R and Python for Oceanographers

R and Python for Oceanographers
Author: Hakan Alyuruk
Publsiher: Elsevier
Total Pages: 186
Release: 2019-06-09
ISBN 10: 0128134925
ISBN 13: 9780128134924
Language: EN, FR, DE, ES & NL

R and Python for Oceanographers Book Review:

R and Python for Oceanographers: A Practical Guide with Applications describes the uses of scientific Python packages and R in oceanographic data analysis, including both script codes and graphic outputs. Each chapter begins with theoretical background that is followed by step-by-step examples of software applications, including scripts, graphics, tables and practical exercises for better understanding of the subject. Examples include frequently used data analysis approaches in physical and chemical oceanography, but also contain topics on data import/export and GIS mapping. The examples seen in book provide uses of the latest versions of Python and R libraries. Presents much needed oceanographic data analysis approaches to chemical and physical oceanography Includes examples with software applications (based on Python and R), including free software for the analysis of oceanographic data Provides guidance on how to get started, along with guidance on example code and output

R and Python for Oceanographers

R and Python for Oceanographers
Author: Hakan Alyuruk,Murat Gunduz
Publsiher: Elsevier
Total Pages: 300
Release: 2019-06-15
ISBN 10: 9780128134917
ISBN 13: 0128134917
Language: EN, FR, DE, ES & NL

R and Python for Oceanographers Book Review:

R and Python for Oceanographers: A Practical Guide with Applications describes the uses of scientific Python packages and R in oceanographic data analysis, including both script codes and graphic outputs. Each chapter begins with theoretical background that is followed by step-by-step examples of software applications, including scripts, graphics, tables and practical exercises for better understanding of the subject. Examples include frequently used data analysis approaches in physical and chemical oceanography, but also contain topics on data import/export and GIS mapping. The examples seen in book provide uses of the latest versions of Python and R libraries. Presents much needed oceanographic data analysis approaches to chemical and physical oceanography Includes examples with software applications (based on Python and R), including free software for the analysis of oceanographic data Provides guidance on how to get started, along with guidance on example code and output

Oceanographic Analysis with R

Oceanographic Analysis with R
Author: Dan E. Kelley
Publsiher: Springer
Total Pages: 290
Release: 2018-10-17
ISBN 10: 1493988441
ISBN 13: 9781493988440
Language: EN, FR, DE, ES & NL

Oceanographic Analysis with R Book Review:

This book presents the R software environment as a key tool for oceanographic computations and provides a rationale for using R over the more widely-used tools of the field such as MATLAB. Kelley provides a general introduction to R before introducing the ‘oce’ package. This package greatly simplifies oceanographic analysis by handling the details of discipline-specific file formats, calculations, and plots. Designed for real-world application and developed with open-source protocols, oce supports a broad range of practical work. Generic functions take care of general operations such as subsetting and plotting data, while specialized functions address more specific tasks such as tidal decomposition, hydrographic analysis, and ADCP coordinate transformation. In addition, the package makes it easy to document work, because its functions automatically update processing logs stored within its data objects. Kelley teaches key R functions using classic examples from the history of oceanography, specifically the work of Alfred Redfield, Gordon Riley, J. Tuzo Wilson, and Walter Munk. Acknowledging the pervasive popularity of MATLAB, the book provides advice to users who would like to switch to R. Including a suite of real-life applications and over 100 exercises and solutions, the treatment is ideal for oceanographers, technicians, and students who want to add R to their list of tools for oceanographic analysis.

Oceanography and Coastal Informatics Breakthroughs in Research and Practice

Oceanography and Coastal Informatics  Breakthroughs in Research and Practice
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 469
Release: 2018-11-02
ISBN 10: 1522573097
ISBN 13: 9781522573098
Language: EN, FR, DE, ES & NL

Oceanography and Coastal Informatics Breakthroughs in Research and Practice Book Review:

To date, a vast amount of the world’s oceans remains uncharted. With water covering more than 70 percent of the Earth’s surface, maritime and oceanographic exploration and research is vital. Oceanography and Coastal Informatics: Breakthroughs in Research and Practice is a critical source of academic knowledge centered on technologies, methodologies, and practices related to the biological and physical aspects of the ocean and coastal environments. This publication is divided into four sections: climate change and environmental concerns; data analysis and management; fisheries management and ecology; and GIS, geospatial analysis, and localization. This publication is an ideal reference source for oceanographers, marine and maritime professionals, researchers, and scholars interested in current research on various aspects of oceanography and coastal informatics.

A Hands On Introduction to Using Python in the Atmospheric and Oceanic Sciences

A Hands On Introduction to Using Python in the Atmospheric and Oceanic Sciences
Author: Johnny Wei-Bing Lin
Publsiher: Lulu.com
Total Pages: 186
Release: 2012
ISBN 10: 130007616X
ISBN 13: 9781300076162
Language: EN, FR, DE, ES & NL

A Hands On Introduction to Using Python in the Atmospheric and Oceanic Sciences Book Review:

This book is a mini-course for researchers in the atmospheric and oceanic sciences. "We assume readers will already know the basics of programming... in some other language." - Back cover.

Python and R for the Modern Data Scientist

Python and R for the Modern Data Scientist
Author: Rick J. Scavetta,Boyan Angelov
Publsiher: "O'Reilly Media, Inc."
Total Pages: 198
Release: 2021-06-22
ISBN 10: 1492093378
ISBN 13: 9781492093374
Language: EN, FR, DE, ES & NL

Python and R for the Modern Data Scientist Book Review:

Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist. Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a case study that demonstrates ways to use these languages together

Chemical Oceanography

Chemical Oceanography
Author: Steven R. Emerson,Roberta C. Hamme
Publsiher: Cambridge University Press
Total Pages: 500
Release: 2022-03-31
ISBN 10: 1107179890
ISBN 13: 9781107179899
Language: EN, FR, DE, ES & NL

Chemical Oceanography Book Review:

A broad, clear introductory textbook on chemical oceanography for undergraduate and graduate students and a reference text for researchers.

Time Series Data Analysis in Oceanography

Time Series Data Analysis in Oceanography
Author: Chunyan Li
Publsiher: Cambridge University Press
Total Pages: 300
Release: 2022-04-30
ISBN 10: 1108474276
ISBN 13: 9781108474276
Language: EN, FR, DE, ES & NL

Time Series Data Analysis in Oceanography Book Review:

Textbook for students and researchers in oceanography and Earth science on theory and practice of time series analysis using MATLAB.

Python for R Users

Python for R Users
Author: Ajay Ohri
Publsiher: John Wiley & Sons
Total Pages: 368
Release: 2017-11-13
ISBN 10: 1119126762
ISBN 13: 9781119126768
Language: EN, FR, DE, ES & NL

Python for R Users Book Review:

The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to code in Python and Python users to program in R. Short on theory and long on actionable analytics, it provides readers with a detailed comparative introduction and overview of both languages and features concise tutorials with command-by-command translations—complete with sample code—of R to Python and Python to R. Following an introduction to both languages, the author cuts to the chase with step-by-step coverage of the full range of pertinent programming features and functions, including data input, data inspection/data quality, data analysis, and data visualization. Statistical modeling, machine learning, and data mining—including supervised and unsupervised data mining methods—are treated in detail, as are time series forecasting, text mining, and natural language processing. • Features a quick-learning format with concise tutorials and actionable analytics • Provides command-by-command translations of R to Python and vice versa • Incorporates Python and R code throughout to make it easier for readers to compare and contrast features in both languages • Offers numerous comparative examples and applications in both programming languages • Designed for use for practitioners and students that know one language and want to learn the other • Supplies slides useful for teaching and learning either software on a companion website Python for R Users: A Data Science Approach is a valuable working resource for computer scientists and data scientists that know R and would like to learn Python or are familiar with Python and want to learn R. It also functions as textbook for students of computer science and statistics. A. Ohri is the founder of Decisionstats.com and currently works as a senior data scientist. He has advised multiple startups in analytics off-shoring, analytics services, and analytics education, as well as using social media to enhance buzz for analytics products. Mr. Ohri's research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces for cloud computing, investigating climate change and knowledge flows. His other books include R for Business Analytics and R for Cloud Computing.

