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PubMed2006

Towards numerical forecasting of long-range air transport of birch pollen: theoretical considerations and a feasibility study.

This paper considers the feasibility of numerical simulation of large-scale atmospheric transport of allergenic pollen. It is shown that at least small grains, such as birch pollen, can stay in the air for a few days, which leads to a characteristic scale for their transport of approximately 10(3) km. The analytical consideration confirmed the applicability of existing dispersion models to the pollen transport task and provided some reference parameterizations of the key processes, including dry and wet deposition. The results were applied to the Finnish Emergency Dispersion Modelling System (SILAM), which was then used to analyze pollen transport to Finland during spring time in 2002-2004. Solutions of the inverse problems (source apportionment) showed that the main source areas, from which the birch flowering can affect Finnish territory, are the Baltic States, Russia, Germany, Poland, and Sweden-depending on the particular meteorological situation. Actual forecasting of pollen dispersion required a birch forest map of Europe and a unified European model for birch flowering, both of which were nonexistent before this study. A map was compiled from the national forest inventories of Western Europe and satellite images of broadleaf forests. The flowering model was based on the mean climatological dates for the onset of birch forests rather than conditions of any specific year. Utilization of probability forecasting somewhat alleviated the problem, but the development of a European-wide flowering model remains the main obstacle for real-time forecasting of large-scale pollen distribution.

Air Movements↗

PubMed1998

A synoptic climatological approach to forecast concentrations of sulfur dioxide and nitrogen oxides in Hong Kong.

The objective of this study is to develop an automated synoptic climatological procedure to forecast high air pollution concentrations in the most polluted synoptic categories. The procedure is able to identify air masses historically associated with high air pollution concentrations. The arrival of air mass can be predicted 24 or 48 h in advance with the use of the weather forecast data. The development and statistical basis of the procedure are discussed, and an analysis of the procedure's ability to forecast weather conditions associated with high air pollution concentrations is presented. In addition, the dataset of 24 weather variables from 1993 to 1995 is used to validate the procedure. The procedure predicts that 70.3 and 83.3% of total high and severe SO2 concentration days fall into the identified most polluted categories, and the corresponding figures for NOx are 47.8 and 73.7%. The agreement between observed and predicted values is generally good. The prediction models can explain about 58 and 45% of total variance for NOx and SO2 with RMSEs of 42.5 and 16.5 microg m(-3), respectively. They are smaller than 1 SD of the observations.

Journal Article↗

PubMed2000

Long range forecasts of the numbers of Helicoverpa punctigera and H. armigera (Lepidoptera: Noctuidae) in Australia using the southern oscillation index and the sea surface temperature.

The use of long-term forecasts of pest pressure is central to better pest management. We relate the Southern Oscillation Index (SOI) and the Sea Surface Temperature (SST) to long-term light-trap catches of the two key moth pests of Australian agriculture, Helicoverpa punctigera (Wallengren) and H. armigera (Hübner), at Narrabri, New South Wales over 11 years, and for H. punctigera only at Turretfield, South Australia over 22 years. At Narrabri, the size of the first spring generation of both species was significantly correlated with the SOI in certain months, sometimes up to 15 months before the date of trapping. Differences in the SOI and SST between significant months were used to build composite variables in multiple regressions which gave fitted values of the trap catches to less than 25% of the observed values. The regressions suggested that useful forecasts of both species could be made 6-15 months ahead. The influence of the two weather variables on trap catches of H. punctigera at Turretfield were not as strong as at Narrabri, probably because the SOI was not as strongly related to rainfall in southern Australia as it is in eastern Australia. The best fits were again given by multiple regressions with SOI plus SST variables, to within 40% of the observed values. The reliability of both variables as predictors of moth numbers may be limited by the lack of stability in the SOI-rainfall correlation over the historical record. As no other data set is available to test the regressions, they can only be tested by future use. The use of long-term forecasts in pest management is discussed, and preliminary analyses of other long sets of insect numbers suggest that the Southern Oscillation Index may be a useful predictor of insect numbers in other parts of the world.

Animals↗

PubMed2003

A dynamic Markov model for forecasting diabetes prevalence in the United States through 2050.

This study develops forecasts of the number of people with diagnosed diabetes and diagnosed diabetes prevalence in the United States through the year 2050. A Markov modeling framework is used to generate forecasts by age, race and ethnicity, and sex. The model forecasts the number of individuals in each of three states (diagnosed with diabetes, not diagnosed with diabetes, and death) in each year using inputs of estimated diagnosed diabetes prevalence and incidence; the relative risk of mortality from diabetes compared with no diabetes; and U.S. Census Bureau estimates of current population, live births, net migration, and the mortality rate of the general population. The projected number of people with diagnosed diabetes rises from 12.0 million in 2000 to 39.0 million in 2050, implying an increase in diagnosed diabetes prevalence from 4.4% in 2000 to 9.7% in 2050.

