Climatological Data PDF Download
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Author:
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Category : Iowa
Languages : en
Pages : 472
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Author:
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ISBN:
Category : Iowa
Languages : en
Pages : 472
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Author: United States. Environmental Data Service
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 1028
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Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 734
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Book Description
Collection of the monthly climatological reports of the United States by state or region, with monthly and annual national summaries.
Author: United States. Environmental Data Service
Publisher:
ISBN:
Category : Hawaii
Languages : en
Pages : 430
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Author:
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ISBN:
Category : Hawaii
Languages : en
Pages :
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Author: United States. Weather Bureau
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 276
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Author: Abdelwaheb Hannachi
Publisher: Springer Nature
ISBN: 3030670732
Category : Science
Languages : en
Pages : 607
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Book Description
Advances in computer power and observing systems has led to the generation and accumulation of large scale weather & climate data begging for exploration and analysis. Pattern Identification and Data Mining in Weather and Climate presents, from different perspectives, most available, novel and conventional, approaches used to analyze multivariate time series in climate science to identify patterns of variability, teleconnections, and reduce dimensionality. The book discusses different methods to identify patterns of spatiotemporal fields. The book also presents machine learning with a particular focus on the main methods used in climate science. Applications to atmospheric and oceanographic data are also presented and discussed in most chapters. To help guide students and beginners in the field of weather & climate data analysis, basic Matlab skeleton codes are given is some chapters, complemented with a list of software links toward the end of the text. A number of technical appendices are also provided, making the text particularly suitable for didactic purposes. The topic of EOFs and associated pattern identification in space-time data sets has gone through an extraordinary fast development, both in terms of new insights and the breadth of applications. We welcome this text by Abdel Hannachi who not only has a deep insight in the field but has himself made several contributions to new developments in the last 15 years. - Huug van den Dool, Climate Prediction Center, NCEP, College Park, MD, U.S.A. Now that weather and climate science is producing ever larger and richer data sets, the topic of pattern extraction and interpretation has become an essential part. This book provides an up to date overview of the latest techniques and developments in this area. - Maarten Ambaum, Department of Meteorology, University of Reading, U.K. This nicely and expertly written book covers a lot of ground, ranging from classical linear pattern identification techniques to more modern machine learning, illustrated with examples from weather & climate science. It will be very valuable both as a tutorial for graduate and postgraduate students and as a reference text for researchers and practitioners in the field. - Frank Kwasniok, College of Engineering, University of Exeter, U.K.
Author: Antonio Navarra
Publisher: Springer Science & Business Media
ISBN: 9048137020
Category : Science
Languages : en
Pages : 151
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Book Description
Climatology and meteorology have basically been a descriptive science until it became possible to use numerical models, but it is crucial to the success of the strategy that the model must be a good representation of the real climate system of the Earth. Models are required to reproduce not only the mean properties of climate, but also its variability and the strong spatial relations between climate variability in geographically diverse regions. Quantitative techniques were developed to explore the climate variability and its relations between different geographical locations. Methods were borrowed from descriptive statistics, where they were developed to analyze variance of related observations-variable pairs, or to identify unknown relations between variables. A Guide to Empirical Orthogonal Functions for Climate Data Analysis uses a different approach, trying to introduce the reader to a practical application of the methods, including data sets from climate simulations and MATLAB codes for the algorithms. All pictures and examples used in the book may be reproduced by using the data sets and the routines available in the book . Though the main thrust of the book is for climatological examples, the treatment is sufficiently general that the discussion is also useful for students and practitioners in other fields. Supplementary datasets are available via http://extra.springer.com
Author:
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Category : Government publications
Languages : en
Pages : 1268
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Author: United States. Superintendent of Documents
Publisher:
ISBN:
Category : Government publications
Languages : en
Pages : 458
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Book Description
