Download or read book Gringorten s Stochastic Model for Climatological Predictions written by U.S. Army Natick Laboratories. Earth Sciences Division and published by . This book was released on 1967 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Physics and Climate Modelling written by Tim Palmer and published by Cambridge University Press. This book was released on 2018-03-01 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to promote the use of stochastic, or random, processes to understand, model and predict our climate system. One of the most important applications of this technique is in the representation of comprehensive climate models of processes which, although crucial, are too small or fast to be explicitly modeled. The book shows how stochastic methods can lead to improvements in climate simulation and prediction, compared with more conventional bulk-formula parameterization procedures. Beginning with expositions of the relevant mathematical theory, the book moves on to describe numerous practical applications. It covers the complete range of time scales of climate variability, from seasonal to decadal, centennial, and millennial. With contributions from leading experts in climate physics, this book is invaluable to anyone working on climate models, including graduate students and researchers in the atmospheric and oceanic sciences, numerical weather forecasting, climate prediction, climate modeling, and climate change.
Download or read book Stochastic Climate Models written by Peter Imkeller and published by Springer Science & Business Media. This book was released on 2001 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: A collection of articles written by mathematicians and physicists, designed to describe the state of the art in climate models with stochastic input. Mathematicians will benefit from a survey of simple models, while physicists will encounter mathematically relevant techniques at work.
Download or read book Stochastic Climate Theory written by Serguei G. Dobrovolski and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author describes the stochastic (probabilistic) approach to the study of changes in the climate system. Climatic data and theoretical considerations suggest that a large part of climatic variation/variability has a random nature and can be analyzed using the theory of stochastic processes. This work summarizes the results of processing existing records of climatic parameters as well as appropriate theories: from the theory of random processes (based on the results of Kolmogorov and Yaglom) and Hasselmann's "stochastic climate model theory" to recently obtained results.
Download or read book The Stochastic Seasonal to Interannual Prediction System written by Lenin Del Rio Amador and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This thesis proposes the new Stochastic Seasonal to Interannual Prediction System (StocSIPS) model of the atmospheric temperature in the macroweather regime, i.e. time scales longer than the lifetime of planetary sized structures (≈10 days). StocSIPS is stochastic and respects two conservation principles: energy balance and scale invariance. The scale-invariance of the fluctuations implies the existence a huge memory in the system that can be exploited for macroweather forecasts and the low intermittency justifies using well-established (Gaussian) techniques. Here, we present StocSIPS, discuss its statistics, use it to perform long-term forecasts and compare it with forecasts from conventional general circulation models (GCMs).GCMs are initial value problems and each has its own climate, requiring complex post-processing correction schemes. In comparison, StocSIPS is a past value problem based on real world historical data that effectively forces predictions to converge to the real-world climate. It extracts the internal variability (weather noise) directly from past data and does not suffer from model drift. It models the temperature as the high-frequency limit of the (fractional) energy balance equation which governs radiative equilibrium processes when the relevant equilibrium relaxation processes are power law, rather than exponential.StocSIPS was first developed as an improvement over the previous ScaLIng Macroweather Model (SLIMM) for monthly and seasonal forecast of globally averaged temperature. The validity of the model is checked through statistical testing and by comparing the theoretically expected skill scores with actual skill scores obtained from hindcast verification. A detailed comparison with the Canadian Seasonal to Interannual Prediction System (CanSIPS) shows that StocSIPS is just as accurate for one-month forecasts, but significantly more accurate for longer lead times.The scaling symmetry, which is the basis of StocSIPS, also holds at the regional level (here, 2.5°×2.5°). This allows applications for predicting the spatially resolved temperature field by treating each grid point as an independent time series. We obtain monthly and seasonal predictions of the surface temperature and show some preliminary comparison with multi-model ensemble (MME) GCM results. For one month lead times, this single pixel based stochastic model shows skill scores similar to the much more complex conventional (GCM) deterministic models.To explore the possibility of improving the predictions at a given place using past temperatures from other grid points, we developed the comprehensive multivariate version of StocSIPS (m-StocSIPS) as a full space-time process. m-StocSIPS allows to show that the regional memory-based StocSIPS forecasts are optimal in this stochastic framework. It also helps to untangle the usually complicated relationship between correlations and causality thanks to the precise notion of Granger causality. For a given position, past information from other locations cannot be used to improve on the forecast obtained as an optimal linear combination of past data: those correlations "were already used" to build the past at that position. By using m-StocSIPS we are able to reproduce the empirical cross-correlation structure of the temperature field over a wide range of time lags. This is made more convincing by making simulations that display numerous realistic but emergent model properties including spatial teleconnection networks and realistic El Niño patterns and indices"--
Download or read book Seasonal Climate Forecasting and Managing Risk written by Alberto Troccoli and published by Springer Science & Business Media. This book was released on 2008-02-22 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally formed around a set of lectures presented at a NATO Advanced Study Institute (ASI), this book has grown to become organised and presented rather more as a textbook than as a standard "collection of proceedings". This therefore is the first unified reference ‘textbook’ in seasonal to interannual climate predictions and their practical uses. Written by some of the world’s leading experts, the book covers a rapidly-developing science of prime social concern.
Download or read book A Stochastic Model of the Frequency and Duration of Weather Events written by Irving I. Gringorten and published by . This book was released on 1967 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: A simple Markov chain has been demonstrated to be a potentially useful device for making estimates of the frequencies and durations, from several hours to several weeks, of a large variety of weather events. In order to answer the practical questions, it was found necessary to simulate probability distributions by a Monte Carlo exercise. The resulting eight sets of charts have wide applicability. Stochastics, model, duration, climatology, probabilities, and frequency distributions.--Abstract/Keywords.
