melt driven rivers such as the Colorado or Rio Grande. At the same time, some basins are reporting decreasing skill in seasonal streamflow forecasts, termed water supply forecasts (WSFs), over the recent decade. While the skill in seasonal precipitation forecasts from dynamical models remains low, their skill in predicting seasonal temperature variations could potentially be harvested for WSFs to account for non-stationarity in regional temperatures. Here, we investigate whether WSF skill can be improved by incorporating seasonal temperature forecasts from dynamical forecasting models (from the North American Multi Model Ensemble and the European Centre for Medium-Range Weather Forecast System 4) into traditional statistical forecast models. We find improved streamflow forecast skill relative to traditional WSF approaches in a majority of headwater locations in the Colorado and Rio Grande basins. Incorporation of temperature into WSFs thus provides a promising avenue to increase the robustness of current forecasting techniques in the face of continued regional warming.

Skillful Spring Forecasts of September Arctic Sea Ice Extent Using Passive Microwave Data

NASA Technical Reports Server (NTRS)

Petty, A. A.; Schroder, D.; Stroeve, J. C.; Markus, Thorsten; Miller, Jeffrey A.; Kurtz, Nathan Timothy; Feltham, D. L.; Flocco, D.

2017-01-01

In this study, we demonstrate skillful spring forecasts of detrended September Arctic sea ice extent using passive microwave observations of sea ice concentration (SIC) and melt onset (MO). We compare these to forecasts produced using data from a sophisticated melt pond model, and find similar to higher skill values, where the forecast skill is calculated relative to linear trend persistence. The MO forecasts shows the highest skill in March-May, while the SIC forecasts produce the highest skill in June-August, especially when the forecasts are evaluated over recent years (since 2008). The high MO forecast skill in early spring appears to be driven primarily by the presence and timing of open water anomalies, while the high SIC forecast skill appears to be driven by both open water and surface melt processes. Spatial maps of detrended anomalies highlight the drivers of the different forecasts, and enable us to understand regions of predictive importance. Correctly capturing sea ice state anomalies, along with changes in open water coverage appear to be key processes in skillfully forecasting summer Arctic sea ice.

Why Don't We Learn to Accurately Forecast Feelings? How Misremembering Our Predictions Blinds Us to Past Forecasting Errors

ERIC Educational Resources Information Center

Meyvis, Tom; Ratner, Rebecca K.; Levav, Jonathan

2010-01-01

Why do affective forecasting errors persist in the face of repeated disconfirming evidence? Five studies demonstrate that people misremember their forecasts as consistent with their experience and thus fail to perceive the extent of their forecasting error. As a result, people do not learn from past forecasting errors and fail to adjust subsequent…

Assessing the viability of `over-the-loop' real-time short-to-medium range ensemble streamflow forecasts

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, E.; Mendoza, P. A.; Nijssen, B.; Newman, A. J.; Clark, M. P.; Arnold, J.; Nowak, K. C.

2016-12-01

Many if not most national operational short-to-medium range streamflow prediction systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow are automated, but others require the hands-on-effort of an experienced human forecaster. This approach evolved out of the need to correct for deficiencies in the models and datasets that were available for forecasting, and often leads to skillful predictions despite the use of relatively simple, conceptual models. On the other hand, the process is not reproducible, which limits opportunities to assess and incorporate process variations, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast ensembles and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun to develop more centralized, `over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, the operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as the systems are being rolled out in major operational forecasting centers. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis, Research, and Prediction' (SHARP) to implement, assess and demonstrate real-time over-the-loop forecasts. We present early hindcast and verification results from SHARP for short to medium range streamflow forecasts in a number of US case study watersheds.

Assessment of an ensemble seasonal streamflow forecasting system for Australia

NASA Astrophysics Data System (ADS)

Bennett, James C.; Wang, Quan J.; Robertson, David E.; Schepen, Andrew; Li, Ming; Michael, Kelvin

2017-11-01

Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean-land-atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall-runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( < 4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall-runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall-runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does not remedy poor reliability in very dry catchments. Overall, FoGSS is an attractive alternative to historical inflow sequences in all but the driest catchments. We discuss ways in which forecast reliability in very dry catchments could be improved in future work.

Evaluation of streamflow forecast for the National Water Model of U.S. National Weather Service

NASA Astrophysics Data System (ADS)

Rafieeinasab, A.; McCreight, J. L.; Dugger, A. L.; Gochis, D.; Karsten, L. R.; Zhang, Y.; Cosgrove, B.; Liu, Y.

2016-12-01

The National Water Model (NWM), an implementation of the community WRF-Hydro modeling system, is an operational hydrologic forecasting model for the contiguous United States. The model forecasts distributed hydrologic states and fluxes, including soil moisture, snowpack, ET, and ponded water. In particular, the NWM provides streamflow forecasts at more than 2.7 million river reaches for three forecast ranges: short (15 hr), medium (10 days), and long (30 days). In this study, we verify short and medium range streamflow forecasts in the context of the verification of their respective quantitative precipitation forecasts/forcing (QPF), the High Resolution Rapid Refresh (HRRR) and the Global Forecast System (GFS). The streamflow evaluation is performed for summer of 2016 at more than 6,000 USGS gauges. Both individual forecasts and forecast lead times are examined. Selected case studies of extreme events aim to provide insight into the quality of the NWM streamflow forecasts. A goal of this comparison is to address how much streamflow bias originates from precipitation forcing bias. To this end, precipitation verification is performed over the contributing areas above (and between assimilated) USGS gauge locations. Precipitation verification is based on the aggregated, blended StageIV/StageII data as the "reference truth". We summarize the skill of the streamflow forecasts, their skill relative to the QPF, and make recommendations for improving NWM forecast skill.

Colour fluctuations in grapheme-colour synaesthesia: The effect of clinical and non-clinical mood changes.

PubMed

Kay, Collette L; Carmichael, Duncan A; Ruffell, Henry E; Simner, Julia

2015-08-01

Synaesthesia is a condition that gives rise to unusual secondary sensations (e.g., colours are perceived when listening to music). These unusual sensations tend to be reported as being stable throughout adulthood (e.g., Simner & Logie, 2007, Neurocase, 13, 358) and the consistency of these experiences over time is taken as the behavioural hallmark of genuineness. Our study looked at the influence of mood states on synaesthetic colours. In Experiment 1, we recruited grapheme-colour synaesthetes (who experience colours from letters/digits) and elicited their synaesthetic colours, as well as their mood and depression states, in two different testing sessions. In each session, participants completed the PANAS-X (Watson & Clark, 1999) and the BDI-II (Beck, Steer, & Brown, 1996, Manual for Beck Depression Inventory-II), and chose their synaesthetic colours for letters A-Z from an interactive colour palette. We found that negative mood significantly decreased the luminance of synaesthetic colours. In Experiment 2, we showed that synaesthetic colours were also less luminant for synaesthetes with anxiety disorder, versus those without. Additional evidence suggests that colour saturation, too, may inversely correlate with depressive symptoms. These results show that fluctuations in mood within both a normal and clinical range influence synaesthetic colours over time. This has implications for our understanding about the longitudinal stability of synaesthetic experiences, and of how mood may interact with the visual (imagery) systems. © 2014 The British Psychological Society.

The design, synthesis and pharmacological characterization of novel β2-adrenoceptor antagonists

PubMed Central

Hothersall, J Daniel; Black, James; Caddick, Stephen; Vinter, Jeremy G; Tinker, Andrew; Baker, James R

2011-01-01

BACKGROUND AND PURPOSE Selective and potent antagonists for the β2-adrenoceptor are potentially interesting as experimental and clinical tools, and we sought to identify novel ligands with this pharmacology. EXPERIMENTAL APPROACH A range of pharmacological assays was used to assess potency, affinity, selectivity (β2-adrenoceptor vs. β1-adrenoceptor) and efficacy. KEY RESULTS Ten novel compounds were identified but none had as high affinity as the prototypical β2-adrenoceptor blocker ICI-118,551, although one of the novel compounds was more selective for β2-adrenoceptors. Most of the ligands were inverse agonists for β2-adrenoceptor-cAMP signalling, although one (5217377) was a partial agonist and another a neutral antagonist (7929193). None of the ligands were efficacious with regard to β2-adrenoceptor-β-arrestin signalling. The (2S,3S) enantiomers were identified as the most active, although unusually the racemates were the most selective for the β2-adrenoceptors. This was taken as evidence for some unusual enantiospecific behaviour. CONCLUSIONS AND IMPLICATIONS In terms of improving on the pharmacology of the ligand ICI-118,551, one of the compounds was more selective (racemic JB-175), while one was a neutral antagonist (7929193), although none had as high an affinity. The results substantiate the notion that β-blockers do more than simply inhibit receptor activation, and differences between the ligands could provide useful tools to investigate receptor biology. PMID:21323900

Shear zone junctions: Of zippers and freeways

NASA Astrophysics Data System (ADS)

Passchier, Cees W.; Platt, John P.

