Monthly Climatic Data for World by Continents

Monthly Climatic Data for World by Continents PDF Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 60

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Monthly Climatic Data for World by Continents

Monthly Climatic Data for World by Continents PDF Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 60

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Book Description


Monthly Climatic Data for World

Monthly Climatic Data for World PDF Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 814

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Monthly Climatic Data for World

Monthly Climatic Data for World PDF Author: United States. Environmental Data Service
Publisher:
ISBN:
Category : Climatology
Languages : en
Pages : 830

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World Climatic Data: Africa

World Climatic Data: Africa PDF Author: Frederick L. Wernstedt
Publisher:
ISBN:
Category : Climatology
Languages : en
Pages : 220

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Climatological Data

Climatological Data PDF Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 454

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Climatological Data

Climatological Data PDF Author: United States. Environmental Data Service
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 734

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A Vast Machine

A Vast Machine PDF Author: Paul N. Edwards
Publisher: MIT Press
ISBN: 0262290715
Category : Technology & Engineering
Languages : en
Pages : 547

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Book Description
The science behind global warming, and its history: how scientists learned to understand the atmosphere, to measure it, to trace its past, and to model its future. Global warming skeptics often fall back on the argument that the scientific case for global warming is all model predictions, nothing but simulation; they warn us that we need to wait for real data, “sound science.” In A Vast Machine Paul Edwards has news for these skeptics: without models, there are no data. Today, no collection of signals or observations—even from satellites, which can “see” the whole planet with a single instrument—becomes global in time and space without passing through a series of data models. Everything we know about the world's climate we know through models. Edwards offers an engaging and innovative history of how scientists learned to understand the atmosphere—to measure it, trace its past, and model its future.

Climatological Data for the United States by Sections

Climatological Data for the United States by Sections PDF Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 994

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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.

Monthly Record of Meteorological Observations in Canada, Newfoundland and Bermuda

Monthly Record of Meteorological Observations in Canada, Newfoundland and Bermuda PDF Author: Canada. Atmospheric Environment Service
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 1092

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Book Description


Big Data Mining for Climate Change

Big Data Mining for Climate Change PDF Author: Zhihua Zhang
Publisher: Elsevier
ISBN: 0128187034
Category : Science
Languages : en
Pages : 344

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Book Description
Climate change mechanisms, impacts, risks, mitigation, adaption, and governance are widely recognized as the biggest, most interconnected problem facing humanity. Big Data Mining for Climate Change addresses one of the fundamental issues facing scientists of climate or the environment: how to manage the vast amount of information available and analyse it. The resulting integrated and interdisciplinary big data mining approaches are emerging, partially with the help of the United Nation's big data climate challenge, some of which are recommended widely as new approaches for climate change research. Big Data Mining for Climate Change delivers a rich understanding of climate-related big data techniques and highlights how to navigate huge amount of climate data and resources available using big data applications. It guides future directions and will boom big-data-driven researches on modeling, diagnosing and predicting climate change and mitigating related impacts. This book mainly focuses on climate network models, deep learning techniques for climate dynamics, automated feature extraction of climate variability, and sparsification of big climate data. It also includes a revelatory exploration of big-data-driven low-carbon economy and management. Its content provides cutting-edge knowledge for scientists and advanced students studying climate change from various disciplines, including atmospheric, oceanic and environmental sciences; geography, ecology, energy, economics, management, engineering, and public policy.