Age Factors↗

PubMed2000

Forecasting Andean rainfall and crop yield from the influence of El Nino on Pleiades visibility

Farmers in drought-prone regions of Andean South America have historically made observations of changes in the apparent brightness of stars in the Pleiades around the time of the southern winter solstice in order to forecast interannual variations in summer rainfall and in autumn harvests. They moderate the effect of reduced rainfall by adjusting the planting dates of potatoes, their most important crop. Here we use data on cloud cover and water vapour from satellite imagery, agronomic data from the Andean altiplano and an index of El Nino variability to analyse this forecasting method. We find that poor visibility of the Pleiades in June-caused by an increase in subvisual high cirrus clouds-is indicative of an El Nino year, which is usually linked to reduced rainfall during the growing season several months later. Our results suggest that this centuries-old method of seasonal rainfall forecasting may be based on a simple indicator of El Nino variability.

Journal Article↗

PubMed2005

Real-time forecasts of tomorrow's earthquakes in California.

Despite a lack of reliable deterministic earthquake precursors, seismologists have significant predictive information about earthquake activity from an increasingly accurate understanding of the clustering properties of earthquakes. In the past 15 years, time-dependent earthquake probabilities based on a generic short-term clustering model have been made publicly available in near-real time during major earthquake sequences. These forecasts describe the probability and number of events that are, on average, likely to occur following a mainshock of a given magnitude, but are not tailored to the particular sequence at hand and contain no information about the likely locations of the aftershocks. Our model builds upon the basic principles of this generic forecast model in two ways: it recasts the forecast in terms of the probability of strong ground shaking, and it combines an existing time-independent earthquake occurrence model based on fault data and historical earthquakes with increasingly complex models describing the local time-dependent earthquake clustering. The result is a time-dependent map showing the probability of strong shaking anywhere in California within the next 24 hours. The seismic hazard modelling approach we describe provides a better understanding of time-dependent earthquake hazard, and increases its usefulness for the public, emergency planners and the media.

Journal Article↗

PubMed2002

What might we learn from climate forecasts?

Most climate models are large dynamical systems involving a million (or more) variables on big computers. Given that they are nonlinear and not perfect, what can we expect to learn from them about the earth's climate? How can we determine which aspects of their output might be useful and which are noise? And how should we distribute resources between making them "better," estimating variables of true social and economic interest, and quantifying how good they are at the moment? Just as "chaos" prevents accurate weather forecasts, so model error precludes accurate forecasts of the distributions that define climate, yielding uncertainty of the second kind. Can we estimate the uncertainty in our uncertainty estimates? These questions are discussed. Ultimately, all uncertainty is quantified within a given modeling paradigm; our forecasts need never reflect the uncertainty in a physical system.

Journal Article↗

PubMed1999

Residual delay maps unveil global patterns of atmospheric nonlinearity and produce improved local forecasts.

We use residual-delay maps of observational field data for barometric pressure to demonstrate the structure of latitudinal gradients in nonlinearity in the atmosphere. Nonlinearity is weak and largely lacking in tropical and subtropical sites and increases rapidly into the temperate regions where the time series also appear to be much noisier. The degree of nonlinearity closely follows the meridional variation of midlatitude storm track frequency. We extract the specific functional form of this nonlinearity, a V shape in the lagged residuals that appears to be a basic feature of midlatitude synoptic weather systems associated with frontal passages. We present evidence that this form arises from the relative time scales of high-pressure versus low-pressure events. Finally, we show that this nonlinear feature is weaker in a well regarded numerical forecast model (European Centre for Medium-Range Forecasts) because small-scale temporal and spatial variation is smoothed out in the grided inputs. This is significant, in that it allows us to demonstrate how application of statistical corrections based on the residual-delay map may provide marked increases in local forecast accuracy, especially for severe weather systems.

Atmosphere↗

PubMed2006

Tsunami: scientific frontiers, mitigation, forecasting and policy implications.