2017-02-01

Ductile shear zones are commonly treated as straight high-strain domains with uniform shear sense and characteristic curved foliation trails, bounded by non-deforming wall rock. Many shear zones, however, are branched, and if movement on such branches is contemporaneous, the resulting shape can be complicated and lead to unusual shear sense arrangement and foliation geometries in the wall rock. For Y-shaped shear zone triple junctions with three joining branches and transport direction at a high angle to the branchline, only eight basic types of junction are thought to be stable and to produce significant displacement. The simplest type, called freeway junctions, have similar shear sense in all three branches. The other types show joining or separating behaviour of shear zone branches similar to the action of a zipper. Such junctions may have shear zone branches that join to form a single branch (closing zipper junction), or a single shear zone that splits to form two branches, (opening zipper junction). All categories of shear zone junctions show characteristic foliation patterns and deflection of markers in the wall rock. Closing zipper junctions are unusual, since they form a non-active zone with opposite deflection of foliations in the wall rock known as an extraction fault or wake. Shear zipper junctions can form domains of overprinting shear sense along their flanks. A small and large field example are given from NE Spain and Eastern Anatolia. The geometry of more complex, 3D shear zone junctions with slip parallel and oblique to the branchline is briefly discussed.

A Wind Forecasting System for Energy Application

NASA Astrophysics Data System (ADS)

Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

2010-05-01

Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated probabilistic wind forecasts which will be invaluable in wind energy management. In brief, this method turns the ensemble forecasts into a calibrated predictive probability distribution. Each ensemble member is provided with a 'weight' determined by its relative predictive skill over a training period of around 30 days. Verification of data is carried out using observed wind data from operational wind farms. These are then compared to existing forecasts produced by ECMWF and Met Eireann in relation to skill scores. We are developing decision-making models to show the benefits achieved using the data produced by our wind energy forecasting system. An energy trading model will be developed, based on the rules currently used by the Single Electricity Market Operator for energy trading in Ireland. This trading model will illustrate the potential for financial savings by using the forecast data generated by this research.

Superensemble forecasts of dengue outbreaks

PubMed Central

Kandula, Sasikiran; Shaman, Jeffrey

2016-01-01

In recent years, a number of systems capable of predicting future infectious disease incidence have been developed. As more of these systems are operationalized, it is important that the forecasts generated by these different approaches be formally reconciled so that individual forecast error and bias are reduced. Here we present a first example of such multi-system, or superensemble, forecast. We develop three distinct systems for predicting dengue, which are applied retrospectively to forecast outbreak characteristics in San Juan, Puerto Rico. We then use Bayesian averaging methods to combine the predictions from these systems and create superensemble forecasts. We demonstrate that on average, the superensemble approach produces more accurate forecasts than those made from any of the individual forecasting systems. PMID:27733698

Use of medium-range numerical weather prediction model output to produce forecasts of streamflow

USGS Publications Warehouse

Clark, M.P.; Hay, L.E.

2004-01-01

This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3??C. In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases he accuracy of precipitation forecasts over the northeastern United States, but overall, the accuracy of MOS-based precipitation forecasts is slightly lower than the raw NCEP forecasts. Four basins in the United States were chosen as case studies to evaluate the value of MRF output for predictions of streamflow. Streamflow forecasts using MRF output were generated for one rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango, Colorado: East Fork of the Carson River near Gardnerville, Nevada: and Cle Elum River near Roslyn, Washington). Hydrologic model output forced with measured-station data were used as "truth" to focus attention on the hydrologic effects of errors in the MRF forecasts. Eight-day streamflow forecasts produced using the MOS-corrected MRF output as input (MOS) were compared with those produced using the climatic Ensemble Streamflow Prediction (ESP) technique. MOS-based streamflow forecasts showed increased skill in the snowmelt-dominated river basins, where daily variations in streamflow are strongly forced by temperature. In contrast, the skill of MOS forecasts in the rainfall-dominated basin (the Alapaha River) were equivalent to the skill of the ESP forecasts. Further improvements in streamflow forecasts require more accurate local-scale forecasts of precipitation and temperature, more accurate specification of basin initial conditions, and more accurate model simulations of streamflow. ?? 2004 American Meteorological Society.

HESS Opinions "On forecast (in)consistency in a hydro-meteorological chain: curse or blessing?"

NASA Astrophysics Data System (ADS)

Pappenberger, F.; Cloke, H. L.; Persson, A.; Demeritt, D.

2011-07-01

Flood forecasting increasingly relies on numerical weather prediction forecasts to achieve longer lead times. One of the key difficulties that is emerging in constructing a decision framework for these flood forecasts is what to dowhen consecutive forecasts are so different that they lead to different conclusions regarding the issuing of warnings or triggering other action. In this opinion paper we explore some of the issues surrounding such forecast inconsistency (also known as "Jumpiness", "Turning points", "Continuity" or number of "Swings"). In thsi opinion paper we define forecast inconsistency; discuss the reasons why forecasts might be inconsistent; how we should analyse inconsistency; and what we should do about it; how we should communicate it and whether it is a totally undesirable property. The property of consistency is increasingly emerging as a hot topic in many forecasting environments.

Resolution of Probabilistic Weather Forecasts with Application in Disease Management.

PubMed

Hughes, G; McRoberts, N; Burnett, F J

2017-02-01

Predictive systems in disease management often incorporate weather data among the disease risk factors, and sometimes this comes in the form of forecast weather data rather than observed weather data. In such cases, it is useful to have an evaluation of the operational weather forecast, in addition to the evaluation of the disease forecasts provided by the predictive system. Typically, weather forecasts and disease forecasts are evaluated using different methodologies. However, the information theoretic quantity expected mutual information provides a basis for evaluating both kinds of forecast. Expected mutual information is an appropriate metric for the average performance of a predictive system over a set of forecasts. Both relative entropy (a divergence, measuring information gain) and specific information (an entropy difference, measuring change in uncertainty) provide a basis for the assessment of individual forecasts.

Skill of a global seasonal ensemble streamflow forecasting system

NASA Astrophysics Data System (ADS)

Candogan Yossef, Naze; Winsemius, Hessel; Weerts, Albrecht; van Beek, Rens; Bierkens, Marc

2013-04-01

Forecasting of water availability and scarcity is a prerequisite for managing the risks and opportunities caused by the inter-annual variability of streamflow. Reliable seasonal streamflow forecasts are necessary to prepare for an appropriate response in disaster relief, management of hydropower reservoirs, water supply, agriculture and navigation. Seasonal hydrological forecasting on a global scale could be valuable especially for developing regions of the world, where effective hydrological forecasting systems are scarce. In this study, we investigate the forecasting skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCR-GLOBWB. FEWS-World has been setup within the European Commission 7th Framework Programme project Global Water Scarcity Information Service (GLOWASIS). Skill is assessed in historical simulation mode as well as retroactive forecasting mode. The assessment in historical simulation mode used a meteorological forcing based on observations from the Climate Research Unit of the University of East Anglia and the ERA-40 reanalysis of the European Center for Medium-Range Weather Forecasts (ECMWF). We assessed the skill of the global hydrological model PCR-GLOBWB in reproducing past discharge extremes in 20 large rivers of the world. This preliminary assessment concluded that the prospects for seasonal forecasting with PCR-GLOBWB or comparable models are positive. However this assessment did not include actual meteorological forecasts. Thus the meteorological forcing errors were not assessed. Yet, in a forecasting setup, the predictive skill of a hydrological forecasting system is affected by errors due to uncertainty from numerical weather prediction models. For the assessment in retroactive forecasting mode, the model is forced with actual ensemble forecasts from the seasonal forecast archives of ECMWF. Skill is assessed at 78 stations on large river basins across the globe, for all the months of the year and for lead times up to 6 months. The forecasted discharges are compared with observed monthly streamflow records using the ensemble verification measures Brier Skill Score (BSS) and Continuous Ranked Probability Score (CRPS). The eventual goal is to transfer FEWS-World to operational forecasting mode, where the system will use operational seasonal forecasts from ECMWF. The results will be disseminated on the internet, and hopefully provide information that is valuable for users in data and model-poor regions of the world.