Climate Mathematics

Climate Mathematics
Author: Samuel S. P. Shen,Richard C. J. Somerville
Publsiher: Cambridge University Press
Total Pages: 456
Release: 2019-09-30
ISBN 10: 1108476872
ISBN 13: 9781108476874
Language: EN, FR, DE, ES & NL

Climate Mathematics Book Review:

Presents the core mathematics, statistics, and programming skills needed for modern climate science courses, with online teaching materials.

Oceanography and Marine Biology

Oceanography and Marine Biology
Author: S. J. Hawkins,A. J. Evans,A.C. Dale,L. B. Firth,I. P. Smith
Publsiher: CRC Press
Total Pages: 510
Release: 2018-11-21
ISBN 10: 0429845758
ISBN 13: 9780429845758
Language: EN, FR, DE, ES & NL

Oceanography and Marine Biology Book Review:

Key features: Explores the implications of long-term climate change for biogeography and ecological processes in the Southern Ocean Updates knowledge of symbiotic polychaetes in light of the last 20 years of research Considers the adaptions and environments of Antarctic marine biodiversity Examines the false hope of cetacean conservation Reviews work in Mediterranean venting systems releasing carbon dioxide as a model for understanding ocean acidification Looks at the impacts and environmental risks of oil spills of marine invertebrates, algae and seagrass Oceanography and Marine Biology: An Annual Review remains one of the most cited sources in marine science and oceanography. The ever increasing interest in work in oceanography and marine biology and its relevance to global environmental issues, especially global climate change and its impacts, creates a demand for authoritative reviews summarizing the results of recent research. OMBAR has catered to this demand since its foundation more than 50 years ago. Following the favourable reception and complimentary reviews accorded to all the volumes, Volume 56 continues to regard the marine sciences—with all their various aspects—as a unity. Physical, chemical, and biological aspects of marine science are dealt with by experts actively engaged in these fields, and every chapter is peer-reviewed by other experts working actively in the specific areas of interest. The series is an essential reference text for researchers and students in all fields of marine science and related subjects, and it finds a place in libraries of universities, marine laboratories, research institutes and government departments. It is consistently among the highest ranking series in terms of impact factor in the marine biology category of the citation indices compiled by the Institute for Scientific Information/Web of Science. Two chapters are available to read Open Access on our Routledge website at https://www.routledge.com/9781138318625

Ocean Circulation in Three Dimensions

Ocean Circulation in Three Dimensions
Author: Barry A. Klinger,Thomas W. N. Haine
Publsiher: Cambridge University Press
Total Pages: 494
Release: 2019-03-31
ISBN 10: 0521768438
ISBN 13: 9780521768436
Language: EN, FR, DE, ES & NL

Ocean Circulation in Three Dimensions Book Review:

An innovative survey of large-scale ocean circulation that links observations, conceptual models, numerical models, and theories.

Marketing Data Science

Marketing Data Science
Author: Thomas W. Miller
Publsiher: FT Press
Total Pages: 225
Release: 2015-05-02
ISBN 10: 0133887340
ISBN 13: 9780133887341
Language: EN, FR, DE, ES & NL

Marketing Data Science Book Review:

Now , a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.