Tsunamis are an ever-present threat to lives and property along the coasts of most of the world's oceans. As the Sumatra tsunami of 26 December 2004 reminded the world, we must be more proactive in developing ways to reduce their impact on our global society. This article provides an overview of the state of knowledge of tsunamis, presents some challenges confronting advances in the field and identifies some promising frontiers leading to a global warning system. This overview is then used to develop guidelines for advancing the science of forecasting, hazard mitigation programmes and the development of public policy to realize a global system. Much of the information on mitigation and forecasting draws upon the development and accomplishments of a joint state/federal partnership that was forged to reduce tsunami hazards along US coastlines-the National Tsunami Hazard Mitigation Programme. By integrating hazard assessment, warning guidance and mitigation activities, the programme has created a roadmap and a set of tools to make communities more resilient to local and distant tsunamis. Among the tools are forecasting, educational programmes, early warning systems and design guidance for tsunami-resilient communities. Information on international cooperation is drawn from the Global Earth Observing System of Systems (GEOSS). GEOSS provides an international framework to assure international compatibility and interoperability for rapid exchange of data and information.

Computer Simulation↗

PubMed2000

Largest lyapunov-exponent estimation and selective prediction by means of simplex forecast algorithms

Limited predictability is one of the remarkable features of deterministic chaos and this feature may be quantized in terms of Lyapunov exponents. Accordingly, Lyapunov-exponent estimates may be expected to follow in a natural way from forecast algorithms. Exploring this idea, we propose a method estimating the largest Lyapunov exponent from a time series which uses the behavior of so-called simplex forecasts. The method considers the estimation of properties of the distribution of local simplex expansion coefficients. These are also used for the definition of error bars for the Lyapunov-exponent estimates and allows for selective forecasts with improved prediction accuracy. We demonstrate these concepts on standard test examples and three realistic applications to time series concerning largest Lyapunov-exponent estimation of an experimentally obtained hyperchaotic NMR signal, brain state differentiation, and stock-market prediction.

Journal Article↗

PubMed2005

"A 30% chance of rain tomorrow": how does the public understand probabilistic weather forecasts?

The weather forecast says that there is a "30% chance of rain," and we think we understand what it means. This quantitative statement is assumed to be unambiguous and to convey more information than does a qualitative statement like "It might rain tomorrow." Because the forecast is expressed as a single-event probability, however, it does not specify the class of events it refers to. Therefore, even numerical probabilities can be interpreted by members of the public in multiple, mutually contradictory ways. To find out whether the same statement about rain probability evokes various interpretations, we randomly surveyed pedestrians in five metropolises located in countries that have had different degrees of exposure to probabilistic forecasts--Amsterdam, Athens, Berlin, Milan, and New York. They were asked what a "30% chance of rain tomorrow" means both in a multiple-choice and a free-response format. Only in New York did a majority of them supply the standard meteorological interpretation, namely, that when the weather conditions are like today, in 3 out of 10 cases there will be (at least a trace of) rain the next day. In each of the European cities, this alternative was judged as the least appropriate. The preferred interpretation in Europe was that it will rain tomorrow "30% of the time," followed by "in 30% of the area." To improve risk communication with the public, experts need to specify the reference class, that is, the class of events to which a single-event probability refers.

Journal Article↗

PubMed2006

The forecast of the postoperative survival time of patients suffered from non-small cell lung cancer based on PCA and extreme learning machine.

In this paper, a new effective model is proposed to forecast how long the postoperative patients suffered from non-small cell lung cancer will survive. The new effective model which is based on the extreme learning machine (ELM) and principal component analysis (PCA) can forecast successfully the postoperative patients' survival time. The new model obtains better prediction accuracy and faster convergence rate which the model using backpropagation (BP) algorithm and the Levenberg-Marquardt (LM) algorithm to forecast the postoperative patients' survival time can not achieve. Finally, simulation results are given to verify the efficiency and effectiveness of our proposed new model.

Algorithms↗

PubMed2002

The impact of the internet on community pharmacy practice: a comparison of a Delphi panel's forecast with emerging trends.

The purpose of this study was to forecast the impact of Internet pharmacy commerce on various stakeholders. A panel of experts assembled from a list of academicians in the social and administrative pharmaceutical sciences participated in a three-iteration Delphi procedure. Feedback from the aggregate responses of the panel was used to construct questionnaires employed in subsequent iterations of the Delphi. The panel converged to form a consensus upon a variety of issues. They forecasted the attainment of a 10-15% share in the market of prescription and over-the-counter pharmaceuticals through on-line purchases, the formation of strategic alliances among stakeholders in the drug distribution process, a shift in marketing strategies by brick-and-mortar stores, an increase in the prevalence of niching among pharmacy service providers and a subsequent growth in the implementation of cognitive services throughout the industry. With few exceptions, the forecast produced by the Delphi panel appears to be coming to fruition.

Consensus↗

PubMed2000

[Forecast of total pollen counts of sugi (Cryptomeria japonica) from the amount of male flower development and the revised total pollen counts].

We have successfully forecast the total pollen counts of sugi (Cryptomeria japonica) since 1996 by the amount of male flower development. The amount of male flower development was observed at 11 forests in the Tanba Mountains and 10 forests in the Chugoku Mountains depending on both in Hyogo Prefecture. The amount of male flower development on each tree was assigned to one of five classes by the number of male flowers per spring. After a large harvest of male flowers, the production of male flowers declined in the following years, especially at high altitudes. It was also followed by a decrease in the number of airborne pollen grains in the later pollen season. According to an analysis of weather conditions, total pollen counts were correlated with the high temperature between July 6 and 20 and the total pollen counts of the previous season. However, the amount of male flower development was the most significant indicator for forecasting total pollen counts. Decrease in total pollen counts due to abnormal weather during the pollen season was correlated with discrepancies in forest flowering time according to observations made in the Rokko Mountains. Increase in total pollen counts was connected by a development of the sugi forest areas. Twenty percent of mature sugi forests from 1992 which showed an annual increase were associated with an increase in total pollen counts. The accuracy of the forecast was improved by revising the total pollen counts for weather conditions during the dispersion stage, a decrease in the production of male flowers at high altitude, and an increase in the production of male flowers connected by a developing forest areas.

Air Pollutants↗

PubMed1978

Population forecasts for health planning: an assessment of the state of the art.

Health planning agencies make use of age-sex detailed forecasts of population. This article evaluates sources of forecasts, notes the essential role of assumptions in forecasts, and indicates the general quality of techniques for projecting components of population change. It clarifies for health planners what demographers can--and can not--deliver.

Demography↗

PubMed1975

Forecasting patient tray census for hospital food service.

Five computerized forecasting models were tested with data on daily patient tray demand in a large medical center food service, and results were compared with intuitive forecasts made by the food service supervisor. All five models gave more accurate results than the intuitive procedure; an adaptive exponential smoothing model was most accurate. The effects of model complexity and data storage requirements are discussed, and simple exponential smoothing is suggested for forecasting patient tray demand in this setting.

Computers↗

PubMedDate not supplied

A pilot project to detect and forecast harmful algal blooms in the northern Gulf of Mexico.

More timely access to data and information on the initiation, evolution and effects of harmful algal blooms can reduce adverse impacts on valued natural resources and human health. To achieve this in the northern Gulf of Mexico, a pilot project was initiated to develop a user-driven, end-to-end (measurements to applications) observing system. A key strategy of the project is to coordinate existing state, federal and academic programs at an unprecedented level of collaboration and partnership. Resource managers charged with protection of public health and aquatic resources require immediate notice of algal events and a forecast of when, where and what adverse effects will likely occur. Further, managers require integrated analyses and interpretations, rather than raw data, to make effective decisions. Consequently, a functional observing system must collect and transform diverse measurements into usable forecasts. Data needed to support development of forecasts will include such properties as sea surface temperature, winds, currents and waves; precipitation and freshwater flows with related discharges of sediment and nutrients; salinity, dissolved oxygen, and chlorophyll concentrations (in vivo fluorescence); and remotely-sensed spatial images of sea surface chlorophyll concentrations. These data will be provided via a mixture of discrete and autonomous in situ sensing with near real-time data telemetry, and remote sensing from space (SeaWiFS), aircraft (hyperspectral imagery) or land (high-frequency radar). With calibration across these platforms, the project will ultimately provide a 4-dimensional visualization of harmful algae events in a time frame suitable to resource managers.

Aircraft↗

PubMedDate not supplied

[Forecasting of prevalence of cardio-vascular pathology in children population].

Statistical modeling and forecasting of morbidity, disability and mortality of circulatory system diseases and congenital anomalies in children of Ryazan oblast was organized. Procedures of expotential smoothing and determination of statistical significance power of predicted values were applied. Application of expotential smoothing models with linear trend enables reliable forecasting of morbidity of circulatory system diseases and congenital anomalies in children. In Ryazan oblast, disability and mortality of children has higher variance which prevent to apply reliable forecasting. Increase in morbidity and disability rate of circulatory system diseases and congenital anomalies and widening of dispensary group is detected. Predicted increasing of morbidity rate of cardiovascular pathology in children and widening of corresponding dispensary group requires enhanced capacity of medical care supported by according financing.

Adolescent↗