Electricity forecasting on the individual household level enhanced based on activity patterns

PubMed Central

Gajowniczek, Krzysztof; Ząbkowski, Tomasz

2017-01-01

Leveraging smart metering solutions to support energy efficiency on the individual household level poses novel research challenges in monitoring usage and providing accurate load forecasting. Forecasting electricity usage is an especially important component that can provide intelligence to smart meters. In this paper, we propose an enhanced approach for load forecasting at the household level. The impacts of residents’ daily activities and appliance usages on the power consumption of the entire household are incorporated to improve the accuracy of the forecasting model. The contributions of this paper are threefold: (1) we addressed short-term electricity load forecasting for 24 hours ahead, not on the aggregate but on the individual household level, which fits into the Residential Power Load Forecasting (RPLF) methods; (2) for the forecasting, we utilized a household specific dataset of behaviors that influence power consumption, which was derived using segmentation and sequence mining algorithms; and (3) an extensive load forecasting study using different forecasting algorithms enhanced by the household activity patterns was undertaken. PMID:28423039

Assimilation of lightning data by nudging tropospheric water vapor and applications to numerical forecasts of convective events

NASA Astrophysics Data System (ADS)

Dixon, Kenneth

A lightning data assimilation technique is developed for use with observations from the World Wide Lightning Location Network (WWLLN). The technique nudges the water vapor mixing ratio toward saturation within 10 km of a lightning observation. This technique is applied to deterministic forecasts of convective events on 29 June 2012, 17 November 2013, and 19 April 2011 as well as an ensemble forecast of the 29 June 2012 event using the Weather Research and Forecasting (WRF) model. Lightning data are assimilated over the first 3 hours of the forecasts, and the subsequent impact on forecast quality is evaluated. The nudged deterministic simulations for all events produce composite reflectivity fields that are closer to observations. For the ensemble forecasts of the 29 June 2012 event, the improvement in forecast quality from lightning assimilation is more subtle than for the deterministic forecasts, suggesting that the lightning assimilation may improve ensemble convective forecasts where conventional observations (e.g., aircraft, surface, radiosonde, satellite) are less dense or unavailable.

Combining forecast weights: Why and how?

NASA Astrophysics Data System (ADS)

Yin, Yip Chee; Kok-Haur, Ng; Hock-Eam, Lim

2012-09-01

This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia.

Algorithm aversion: people erroneously avoid algorithms after seeing them err.

PubMed

Dietvorst, Berkeley J; Simmons, Joseph P; Massey, Cade

2015-02-01

Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In 5 studies, participants either saw an algorithm make forecasts, a human make forecasts, both, or neither. They then decided whether to tie their incentives to the future predictions of the algorithm or the human. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human.

Evaluation of Wind Power Forecasts from the Vermont Weather Analytics Center and Identification of Improvements

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

Optis, Michael; Scott, George N.; Draxl, Caroline

The goal of this analysis was to assess the wind power forecast accuracy of the Vermont Weather Analytics Center (VTWAC) forecast system and to identify potential improvements to the forecasts. Based on the analysis at Georgia Mountain, the following recommendations for improving forecast performance were made: 1. Resolve the significant negative forecast bias in February-March 2017 (50% underprediction on average) 2. Improve the ability of the forecast model to capture the strong diurnal cycle of wind power 3. Add ability for forecast model to assess internal wake loss, particularly at sites where strong diurnal shifts in wind direction are present.more » Data availability and quality limited the robustness of this forecast assessment. A more thorough analysis would be possible given a longer period of record for the data (at least one full year), detailed supervisory control and data acquisition data for each wind plant, and more detailed information on the forecast system input data and methodologies.« less

Verification of space weather forecasts at the UK Met Office

NASA Astrophysics Data System (ADS)

Bingham, S.; Sharpe, M.; Jackson, D.; Murray, S.

2017-12-01

The UK Met Office Space Weather Operations Centre (MOSWOC) has produced space weather guidance twice a day since its official opening in 2014. Guidance includes 4-day probabilistic forecasts of X-ray flares, geomagnetic storms, high-energy electron events and high-energy proton events. Evaluation of such forecasts is important to forecasters, stakeholders, model developers and users to understand the performance of these forecasts and also strengths and weaknesses to enable further development. Met Office terrestrial near real-time verification systems have been adapted to provide verification of X-ray flare and geomagnetic storm forecasts. Verification is updated daily to produce Relative Operating Characteristic (ROC) curves and Reliability diagrams, and rolling Ranked Probability Skill Scores (RPSSs) thus providing understanding of forecast performance and skill. Results suggest that the MOSWOC issued X-ray flare forecasts are usually not statistically significantly better than a benchmark climatological forecast (where the climatology is based on observations from the previous few months). By contrast, the issued geomagnetic storm activity forecast typically performs better against this climatological benchmark.

Electricity forecasting on the individual household level enhanced based on activity patterns.

PubMed

Gajowniczek, Krzysztof; Ząbkowski, Tomasz

2017-01-01

Leveraging smart metering solutions to support energy efficiency on the individual household level poses novel research challenges in monitoring usage and providing accurate load forecasting. Forecasting electricity usage is an especially important component that can provide intelligence to smart meters. In this paper, we propose an enhanced approach for load forecasting at the household level. The impacts of residents' daily activities and appliance usages on the power consumption of the entire household are incorporated to improve the accuracy of the forecasting model. The contributions of this paper are threefold: (1) we addressed short-term electricity load forecasting for 24 hours ahead, not on the aggregate but on the individual household level, which fits into the Residential Power Load Forecasting (RPLF) methods; (2) for the forecasting, we utilized a household specific dataset of behaviors that influence power consumption, which was derived using segmentation and sequence mining algorithms; and (3) an extensive load forecasting study using different forecasting algorithms enhanced by the household activity patterns was undertaken.

HESS Opinions "On forecast (in)consistency in a hydro-meteorological chain: curse or blessing?"

NASA Astrophysics Data System (ADS)

Pappenberger, F.; Cloke, H. L.; Persson, A.; Demeritt, D.

2011-01-01

Flood forecasting increasingly relies on Numerical Weather Prediction (NWP) forecasts to achieve longer lead times (see Cloke et al., 2009; Cloke and Pappenberger, 2009). One of the key difficulties that is emerging in constructing a decision framework for these flood forecasts is when consecutive forecasts are different, leading to different conclusions regarding the issuing of forecasts, and hence inconsistent. In this opinion paper we explore some of the issues surrounding such forecast inconsistency (also known as "jumpiness", "turning points", "continuity" or number of "swings"; Zoster et al., 2009; Mills and Pepper, 1999; Lashley et al., 2008). We begin by defining what forecast inconsistency is; why forecasts might be inconsistent; how we should analyse it; what we should do about it; how we should communicate it and whether it is a totally undesirable property. The property of consistency is increasingly emerging as a hot topic in many forecasting environments (for a limited discussion on NWP inconsistency see Persson, 2011). However, in this opinion paper we restrict the discussion to a hydro-meteorological forecasting chain in which river discharge forecasts are produced using inputs from NWP. In this area of research (in)consistency is receiving recent interest and application (see e.g., Bartholmes et al., 2008; Pappenberger et al., 2011).

Wind power forecasting: IEA Wind Task 36 & future research issues

NASA Astrophysics Data System (ADS)

Giebel, G.; Cline, J.; Frank, H.; Shaw, W.; Pinson, P.; Hodge, B.-M.; Kariniotakis, G.; Madsen, J.; Möhrlen, C.

2016-09-01

This paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.

On the reliability of seasonal climate forecasts

PubMed Central

Weisheimer, A.; Palmer, T. N.