Download or read book Climate Change Modeling Methodology written by Philip J. Rasch and published by Springer Science & Business Media. This book was released on 2012-12-09 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Earth's average temperature has risen by 1.4°F over the past century, and computer models project that it will rise much more over the next hundred years, with significant impacts on weather, climate, and human society. Many climate scientists attribute these increases to the build up of greenhouse gases produced by the burning of fossil fuels and to the anthropogenic production of short-lived climate pollutants. Climate Change Modeling Methodologies: Selected Entries from the Encyclopaedia of Sustainability Science and Technology provides readers with an introduction to the tools and analysis techniques used by climate change scientists to interpret the role of these forcing agents on climate. Readers will also gain a deeper understanding of the strengths and weaknesses of these models and how to test and assess them. The contributions include a glossary of key terms and a concise definition of the subject for each topic, as well as recommendations for sources of more detailed information.
Download or read book New techniques for improving climate models predictions and projections written by Matthew Collins and published by Frontiers Media SA. This book was released on 2022-01-24 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Statistics in Climatology written by Ilya Polyak and published by Oxford University Press. This book was released on 1996-08-01 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific descriptions of the climate have traditionally been based on the study of average meteorological values taken from different positions around the world. In recent years however it has become apparent that these averages should be considered with other statistics that ultimately characterize spatial and temporal variability. This book is designed to meet that need. It is based on a course in computational statistics taught by the author that arose from a variety of projects on the design and development of software for the study of climate change, using statistics and methods of random functions.
Download or read book Prediction of Interannual Climate Variations written by J. Shukla and published by Springer. This book was released on 1993 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: It has been known for some time that the behavior of the short-term fluctuations of the earth's atmosphere resembles that of a chaotic non-linear dynamical system, and that the day-to-day weather cannot be predicted beyond a few weeks. However, it has also been found that the interactions of the atmosphere with the underlying oceans and the land surfaces can produce fluctuations whose time scales are much longer than the limits of deterministic prediction of weather. It is, therefore, natural to ask whether it is possible that the seasonal and longer time averages of climate fluctuations can be predicted with sufficient skill to be beneficial for social and economic applications, even though the details of the day-to-day weather cannot be predicted beyond a few weeks. The main objective of the workshop was to address this question by assessing the current state of knowledge on predictability of seasonal and interannual climate variability and to investigate various possibilities for its prediction.
Download or read book Demystifying Climate Models written by Andrew Gettelman and published by Springer. This book was released on 2018-04-22 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demystifies the models we use to simulate present and future climates, allowing readers to better understand how to use climate model results. In order to predict the future trajectory of the Earth’s climate, climate-system simulation models are necessary. When and how do we trust climate model predictions? The book offers a framework for answering this question. It provides readers with a basic primer on climate and climate change, and offers non-technical explanations for how climate models are constructed, why they are uncertain, and what level of confidence we should place in them. It presents current results and the key uncertainties concerning them. Uncertainty is not a weakness but understanding uncertainty is a strength and a key part of using any model, including climate models. Case studies of how climate model output has been used and how it might be used in the future are provided. The ultimate goal of this book is to promote a better understanding of the structure and uncertainties of climate models among users, including scientists, engineers and policymakers.
Download or read book Stochastic Climate Theory written by Serguei Dobrovolski and published by . This book was released on 2014-01-15 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Objective Prediction of Mesoscale Variations of Sensor Equivalent Visibility During Advective Situations written by Donald A. Chisholm and published by . This book was released on 1976 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Hanscom AFB mesonetwork was established to examine the potential forecasting benefits to be derived from automated mesoscale observations. Experiments were set up to evaluate three objective procedures for prediction short-period (15 to 60 min) fluctuations in sensor equivalent visibility against a specialized conditional climatology model. The procedures evaluated were: a translation technique based on vectors determined by tracking mesoscale disturbances objectively, an advection technique which utilized forecast wind fields from a limited-area fine-mesh model, and a simple area-averaged trend technique. Data from 24 episodes of reduced visibility gathered during the 1972-74 period of mesonetwork operations were used to evaluate the techniques. The translation and area-averaged trend technique yielded positive skill relative to the conditional climatology model, while the advection technique did not. Although there were episodes in which the spatial selectivity of the translation technique yielded significant improvements, the trend technique was an overall better forecast indicator, especially when one considers its relative simplicity. (Author).
Download or read book Investigation of the Application of Stochastic Modeling to Climate Prediction written by J. A. Laurmann and published by . This book was released on 1974 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report summarizes preliminary work undertaken inconsideration of the use of stochastic approaches to climate modeling. It includes a survey of the difficulties involved with representation of atmospheric dynamics for climate questions and some recommendations for directions of research needed to deal with them. The results of two specific analytic studies are included. The first demonstrates that the complete stochastic formulation in terms of an infinite hierarchy of moment equations is directly applicable to time-averaged as well as instantaneous representations of the dependent variables. The second analytic result presents a methodology for time (and space) truncation of the deterministic predictive part of the equations of atmospheric motion that can considerably reduce computation times for climatic (and weather) models.
Download or read book Annotated Bibliography on Hydrology and Sedimentation 1966 1968 United States and Canada written by Engineering-Science, Inc and published by . This book was released on 1970 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Meteorological and Geoastrophysical Abstracts written by and published by . This book was released on 1986 with total page 968 pages. Available in PDF, EPUB and Kindle. Book excerpt:
