Today's Forecast Research Articles

IDENTIFICATION OF OIL RESERVOIR MICROORGANISMS BY 16S rRNA

According to today's forecasts, global oil reserves may decrease over the next 50 years. Kazakhstan is one of the leading countries in the world in terms of oil resources. With modern methods, only half of the oil in the fields can be extracted. In this regard, the relevance is due to the growing interest in finding ways and means to increase oil recovery, especially to the constant use of microbiological methods. Oil is an important source of energy and chemical raw materials. Its reserves are limited and irreplaceable. The existing methods allow us to extract up to 40-60% of geological oil reserves in the development of oil fields. One of the most urgent tasks is to create the most effective methods to increase oil production in the developed fields. Microbiological methods used to increase oil production attract attention with their high efficiency and environmental safety, low capital intensity. In biotechnology, additional oil displacement occurs to a certain extent, these mechanisms provide both physical and chemical methods, but since the metabolites of microorganisms are formed directly in the plate openings, their impact efficiency is higher. It is impossible to master these methods without taking into account the microbiological and physico–chemical conditions in oil plates.

50th anniversary of Numerical Weather Prediction (NWP) in the UK

50th anniversary of Numerical Weather Prediction (<scp>NWP</scp>) in the <scp>UK</scp>

Today's Forecast: Higher Thinking With a Chance of Conceptual Growth

Weather has all the characteristics of a motivating, authentic subject: Everybody has an interest in it and strong opinions about it. This interest has provided a way to tie science to a meaningful learning activity in an introductory meteorology course for nonscience students. The pedagogical foundation of such a course is that it is more important for students in science classes to learn to think like scientists than to accumulate facts; weather forecasting allows them to progressively apply their knowledge about the atmosphere by hypothesizing the next day's weather. By forecasting tomorrow's weather repeatedly throughout the course, students are given the opportunity to link what they are learning in class to a topic to which they all relate.

Bias‐corrected short‐range ensemble forecasts of near surface variables

AbstractA multimodel short‐range ensemble forecasting system created as part of a National Oceanic and Atmospheric Administration program on improved high temperature forecasting during the summer of 2003 is evaluated. Results from this short‐range ensemble system indicate that using the past complete 12 days of forecasts to bias correct today's forecast yields ensemble mean forecasts of 2‐m temperature, 2‐m dewpoint temperature, and 10‐m wind speed that are competitive with or better than those available from any of the model output statistics presently generated operationally in the United States. However, the bias‐corrected ensemble system provides more than just the ensemble mean forecast. Probabilities produced by this system are skilful and reliable, and have been found to be valuable when evaluated in a cost‐loss model. The ensemble appears to provide better guidance for more unlikely events, such as very warm temperatures, that likely have the greatest economic significance. Industries that are sensitive to the weather, such as power companies, transportation and agriculture, may benefit from the probability information provided. Thus, it is possible to develop post‐processing for short‐range ensemble forecasting systems that is competitive with or better than traditional post‐processing techniques, thereby allowing the rapid production of useful and accurate guidance forecasts of many near surface variables. Copyright © 2005 Royal Meteorological Society

Conditional Probabilistic Population Forecasting

Summary Since policy‐makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy‐makers because it allows them to answer “what if” type questions properly when outcomes are uncertain. The second is a new category that we call “future jump‐off date forecasts”. Future jump‐off date forecasts are valuable because they show policy‐makers the likelihood that crucial features of today's forecasts will also be present in forecasts made in the future.

IT MUST BE THE WEATHER: Today's Forecast: Again, Mainly Capitalism

Previous articleNext article No AccessIT MUST BE THE WEATHER: Today's Forecast: Again, Mainly CapitalismShep SteinerShep Steiner Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Afterall Volume 22000 Published by Central Saint Martins, University of the Arts London Article DOIhttps://doi.org/10.1086/aft.2.20711405 Views: 30Total views on this site © 1999 Central Saint Martins College of Art & DesignPDF download Crossref reports no articles citing this article.

Numerical Weather Prediction in Daily Use

The last 10 years have seen a revolutionary change in the way weather forecasts are made. The basis for today's forecasts is a numerical calculation of the evolution of the energy distribution and motions in a physical model of the atmosphere. The benefits of this change have affected all types of weather forecasting. The substantial benefits to aviation are well established. The benefits to forecasts for the general public can't be conclusively documented but are strongly suggested. Our present limitations are mainly due to insufficient completeness of our atmospheric models. The removal of some of these deficiencies appears to be a relatively straightforward task. Other problems, particularly those of phase change of water, are more difficult. The eventual limitation to the prediction of atmospheric motions appears to be the supply of data describing the initial conditions, but I can safely say that solution of the other problems will require more than just a few years.