2014-01-01

Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1–5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that ‘goodness’ should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a ‘5’ should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of ‘goodness’ rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching ‘5’ across all regions and variables in 30 years time. PMID:24789559

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

PubMed

Joslyn, Susan L; LeClerc, Jared E

2012-03-01

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

Assessing probabilistic predictions of ENSO phase and intensity from the North American Multimodel Ensemble

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Ranganathan, Meghana; L'Heureux, Michelle; Barnston, Anthony G.; DelSole, Timothy

2017-05-01

Here we examine the skill of three, five, and seven-category monthly ENSO probability forecasts (1982-2015) from single and multi-model ensemble integrations of the North American Multimodel Ensemble (NMME) project. Three-category forecasts are typical and provide probabilities for the ENSO phase (El Niño, La Niña or neutral). Additional forecast categories indicate the likelihood of ENSO conditions being weak, moderate or strong. The level of skill observed for differing numbers of forecast categories can help to determine the appropriate degree of forecast precision. However, the dependence of the skill score itself on the number of forecast categories must be taken into account. For reliable forecasts with same quality, the ranked probability skill score (RPSS) is fairly insensitive to the number of categories, while the logarithmic skill score (LSS) is an information measure and increases as categories are added. The ignorance skill score decreases to zero as forecast categories are added, regardless of skill level. For all models, forecast formats and skill scores, the northern spring predictability barrier explains much of the dependence of skill on target month and forecast lead. RPSS values for monthly ENSO forecasts show little dependence on the number of categories. However, the LSS of multimodel ensemble forecasts with five and seven categories show statistically significant advantages over the three-category forecasts for the targets and leads that are least affected by the spring predictability barrier. These findings indicate that current prediction systems are capable of providing more detailed probabilistic forecasts of ENSO phase and amplitude than are typically provided.

Towards an Australian ensemble streamflow forecasting system for flood prediction and water management

NASA Astrophysics Data System (ADS)

Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.

2016-12-01

Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.

Added value of dynamical downscaling of winter seasonal forecasts over North America

NASA Astrophysics Data System (ADS)

Tefera Diro, Gulilat; Sushama, Laxmi

2017-04-01

Skillful seasonal forecasts have enormous potential benefits for socio-economic sectors that are sensitive to weather and climate conditions, as the early warning routines could reduce the vulnerability of such sectors. In this study, individual ensemble members of the ECMWF global ensemble seasonal forecasts are dynamically downscaled to produce ensemble of regional seasonal forecasts over North America using the fifth generation Canadian Regional Climate Model (CRCM5). CRCM5 forecasts are initialized on November 1st of each year and are integrated for four months for the 1991-2001 period at 0.22 degree resolution to produce a one-month lead-time forecast. The initial conditions for atmospheric variables are obtained from ERA-Interim reanalysis, whereas the initial conditions for land surface are obtained from a separate ERA-interim driven CRCM5 simulation with spectral nudging applied to the interior domain. The global and regional ensemble forecasts were then verified to investigate the skill and economic benefits of dynamical downscaling. Results indicate that both the global and regional climate models produce skillful precipitation forecast over the southern Great Plains and eastern coasts of the U.S and skillful temperature forecasts over the northern U.S. and most of Canada. In comparison to ECMWF forecasts, CRCM5 forecasts improved the temperature forecast skill over most part of the domain, but the improvements for precipitation is limited to regions with complex topography, where it improves the frequency of intense daily precipitation. CRCM5 forecast also yields a better economic value compared to ECMWF precipitation forecasts, for users whose cost to loss ratio is smaller than 0.5.

Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin

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

Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.

2011-08-15

A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatialmore » scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.« less

Probabilistic Solar Wind and Geomagnetic Forecasting Using an Analogue Ensemble or "Similar Day" Approach

NASA Astrophysics Data System (ADS)

Owens, M. J.; Riley, P.; Horbury, T. S.

2017-05-01

Effective space-weather prediction and mitigation requires accurate forecasting of near-Earth solar-wind conditions. Numerical magnetohydrodynamic models of the solar wind, driven by remote solar observations, are gaining skill at forecasting the large-scale solar-wind features that give rise to near-Earth variations over days and weeks. There remains a need for accurate short-term (hours to days) solar-wind forecasts, however. In this study we investigate the analogue ensemble (AnEn), or "similar day", approach that was developed for atmospheric weather forecasting. The central premise of the AnEn is that past variations that are analogous or similar to current conditions can be used to provide a good estimate of future variations. By considering an ensemble of past analogues, the AnEn forecast is inherently probabilistic and provides a measure of the forecast uncertainty. We show that forecasts of solar-wind speed can be improved by considering both speed and density when determining past analogues, whereas forecasts of the out-of-ecliptic magnetic field [BN] are improved by also considering the in-ecliptic magnetic-field components. In general, the best forecasts are found by considering only the previous 6 - 12 hours of observations. Using these parameters, the AnEn provides a valuable probabilistic forecast for solar-wind speed, density, and in-ecliptic magnetic field over lead times from a few hours to around four days. For BN, which is central to space-weather disturbance, the AnEn only provides a valuable forecast out to around six to seven hours. As the inherent predictability of this parameter is low, this is still likely a marked improvement over other forecast methods. We also investigate the use of the AnEn in forecasting geomagnetic indices Dst and Kp. The AnEn provides a valuable probabilistic forecast of both indices out to around four days. We outline a number of future improvements to AnEn forecasts of near-Earth solar-wind and geomagnetic conditions.

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.

High-Resolution Hydrological Sub-Seasonal Forecasting for Water Resources Management Over Europe

NASA Astrophysics Data System (ADS)

Wood, E. F.; Wanders, N.; Pan, M.; Sheffield, J.; Samaniego, L. E.; Thober, S.; Kumar, R.; Prudhomme, C.; Houghton-Carr, H.

2017-12-01

For decision-making at the sub-seasonal and seasonal time scale, hydrological forecasts with a high temporal and spatial resolution are required by water managers. So far such forecasts have been unavailable due to 1) lack of availability of meteorological seasonal forecasts, 2) coarse temporal resolution of meteorological seasonal forecasts, requiring temporal downscaling, 3) lack of consistency between observations and seasonal forecasts, requiring bias-correction. The EDgE (End-to-end Demonstrator for improved decision making in the water sector in Europe) project commissioned by the ECMWF (C3S) created a unique dataset of hydrological seasonal forecasts derived from four global climate models (CanCM4, FLOR-B01, ECMF, LFPW) in combination with four global hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), resulting in 208 forecasts for any given day. The forecasts provide a daily temporal and 5-km spatial resolution, and are bias corrected against E-OBS meteorological observations. The forecasts are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs), created in collaboration with the end-user community of the EDgE project (e.g. the percentage of ensemble realizations above the 10th percentile of monthly river flow, or below the 90th). Results show skillful forecasts for discharge from 3 months to 6 months (latter for N Europe due to snow); for soil moisture up to three months due precipitation forecast skill and short initial condition memory; and for groundwater greater than 6 months (lowest skill in western Europe.) The SCIIs are effective in communicating both forecast skill and uncertainty. Overall the new system provides an unprecedented ensemble for seasonal forecasts with significant skill over Europe to support water management. The consistency in both the GCM forecasts and the LSM parameterization ensures a stable and reliable forecast framework and methodology, even if additional GCMs or LSMs are added in the future.

National Weather Service Forecast Office - Honolulu, Hawai`i

Science.gov Websites

Locations - Coastal Forecast Kauai Northwest Waters Kauai Windward Waters Kauai Leeward Waters Kauai Channel Oahu Forecast Oahu Surf Forecast Coastal Wind Observations Buoy Reports, and current weather conditions for selected locations tides, sunrise and sunset information Coastal Waters Forecast general weather

Verification of Ensemble Forecasts for the New York City Operations Support Tool

NASA Astrophysics Data System (ADS)

Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

2012-12-01

The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble forecasts is needed to verify that the post-processed forecasts are unbiased, statistically reliable, and preserve the skill inherent in the "raw" NWS ensemble forecasts. A verification procedure and set of metrics will be presented that provide an objective assessment of ensemble forecasts. The procedure will be applied to both raw ensemble hindcasts and to post-processed ensemble hindcasts. The verification metrics will be used to validate proper functioning of the post-processor and to provide a benchmark for comparison of different types of forecasts. For example, current NWS ensemble forecasts are based on climatology, using each historical year to generate a forecast trace. The NWS Hydrologic Ensemble Forecast System (HEFS) under development will utilize output from both the National Oceanic Atmospheric Administration (NOAA) Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFS). Incorporating short-term meteorological forecasts and longer-term climate forecast information should provide sharper, more accurate forecasts. Hindcasts from HEFS will enable New York City to generate verification results to validate the new forecasts and further fine-tune system operating rules. Project verification results will be presented for different watersheds across a range of seasons, lead times, and flow levels to assess the quality of the current ensemble forecasts.

7 CFR 612.6 - Application for water supply forecast service.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 6 2010-01-01 2010-01-01 false Application for water supply forecast service. 612.6... CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SNOW SURVEYS AND WATER SUPPLY FORECASTS § 612.6 Application for water supply forecast service. Requests for obtaining water supply forecasts or...

LINKS to NATIONAL WEATHER SERVICE MARINE FORECAST OFFICES

Science.gov Websites

Coastal Flooding Tsunamis 406 EPIRB's National Weather Service Marine Forecasts LINKS to NATIONAL WEATHER Marine Forecasts in text form ) Coastal NWS Forecast Offices have regionally focused marine webpages which are overflowing with information such as coastal forecasts, predicted tides, and buoy observations

Implementation of Automatic Clustering Algorithm and Fuzzy Time Series in Motorcycle Sales Forecasting

NASA Astrophysics Data System (ADS)

Rasim; Junaeti, E.; Wirantika, R.

2018-01-01

Accurate forecasting for the sale of a product depends on the forecasting method used. The purpose of this research is to build motorcycle sales forecasting application using Fuzzy Time Series method combined with interval determination using automatic clustering algorithm. Forecasting is done using the sales data of motorcycle sales in the last ten years. Then the error rate of forecasting is measured using Means Percentage Error (MPE) and Means Absolute Percentage Error (MAPE). The results of forecasting in the one-year period obtained in this study are included in good accuracy.

Selecting Single Model in Combination Forecasting Based on Cointegration Test and Encompassing Test

PubMed Central

Jiang, Chuanjin; Zhang, Jing; Song, Fugen

2014-01-01

Combination forecasting takes all characters of each single forecasting method into consideration, and combines them to form a composite, which increases forecasting accuracy. The existing researches on combination forecasting select single model randomly, neglecting the internal characters of the forecasting object. After discussing the function of cointegration test and encompassing test in the selection of single model, supplemented by empirical analysis, the paper gives the single model selection guidance: no more than five suitable single models can be selected from many alternative single models for a certain forecasting target, which increases accuracy and stability. PMID:24892061

Selecting single model in combination forecasting based on cointegration test and encompassing test.

PubMed

Jiang, Chuanjin; Zhang, Jing; Song, Fugen

2014-01-01

Combination forecasting takes all characters of each single forecasting method into consideration, and combines them to form a composite, which increases forecasting accuracy. The existing researches on combination forecasting select single model randomly, neglecting the internal characters of the forecasting object. After discussing the function of cointegration test and encompassing test in the selection of single model, supplemented by empirical analysis, the paper gives the single model selection guidance: no more than five suitable single models can be selected from many alternative single models for a certain forecasting target, which increases accuracy and stability.

Neural network versus classical time series forecasting models

NASA Astrophysics Data System (ADS)

Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

2017-05-01

Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

NWS Operational Requirements for Ensemble-Based Hydrologic Forecasts

NASA Astrophysics Data System (ADS)

Hartman, R. K.

2008-12-01

Ensemble-based hydrologic forecasts have been developed and issued by National Weather Service (NWS) staff at River Forecast Centers (RFCs) for many years. Used principally for long-range water supply forecasts, only the uncertainty associated with weather and climate have been traditionally considered. As technology and societal expectations of resource managers increase, the use and desire for risk-based decision support tools has also increased. These tools require forecast information that includes reliable uncertainty estimates across all time and space domains. The development of reliable uncertainty estimates associated with hydrologic forecasts is being actively pursued within the United States and internationally. This presentation will describe the challenges, components, and requirements for operational hydrologic ensemble-based forecasts from the perspective of a NOAA/NWS River Forecast Center.

Forecasting in foodservice: model development, testing, and evaluation.

PubMed

Miller, J L; Thompson, P A; Orabella, M M

1991-05-01

This study was designed to develop, test, and evaluate mathematical models appropriate for forecasting menu-item production demand in foodservice. Data were collected from residence and dining hall foodservices at Ohio State University. Objectives of the study were to collect, code, and analyze the data; develop and test models using actual operation data; and compare forecasting results with current methods in use. Customer count was forecast using deseasonalized simple exponential smoothing. Menu-item demand was forecast by multiplying the count forecast by a predicted preference statistic. Forecasting models were evaluated using mean squared error, mean absolute deviation, and mean absolute percentage error techniques. All models were more accurate than current methods. A broad spectrum of forecasting techniques could be used by foodservice managers with access to a personal computer and spread-sheet and database-management software. The findings indicate that mathematical forecasting techniques may be effective in foodservice operations to control costs, increase productivity, and maximize profits.

The use of ambient humidity conditions to improve influenza forecast.

PubMed

Shaman, Jeffrey; Kandula, Sasikiran; Yang, Wan; Karspeck, Alicia

2017-11-01

Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.

ECMWF Extreme Forecast Index for water vapor transport: A forecast tool for atmospheric rivers and extreme precipitation

NASA Astrophysics Data System (ADS)

Lavers, David A.; Pappenberger, Florian; Richardson, David S.; Zsoter, Ervin

2016-11-01

In winter, heavy precipitation and floods along the west coasts of midlatitude continents are largely caused by intense water vapor transport (integrated vapor transport (IVT)) within the atmospheric river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium-Range Weather Forecasts Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.

Solar flare predictions and warnings

NASA Technical Reports Server (NTRS)

White, K. P., III

1972-01-01

The real-time solar monitoring information supplied to support SPARCS equipped rocket launches, the routine collection and analysis of 3.3-mm solar radio maps, short-term flare forecasts based on these maps, longer-term forecasts based on the recurrence of active regions, and an extension of the flare forecasting technique are summarized. Forecasts for expectation of a solar flare of class or = 2F are given and compared with observed flares. A total of 52 plage regions produced all the flares of class or = 1N during the study period. The following results are indicated: of the total of 21 positive forecasts, 3 were correct and 18 were incorrect; of the total of 31 negative forecasts, 3 were incorrect and 28 were correct; of a total of 6 plage regions producing large flares, 3 were correctly forecast and 3 were missed; and of 46 regions not producing any large flares, 18 were incorrectly forecast and 28 were correctly forecast.

The use of ambient humidity conditions to improve influenza forecast

PubMed Central

Kandula, Sasikiran; Karspeck, Alicia

2017-01-01

Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1–4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast. PMID:29145389

State-space adjustment of radar rainfall and skill score evaluation of stochastic volume forecasts in urban drainage systems.

PubMed

Löwe, Roland; Mikkelsen, Peter Steen; Rasmussen, Michael R; Madsen, Henrik

2013-01-01

Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input for forecasting outflow from two catchments in the Copenhagen area. Stochastic grey-box models are applied to create the runoff forecasts, providing us with not only a point forecast but also a quantification of the forecast uncertainty. Evaluating the results, we can show that using the adjusted radar data improves runoff forecasts compared with using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short-term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time control.

Impact of the initial specification of moisture and vertical motion on precipitation forecasts with a mesoscale model Implications for a satellite mesoscale data base

NASA Technical Reports Server (NTRS)

Mlynczak, Pamela E.; Houghton, David D.; Diak, George R.

1986-01-01

Using a numerical mesoscale model, four simulations were performed to determine the effects of suppressing the initial mesoscale information in the moisture and wind fields on the precipitation forecasts. The simulations included a control forecast 12-h simulation that began at 1200 GMT March 1982 and three experiment simulations with modifications to the moisture and vertical motion fields incorporated at 1800 GMT. The forecasts from 1800 GMT were compared to the second half of the control forecast. It was found that, compared to the control forecast, suppression of the moisture and/or wind initial field(s) produces a drier forecast. However, the characteristics of the precipitation forecasts of the experiments were not different enough to conclude that either mesoscale moisture or mesoscale vertical velocity at the initial time are more important for producing a forecast closer to that of the control.

Enhanced seasonal forecast skill following stratospheric sudden warmings

NASA Astrophysics Data System (ADS)

Sigmond, M.; Scinocca, J. F.; Kharin, V. V.; Shepherd, T. G.

2013-02-01

Advances in seasonal forecasting have brought widespread socio-economic benefits. However, seasonal forecast skill in the extratropics is relatively modest, prompting the seasonal forecasting community to search for additional sources of predictability. For over a decade it has been suggested that knowledge of the state of the stratosphere can act as a source of enhanced seasonal predictability; long-lived circulation anomalies in the lower stratosphere that follow stratospheric sudden warmings are associated with circulation anomalies in the troposphere that can last up to two months. Here, we show by performing retrospective ensemble model forecasts that such enhanced predictability can be realized in a dynamical seasonal forecast system with a good representation of the stratosphere. When initialized at the onset date of stratospheric sudden warmings, the model forecasts faithfully reproduce the observed mean tropospheric conditions in the months following the stratospheric sudden warmings. Compared with an equivalent set of forecasts that are not initialized during stratospheric sudden warmings, we document enhanced forecast skill for atmospheric circulation patterns, surface temperatures over northern Russia and eastern Canada and North Atlantic precipitation. We suggest that seasonal forecast systems initialized during stratospheric sudden warmings are likely to yield significantly greater forecast skill in some regions.