Oceanographic and Marine Cross Domain Data Management for Sustainable Development

Oceanographic and Marine Cross Domain Data Management for Sustainable Development
Author: Diviacco, Paolo,Leadbetter, Adam,Glaves, Helen
Publsiher: IGI Global
Total Pages: 425
Release: 2016-09-23
ISBN 10: 1522507019
ISBN 13: 9781522507017
Language: EN, FR, DE, ES & NL

Oceanographic and Marine Cross Domain Data Management for Sustainable Development Book Review:

As human activity makes a greater impact on the environment, sustainability becomes an increasingly imperative goal. With the assistance of current technological innovations, environmental systems can be better preserved. Oceanographic and Marine Cross-Domain Data Management for Sustainable Development is a pivotal resource for the latest research on the collection of environmental data for sustainability initiatives and the associate challenges with this data acquisition. Highlighting various technological, scientific, semantic, and semiotic perspectives, this book is ideally designed for researchers, technology developers, practitioners, students, and professionals in the field of environmental science and technology.

Deep Learning with Python

Deep Learning with Python
Author: Francois Chollet
Publsiher: Simon and Schuster
Total Pages: 384
Release: 2017-11-30
ISBN 10: 1638352046
ISBN 13: 9781638352044
Language: EN, FR, DE, ES & NL

Deep Learning with Python Book Review:

Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

Mastering Python Scientific Computing

Mastering Python Scientific Computing
Author: Hemant Kumar Mehta
Publsiher: Packt Publishing Ltd
Total Pages: 300
Release: 2015-09-23
ISBN 10: 1783288833
ISBN 13: 9781783288830
Language: EN, FR, DE, ES & NL

Mastering Python Scientific Computing Book Review:

A complete guide for Python programmers to master scientific computing using Python APIs and tools About This Book The basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered. Most of the Python APIs and tools used in scientific computing are discussed in detail The concepts are discussed with suitable example programs Who This Book Is For If you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming. What You Will Learn Fundamentals and components of scientific computing Scientific computing data management Performing numerical computing using NumPy and SciPy Concepts and programming for symbolic computing using SymPy Using the plotting library matplotlib for data visualization Data analysis and visualization using Pandas, matplotlib, and IPython Performing parallel and high performance computing Real-life case studies and best practices of scientific computing In Detail In today's world, along with theoretical and experimental work, scientific computing has become an important part of scientific disciplines. Numerical calculations, simulations and computer modeling in this day and age form the vast majority of both experimental and theoretical papers. In the scientific method, replication and reproducibility are two important contributing factors. A complete and concrete scientific result should be reproducible and replicable. Python is suitable for scientific computing. A large community of users, plenty of help and documentation, a large collection of scientific libraries and environments, great performance, and good support makes Python a great choice for scientific computing. At present Python is among the top choices for developing scientific workflow and the book targets existing Python developers to master this domain using Python. The main things to learn in the book are the concept of scientific workflow, managing scientific workflow data and performing computation on this data using Python. The book discusses NumPy, SciPy, SymPy, matplotlib, Pandas and IPython with several example programs. Style and approach This book follows a hands-on approach to explain the complex concepts related to scientific computing. It details various APIs using appropriate examples.

The Data Science Handbook

The Data Science Handbook
Author: Field Cady
Publsiher: John Wiley & Sons
Total Pages: 416
Release: 2017-02-28
ISBN 10: 1119092949
ISBN 13: 9781119092940
Language: EN, FR, DE, ES & NL

The Data Science Handbook Book Review:

A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features: • Extensive sample code and tutorials using Python™ along with its technical libraries • Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems • Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity • A wide variety of case studies from industry • Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set. FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon.