The Texas Children's Hospital immunization forecaster: conceptualization to implementation.

PubMed

Cunningham, Rachel M; Sahni, Leila C; Kerr, G Brady; King, Laura L; Bunker, Nathan A; Boom, Julie A

2014-12-01

Immunization forecasting systems evaluate patient vaccination histories and recommend the dates and vaccines that should be administered. We described the conceptualization, development, implementation, and distribution of a novel immunization forecaster, the Texas Children's Hospital (TCH) Forecaster. In 2007, TCH convened an internal expert team that included a pediatrician, immunization nurse, software engineer, and immunization subject matter experts to develop the TCH Forecaster. Our team developed the design of the model, wrote the software, populated the Excel tables, integrated the software, and tested the Forecaster. We created a table of rules that contained each vaccine's recommendations, minimum ages and intervals, and contraindications, which served as the basis for the TCH Forecaster. We created 15 vaccine tables that incorporated 79 unique dose states and 84 vaccine types to operationalize the entire United States recommended immunization schedule. The TCH Forecaster was implemented throughout the TCH system, the Indian Health Service, and the Virginia Department of Health. The TCH Forecast Tester is currently being used nationally. Immunization forecasting systems might positively affect adherence to vaccine recommendations. Efforts to support health care provider utilization of immunization forecasting systems and to evaluate their impact on patient care are needed.

Counteracting structural errors in ensemble forecast of influenza outbreaks.

PubMed

Pei, Sen; Shaman, Jeffrey

2017-10-13

For influenza forecasts generated using dynamical models, forecast inaccuracy is partly attributable to the nonlinear growth of error. As a consequence, quantification of the nonlinear error structure in current forecast models is needed so that this growth can be corrected and forecast skill improved. Here, we inspect the error growth of a compartmental influenza model and find that a robust error structure arises naturally from the nonlinear model dynamics. By counteracting these structural errors, diagnosed using error breeding, we develop a new forecast approach that combines dynamical error correction and statistical filtering techniques. In retrospective forecasts of historical influenza outbreaks for 95 US cities from 2003 to 2014, overall forecast accuracy for outbreak peak timing, peak intensity and attack rate, are substantially improved for predicted lead times up to 10 weeks. This error growth correction method can be generalized to improve the forecast accuracy of other infectious disease dynamical models.Inaccuracy of influenza forecasts based on dynamical models is partly due to nonlinear error growth. Here the authors address the error structure of a compartmental influenza model, and develop a new improved forecast approach combining dynamical error correction and statistical filtering techniques.

Assessment of reservoir system variable forecasts

NASA Astrophysics Data System (ADS)

Kistenmacher, Martin; Georgakakos, Aris P.

2015-05-01

Forecast ensembles are a convenient means to model water resources uncertainties and to inform planning and management processes. For multipurpose reservoir systems, forecast types include (i) forecasts of upcoming inflows and (ii) forecasts of system variables and outputs such as reservoir levels, releases, flood damage risks, hydropower production, water supply withdrawals, water quality conditions, navigation opportunities, and environmental flows, among others. Forecasts of system variables and outputs are conditional on forecasted inflows as well as on specific management policies and can provide useful information for decision-making processes. Unlike inflow forecasts (in ensemble or other forms), which have been the subject of many previous studies, reservoir system variable and output forecasts are not formally assessed in water resources management theory or practice. This article addresses this gap and develops methods to rectify potential reservoir system forecast inconsistencies and improve the quality of management-relevant information provided to stakeholders and managers. The overarching conclusion is that system variable and output forecast consistency is critical for robust reservoir management and needs to be routinely assessed for any management model used to inform planning and management processes. The above are demonstrated through an application from the Sacramento-American-San Joaquin reservoir system in northern California.

A probabilistic drought forecasting framework: A combined dynamical and statistical approach

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

Yan, Hongxiang; Moradkhani, Hamid; Zarekarizi, Mahkameh

In order to improve drought forecasting skill, this study develops a probabilistic drought forecasting framework comprised of dynamical and statistical modeling components. The novelty of this study is to seek the use of data assimilation to quantify initial condition uncertainty with the Monte Carlo ensemble members, rather than relying entirely on the hydrologic model or land surface model to generate a single deterministic initial condition, as currently implemented in the operational drought forecasting systems. Next, the initial condition uncertainty is quantified through data assimilation and coupled with a newly developed probabilistic drought forecasting model using a copula function. The initialmore » condition at each forecast start date are sampled from the data assimilation ensembles for forecast initialization. Finally, seasonal drought forecasting products are generated with the updated initial conditions. This study introduces the theory behind the proposed drought forecasting system, with an application in Columbia River Basin, Pacific Northwest, United States. Results from both synthetic and real case studies suggest that the proposed drought forecasting system significantly improves the seasonal drought forecasting skills and can facilitate the state drought preparation and declaration, at least three months before the official state drought declaration.« less

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

NASA Astrophysics Data System (ADS)

Rogelis, María Carolina; Werner, Micha

2018-02-01

Numerical weather prediction (NWP) models are fundamental to extend forecast lead times beyond the concentration time of a watershed. Particularly for flash flood forecasting in tropical mountainous watersheds, forecast precipitation is required to provide timely warnings. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that bias correction can provide, in a tropical mountainous area. The paper focuses on the comparison of streamflows obtained from the post-processed precipitation forecasts, particularly the comparison of ensemble forecasts and their potential in providing skilful flood forecasts. The Weather Research and Forecasting (WRF) model is used to produce precipitation forecasts that are post-processed and used to drive a hydrologic model. Discharge forecasts obtained from the hydrological model are used to assess the skill of the WRF model. The results show that post-processed WRF precipitation adds value to the flood early warning system when compared to zero-precipitation forecasts, although the precipitation forecast used in this analysis showed little added value when compared to climatology. However, the reduction of biases obtained from the post-processed ensembles show the potential of this method and model to provide usable precipitation forecasts in tropical mountainous watersheds. The need for more detailed evaluation of the WRF model in the study area is highlighted, particularly the identification of the most suitable parameterisation, due to the inability of the model to adequately represent the convective precipitation found in the study area.

Development and application of an atmospheric-hydrologic-hydraulic flood forecasting model driven by TIGGE ensemble forecasts

NASA Astrophysics Data System (ADS)

Bao, Hongjun; Zhao, Linna

2012-02-01

A coupled atmospheric-hydrologic-hydraulic ensemble flood forecasting model, driven by The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data, has been developed for flood forecasting over the Huaihe River. The incorporation of numerical weather prediction (NWP) information into flood forecasting systems may increase forecast lead time from a few hours to a few days. A single NWP model forecast from a single forecast center, however, is insufficient as it involves considerable non-predictable uncertainties and leads to a high number of false alarms. The availability of global ensemble NWP systems through TIGGE offers a new opportunity for flood forecast. The Xinanjiang model used for hydrological rainfall-runoff modeling and the one-dimensional unsteady flow model applied to channel flood routing are coupled with ensemble weather predictions based on the TIGGE data from the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centers for Environmental Prediction (NCEP). The developed ensemble flood forecasting model is applied to flood forecasting of the 2007 flood season as a test case. The test case is chosen over the upper reaches of the Huaihe River above Lutaizi station with flood diversion and retarding areas. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The Muskingum method is used for flood routing in the flood diversion area. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE ensemble forecasts. The results demonstrate satisfactory flood forecasting with clear signals of probability of floods up to a few days in advance, and show that TIGGE ensemble forecast data are a promising tool for forecasting of flood inundation, comparable with that driven by raingauge observations.

Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

NASA Astrophysics Data System (ADS)

Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

2017-04-01

The improvement of a forecasting system and the evaluation of the quality of its forecasts are recurrent steps in operational practice. However, the evaluation of forecast value or forecast usefulness for better decision-making is, to our knowledge, less frequent, even if it might be essential in many sectors such as hydropower and flood warning. In the hydropower sector, forecast value can be quantified by the economic gain obtained with the optimization of operations or reservoir management rules. Several hydropower operational systems use medium-range forecasts (up to 7-10 days ahead) and energy price predictions to optimize hydropower production. Hence, the operation of hydropower systems, including the management of water in reservoirs, is impacted by weather, climate and hydrologic variability as well as extreme events. In order to assess how the quality of hydrometeorological forecasts impact operations, it is essential to first understand if and how operations and management rules are sensitive to input predictions of different quality. This study investigates how 7-day ahead deterministic and ensemble streamflow forecasts of different quality might impact the economic gains of energy production. It is based on a research model developed by Irstea and EDF to investigate issues relevant to the links between quality and value of forecasts in the optimisation of energy production at the short range. Based on streamflow forecasts and pre-defined management constraints, the model defines the best hours (i.e., the hours with high energy prices) to produce electricity. To highlight the link between forecasts quality and their economic value, we built several synthetic ensemble forecasts based on observed streamflow time series. These inputs are generated in a controlled environment in order to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts are used to assess the sensitivity of the decision model to forecast quality. Relationships between forecast quality and economic value are discussed. This work is part of the IMPREX project, a research project supported by the European Commission under the Horizon 2020 Framework programme, with grant No. 641811 (http://www.imprex.eu)

Global Impacts and Regional Actions: Preparing for the 1997-98 El Niño.

NASA Astrophysics Data System (ADS)

Buizer, James L.; Foster, Josh; Lund, David

2000-09-01

It has been estimated that severe El Niño-related flooding and droughts in Africa, Latin America, North America, and Southeast Asia resulted in more than 22 000 lives lost and in excess of $36 billion in damages during 1997-98. As one of the most severe events this century, the 1997-98 El Niño was unique not only in terms of physical magnitude, but also in terms of human response. This response was made possible by recent advances in climate-observing and forecasting systems, creation and dissemination of forecast information by institutions such as the International Research Institute for Climate Prediction and NOAA's Climate Prediction Center, and individuals in climate-sensitive sectors willing to act on forecast information by incorporating it into their decision-making. The supporting link between the forecasts and their practical application was a product of efforts by several national and international organizations, and a primary focus of the United States National Oceanic and Atmospheric Administration Office of Global Programs (NOAA/OGP).NOAA/OGP over the last decade has supported pilot projects in Latin America, the Caribbean, the South Pacific, Southeast Asia, and Africa to improve transfer of forecast information to climate sensitive sectors, study linkages between climate and human health, and distribute climate information products in certain areas. Working with domestic and international partners, NOAA/OGP helped organize a total of 11 Climate Outlook Fora around the world during the 1997-98 El Niño. At each Outlook Forum, climatologists and meteorologists created regional, consensus-based, seasonal precipitation forecasts and representatives from climate-sensitive sectors discussed options for applying forecast information. Additional ongoing activities during 1997-98 included research programs focused on the social and economic impacts of climate change and the regional manifestations of global-scale climate variations and their effect on decision-making in climate-sensitive sectors in the United States.The overall intent of NOAA/OGP's activities was to make experimental forecast information broadly available to potential users, and to foster a learning process on how seasonal-to-interannual forecasts could be applied in sectors susceptible to climate variability. This process allowed users to explore the capabilities and limitations of climate forecasts currently available, and forecast producers to receive feedback on the utility of their products. Through activities in which NOAA/OGP and its partners were involved, it became clear that further application of forecast information will be aided by improved forecast accuracy and detail, creation of common validation techniques, continued training in forecast generation and application, alternate methods for presenting forecast information, and a systematic strategy for creation and dissemination of forecast products.The overall intent of NOAA/OGP's activities was to make experimental forecast information broadly available to potential users, and to foster a learning process on how seasonal-to-interannual forecasts could be applied in sectors susceptible to climate variability. This process allowed users to explore the capabilities and limitations of climate forecasts currently available, and forecast producers to receive feedback on the utility of their products. Through activities in which NOAA/OGP and its partners were involved, it became clear that further application of forecast information will be aided by improved forecast accuracy and detail, creation of common validation techniques, continued training in forecast generation and application, alternate methods for presenting forecast information, and a systematic strategy for creation and dissemination of forecast products.

A case of Klinefelter syndrome with hypersexual desire

PubMed Central

Perampalam, Sumathy; Barker, Anthony; Nolan, Christopher J

2017-01-01

Klinefelter syndrome (KS) is a chromosomal disorder affecting males, with the typical karyotype of 47,XXY due to a supernumerary X chromosome, which causes progressive testicular failure resulting in androgen deficiency and infertility. Despite it being the most common sex chromosomal disorder, its diagnosis is easily missed. In addition to its classical clinical features of tall stature, gynaecomastia, small testes, and symptoms and signs of hypogonadism including infertility, KS is also often associated with neurocognitive, behavioural and psychiatric disorders. We present a 44-year-old man with KS who, despite having erectile dysfunction, paradoxically had increased libido. He used sildenafil to overcome his erectile dysfunction. Hypersexuality was manifested by very frequent masturbation, multiple sexual partners most of whom were casual, and a sexual offence conviction at the age of 17 years. Discussion focuses on the frequent failure of clinicians to diagnose KS, the neurocognitive, behavioural and psychiatric aspects of KS, this unusual presentation of hypersexuality in a man with KS, and the challenges of medical management of hypogonadism in a man with a history of a sexual offence. Learning points: Klinefelter syndrome (KS) is common in men (about 1 in 600 males), but the diagnosis is very often missed. In addition to classic features of hypogonadism, patients with KS can often have associated neurocognitive, behavioural and/or psychiatric disorders. More awareness of the association between KS and difficulties related to verbal skills in boys could improve rates of early diagnosis and prevent longer-term psychosocial disability. Hypersexuality in the context of hypogonadism raises the possibility of sex steroid independent mechanistic pathways for libido. Testosterone replacement therapy in KS with hypersexuality should be undertaken with caution using a multidisciplinary team approach. PMID:28883919

Pseudocopulatory pollination in lepanthes (orchidaceae: pleurothallidinae) by fungus gnats.

PubMed

Blanco, Mario A; Barboza, Gabriel

2005-04-01

Lepanthes is one of the largest angiosperm genera (>800 species). Their non-rewarding, tiny and colourful flowers are structurally complex. Their pollination mechanism has hitherto remained unknown, but has been subject of ample speculation; the function of the minuscule labellum appendix is especially puzzling. Here, the pollination of L. glicensteinii by sexually deceived male fungus gnats is described and illustrated. Visitors to flowers of L. glicensteinii were photographed and their behaviour documented; some were captured for identification. Occasional visits to flowers of L. helleri, L. stenorhyncha and L. turialvae were also observed. Structural features of flowers and pollinators were studied with SEM. Sexually aroused males of the fungus gnat Bradysia floribunda (Diptera: Sciaridae) were the only visitors and pollinators of L. glicensteinii. The initial long-distance attractant seems to be olfactory. Upon finding a flower, the fly curls his abdomen under the labellum and grabs the appendix with his genitalic claspers, then dismounts the flower and turns around to face away from it. The pollinarium attaches to his abdomen during this pivoting manoeuvre. Pollinia are deposited on the stigma during a subsequent flower visit. The flies appear to ejaculate during pseudocopulation. The visitors of L. helleri, L. stenorhyncha and L. turialvae are different species of fungus gnats that display a similar behaviour. Lepanthes glicensteinii has genitalic pseudocopulatory pollination, the first case reported outside of the Australian orchid genus Cryptostylis. Since most species of Lepanthes have the same unusual flower structure, it is predicted that pollination by sexual deception is prevalent in the genus. Several morphological and phenological traits in Lepanthes seem well suited for exploiting male fungus gnats as pollinators. Correspondingly, some demographic trends common in Lepanthes are consistent with patterns of male sciarid behaviour.

Pseudocopulatory Pollination in Lepanthes (Orchidaceae: Pleurothallidinae) by Fungus Gnats

PubMed Central

BLANCO, MARIO A.; BARBOZA, GABRIEL

2005-01-01

• Background and Aims Lepanthes is one of the largest angiosperm genera (>800 species). Their non-rewarding, tiny and colourful flowers are structurally complex. Their pollination mechanism has hitherto remained unknown, but has been subject of ample speculation; the function of the minuscule labellum appendix is especially puzzling. Here, the pollination of L. glicensteinii by sexually deceived male fungus gnats is described and illustrated. • Methods Visitors to flowers of L. glicensteinii were photographed and their behaviour documented; some were captured for identification. Occasional visits to flowers of L. helleri, L. stenorhyncha and L. turialvae were also observed. Structural features of flowers and pollinators were studied with SEM. • Key Results Sexually aroused males of the fungus gnat Bradysia floribunda (Diptera: Sciaridae) were the only visitors and pollinators of L. glicensteinii. The initial long-distance attractant seems to be olfactory. Upon finding a flower, the fly curls his abdomen under the labellum and grabs the appendix with his genitalic claspers, then dismounts the flower and turns around to face away from it. The pollinarium attaches to his abdomen during this pivoting manoeuvre. Pollinia are deposited on the stigma during a subsequent flower visit. The flies appear to ejaculate during pseudocopulation. The visitors of L. helleri, L. stenorhyncha and L. turialvae are different species of fungus gnats that display a similar behaviour. • Conclusions Lepanthes glicensteinii has genitalic pseudocopulatory pollination, the first case reported outside of the Australian orchid genus Cryptostylis. Since most species of Lepanthes have the same unusual flower structure, it is predicted that pollination by sexual deception is prevalent in the genus. Several morphological and phenological traits in Lepanthes seem well suited for exploiting male fungus gnats as pollinators. Correspondingly, some demographic trends common in Lepanthes are consistent with patterns of male sciarid behaviour. PMID:15728665

An unusual stratospheric ozone decrease in the Southern Hemisphere subtropics linked to isentropic air-mass transport as observed over Irene (25.5° S, 28.1° E) in mid-May 2002

NASA Astrophysics Data System (ADS)

Semane, N.; Bencherif, H.; Morel, B.; Hauchecorne, A.; Diab, R. D.

2006-06-01

A prominent ozone minimum of less than 240 Dobson Units (DU) was observed over Irene (25.5° S, 28.1° E), a subtropical site in the Southern Hemisphere, by the Total Ozone Mapping Spectrometer (TOMS) during May 2002 with an extremely low ozone value of less than 219 DU recorded on 12 May, as compared to the climatological mean value of 249 DU for May between 1999 and 2005. In this study, the vertical structure of this ozone minimum is examined using ozonesonde measurements performed over Irene on 15 May 2002, when the total ozone (as given by TOMS) was about 226 DU. It is shown that this ozone minimum is of Antarctic polar origin with a low-ozone layer in the middle stratosphere above 625 K (where the climatological ozone gradient points equatorward), and is of tropical origin with a low-ozone layer in the lower stratosphere between the 400-K and 450-K isentropic levels (where the climatological ozone gradient is reversed). The upper and lower depleted parts of the ozonesonde profile for 15 May are then respectively attributed to equatorward and poleward transport of low-ozone air toward the subtropics in the Southern Hemisphere. The tropical air moving over Irene and the polar one passing over the same area associated with enhanced planetary-wave activity are successfully simulated using the high-resolution advection contour model of Ertel's potential vorticity MIMOSA. The unusual distribution of ozone over Irene during May 2002 in the middle stratosphere is connected to the anomalously pre-conditioned structure of the polar vortex at that time of the year. The winter stratospheric wave driving leading to the ozone minimum is investigated by means of the Eliassen-Palm flux computed from the European Center for Medium-range Weather Forecasts (ECMWF) ERA40 re-analyses.

Easterly wave activity and associated heavy rainfall during the pre-monsoon season of 2005

NASA Astrophysics Data System (ADS)

Sawaisarje, G. K.; Khare, Prakash; Chaudhari, Hemantkumar S.; Puviarasan, N.; Ranalkar, M. R.

2017-12-01

Waves in easterlies are a tropical disturbance, which are moving from east to west or west-northwest (WNW). Over the Indian region, easterly waves occur mainly in winter, pre-monsoon and post-monsoon seasons. These easterly waves have attracted the attention of many researchers due to the associated heavy rainfall, lightning and thunder squalls. Influence of easterly waves is less explored during pre-monsoon season. It is seen that during years 2001-2015, a total of 80 cases of trough in easterlies were witnessed by southern peninsular India in the pre-monsoon season. The maxima occurred in March (43 cases), followed by April (25 cases) and May (12 cases). It is observed that the year 2005 witnessed the longest spell of easterly waves for 18 days during 24 March to 10 April 2005, which is quite unusual. The event has claimed a death toll of 55 people in the two states of Tamil Nadu and Kerala, and heavy rains associated with this event damaged many houses and huts in Tamil Nadu. The unusual nature of the event has prompted us to undertake the study in details. In all, the event witnessed six systems as troughs in easterlies with their movement westwards from south Andaman Sea region to Lakshadweep and southeast Arabian Sea and Sri Lanka and adjoining Cape Comorin area. An attempt has been made to study the event of easterly waves during the year 2005 by exploring winds, temperature advection, vorticity, moisture convergence and potential instability. The causative reason is due to culmination of positive temperature advection, its multiple interactions with deep convective clouds and moisture incursion from anticyclonic flow close to eastern coast of south peninsular region of India. Observing the waves with the internal mechanism makes the study useful for operational forecasting and provides a better understanding of easterly waves.

Multilevel Cloud Structures above Svalbard

NASA Astrophysics Data System (ADS)

Dörnbrack, Andreas; Pitts, Micheal; Poole, Lamont; Gisinger, Sonja; Maturlli, Marion

2017-04-01

The presentation focusses on the reslts recently published by the authors under the heading "picture of the month" in Monthly Weather Review. The presented picture of the month is a superposition of space-borne lidar observations and high-resolution temperature fields of the ECMWF integrated forecast system (IFS). It displays complex tropospheric and stratospheric clouds in the Arctic winter 2015/16. Near the end of December 2015, the unusual northeastward propagation of warm and humid subtropical air masses as far north as 80°N lifted the tropopause by more than 3 km in 24 h and cooled the stratosphere on a large scale. A widespread formation of thick cirrus clouds near the tropopause and of synoptic-scale polar stratospheric clouds (PSCs) occurred as the temperature dropped below the thresholds for the existence of cloud particles. Additionally, mountain waves were excited by the strong flow at the western edge of the ridge across Svalbard, leading to the formation of mesoscale ice PSCs. The most recent IFS cycle using a horizontal resolution of 8 km globally reproduces the large-scale and mesoscale flow features and leads to a remarkable agreement with the wave structure revealed by the space-borne observations.

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.

Weather features associated with aircraft icing conditions: a case study.

PubMed

Fernández-González, Sergio; Sánchez, José Luis; Gascón, Estíbaliz; López, Laura; García-Ortega, Eduardo; Merino, Andrés

2014-01-01

In the context of aviation weather hazards, the study of aircraft icing is very important because of several accidents attributed to it over recent decades. On February 1, 2012, an unusual meteorological situation caused severe icing of a C-212-200, an aircraft used during winter 2011-2012 to study winter cloud systems in the Guadarrama Mountains of the central Iberian Peninsula. Observations in this case were from a MP-3000A microwave radiometric profiler, which acquired atmospheric temperature and humidity profiles continuously every 2.5 minutes. A Cloud Aerosol and Precipitation Spectrometer (CAPS) was also used to study cloud hydrometeors. Finally, ice nuclei concentration was measured in an isothermal cloud chamber, with the goal of calculating concentrations in the study area. Synoptic and mesoscale meteorological conditions were analysed using the Weather Research and Forecasting (WRF) model. It was demonstrated that topography influenced generation of a mesolow and gravity waves on the lee side of the orographic barrier, in the region where the aircraft experienced icing. Other factors such as moisture, wind direction, temperature, atmospheric stability, and wind shear were decisive in the appearance of icing. This study indicates that icing conditions may arise locally, even when the synoptic situation does not indicate any risk.

The Atmospheric Monitoring Strategy for the Cherenkov Telescope Array

NASA Astrophysics Data System (ADS)

Daniel, M. K.; CTA Consortium

2015-04-01

The Imaging Atmospheric Cherenkov Technique (IACT) is unusual in astronomy as the atmosphere actually forms an intrinsic part of the detector system, with telescopes indirectly detecting very high energy particles by the generation and transport of Cherenkov photons deep within the atmosphere. This means that accurate measurement, characterisation and monitoring of the atmosphere is at the very heart of successfully operating an IACT system. The Cherenkov Telescope Array (CTA) will be the next generation IACT observatory with an ambitious aim to improve the sensitivity of an order of magnitude over current facilities, along with corresponding improvements in angular and energy resolution and extended energy coverage, through an array of Large (23 m), Medium (12 m) and Small (4 m) sized telescopes spread over an area of order ~km2. Whole sky coverage will be achieved by operating at two sites: one in the northern hemisphere and one in the southern hemisphere. This proceedings will cover the characterisation of the candidate sites and the atmospheric calibration strategy. CTA will utilise a suite of instrumentation and analysis techniques for atmospheric modelling and monitoring regarding pointing forecasts, intelligent pointing selection for the observatory operations and for offline data correction.