Algorithms For Dummies

Algorithms For Dummies
Author: John Paul Mueller,Luca Massaron
Publsiher: John Wiley & Sons
Total Pages: 432
Release: 2017-04-11
ISBN 10: 1119330521
ISBN 13: 9781119330523
Language: EN, FR, DE, ES & NL

Algorithms For Dummies Book Review:

Discover how algorithms shape and impact our digital world All data, big or small, starts with algorithms. Algorithms are mathematical equations that determine what we see—based on our likes, dislikes, queries, views, interests, relationships, and more—online. They are, in a sense, the electronic gatekeepers to our digital, as well as our physical, world. This book demystifies the subject of algorithms so you can understand how important they are business and scientific decision making. Algorithms for Dummies is a clear and concise primer for everyday people who are interested in algorithms and how they impact our digital lives. Based on the fact that we already live in a world where algorithms are behind most of the technology we use, this book offers eye-opening information on the pervasiveness and importance of this mathematical science—how it plays out in our everyday digestion of news and entertainment, as well as in its influence on our social interactions and consumerism. Readers even learn how to program an algorithm using Python! Become well-versed in the major areas comprising algorithms Examine the incredible history behind algorithms Get familiar with real-world applications of problem-solving procedures Experience hands-on development of an algorithm from start to finish with Python If you have a nagging curiosity about why an ad for that hammock you checked out on Amazon is appearing on your Facebook page, you'll find Algorithm for Dummies to be an enlightening introduction to this integral realm of math, science, and business.

Evaluating Climate Change Impacts

Evaluating Climate Change Impacts
Author: Vyacheslav Lyubchich,Yulia Gel,K. Halimeda Kilbourne,Thomas James Miller,Nathaniel K. Newlands,A. Smith
Publsiher: CRC Press
Total Pages: 382
Release: 2020-10-07
ISBN 10: 1351190814
ISBN 13: 9781351190817
Language: EN, FR, DE, ES & NL

Evaluating Climate Change Impacts Book Review:

Evaluating Climate Change Impacts discusses assessing and quantifying climate change and its impacts from a multi-faceted perspective of ecosystem, social, and infrastructure resilience, given through a lens of statistics and data science. It provides a multi-disciplinary view on the implications of climate variability and shows how the new data science paradigm can help us to mitigate climate-induced risk and to enhance climate adaptation strategies. This book consists of chapters solicited from leading topical experts and presents their perspectives on climate change effects in two general areas: natural ecosystems and socio-economic impacts. The chapters unveil topics of atmospheric circulation, climate modeling, and long-term prediction; approach the problems of increasing frequency of extreme events, sea level rise, and forest fires, as well as economic losses, analysis of climate impacts for insurance, agriculture, fisheries, and electric and transport infrastructures. The readers will be exposed to the current research using a variety of methods from physical modeling, statistics, and machine learning, including the global circulation models (GCM) and ocean models, statistical generalized additive models (GAM) and generalized linear models (GLM), state space and graphical models, causality networks, Bayesian ensembles, a variety of index methods and statistical tests, and machine learning methods. The reader will learn about data from various sources, including GCM and ocean model outputs, satellite observations, and data collected by different agencies and research units. Many of the chapters provide references to open source software R and Python code that are available for implementing the methods.

Sea Salt Aerosol Production

Sea Salt Aerosol Production
Author: Ernie R. Lewis,Ernie R.. Lewis,R. Lewis,Stephen E. Schwartz
Publsiher: American Geophysical Union
Total Pages: 413
Release: 2004-01-09
ISBN 10: 0875904173
ISBN 13: 9780875904177
Language: EN, FR, DE, ES & NL

Sea Salt Aerosol Production Book Review:

Published by the American Geophysical Union as part of the Geophysical Monograph Series, Volume 152. Sea salt aerosol (SSA) exerts a major influence over a broad reach of geophysics. It is important to the physics and chemistry of the marine atmosphere and to marine geochemistry and biogeochemistry generally. It affects visibility, remote sensing, atmospheric chemistry, and air quality. Sea salt aerosol particles interact with other atmospheric gaseous and aerosol constituents by acting as sinks for condensable gases and suppressing new particle formation, thus influencing the size distribution of these other aerosols and more broadly influencing the geochemical cycles of substances with which they interact. As the key aerosol constituent over much of Earth's surface at present, and all the more so in pre-industrial times, SSA is central to description of Earth's aerosol burden.