Using Self-organizing Maps to Detail Synoptic Connections Between Climate Indices and Alaska Weather


Book Description

Seasonal forecasts for Alaska strongly depend on the phases of Pacific Decadal Oscillation (PDO), El Niño-Southern Oscillation (ENSO), and warm water in the North Pacific called the North Pacific Mode or more popularly the "Pacific blob." The canonical descriptions of these climate indices are based on seasonal averages, and anomalies that are based on a long-term mean. The patterns highlight general geographical placement and display a sharp contrast between opposing phases, but this may be misleading since seasonal averages hide much of the synoptic variability. Self-organizing maps (SOMs) are a way of grouping daily sea level pressure (SLP) patterns, over many time realizations into a specified set of maps (e.g. 35 maps) that describe commonly occurring patterns. This study uses the SOMs in the context of climate indices to describe the range of synoptic patterns that are relevant for Alaska. This study found that the patterns common during a given phase of the PDO include subtle differences that would result in Alaska weather that is very different from what is expected from the canonical PDO description, thus providing some explanation for recent studies that find the PDO link to Alaska climate is weakening. SOMs analysis is consistent with recent studies suggesting that the pattern responsible for the 2014 Pacific warm blob is linked to tropical sea-surface temperature (SST) forcing. An analysis of the summer SLP SOMs in the context of Alaska wildland fires was also conducted. This analysis identified several commonly occurring patterns during summers with large areas burned. These patterns are characterized by low pressure in the Bering Sea, which would be consistent with increased storm activity and thus an ignition source for the fires. Identifying synoptic patterns that occur during a particular phase of a teleconnection index contributes towards understanding the mechanisms of how these indices influence the weather and climate of Alaska.







Patterns Identification and Data Mining in Weather and Climate


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.




Attribution of Extreme Weather Events in the Context of Climate Change


Book Description

As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities.




Self-Organizing Maps


Book Description

The book we have at hand is the fourth monograph I wrote for Springer Verlag. The previous one named "Self-Organization and Associative Mem ory" (Springer Series in Information Sciences, Volume 8) came out in 1984. Since then the self-organizing neural-network algorithms called SOM and LVQ have become very popular, as can be seen from the many works re viewed in Chap. 9. The new results obtained in the past ten years or so have warranted a new monograph. Over these years I have also answered lots of questions; they have influenced the contents of the present book. I hope it would be of some interest and help to the readers if I now first very briefly describe the various phases that led to my present SOM research, and the reasons underlying each new step. I became interested in neural networks around 1960, but could not in terrupt my graduate studies in physics. After I was appointed Professor of Electronics in 1965, it still took some years to organize teaching at the uni versity. In 1968 - 69 I was on leave at the University of Washington, and D. Gabor had just published his convolution-correlation model of autoasso ciative memory. I noticed immediately that there was something not quite right about it: the capacity was very poor and the inherent noise and crosstalk were intolerable. In 1970 I therefore sugge~ted the auto associative correlation matrix memory model, at the same time as J.A. Anderson and K. Nakano.




Computational Science -- ICCS 2005


Book Description

The Fifth International Conference on Computational Science (ICCS 2005) held in Atlanta, Georgia, USA, May 22–25, 2005, continued in the tradition of p- vious conferences in the series: ICCS 2004 in Krakow, Poland; ICCS 2003 held simultaneously at two locations, in Melbourne, Australia and St. Petersburg, Russia; ICCS 2002 in Amsterdam, The Netherlands; and ICCS 2001 in San Francisco, California, USA. Computational science is rapidly maturing as a mainstream discipline. It is central to an ever-expanding variety of ?elds in which computational methods and tools enable new discoveries with greater accuracy and speed. ICCS 2005 wasorganizedasaforumforscientistsfromthecoredisciplinesofcomputational science and numerous application areas to discuss and exchange ideas, results, and future directions. ICCS participants included researchers from many app- cation domains, including those interested in advanced computational methods for physics, chemistry, life sciences, engineering, economics and ?nance, arts and humanities, as well as computer system vendors and software developers. The primary objectives of this conference were to discuss problems and solutions in allareas,toidentifynewissues,toshapefuturedirectionsofresearch,andtohelp users apply various advanced computational techniques. The event highlighted recent developments in algorithms, computational kernels, next generation c- puting systems, tools, advanced numerical methods, data-driven systems, and emerging application ?elds, such as complex systems, ?nance, bioinformatics, computational aspects of wireless and mobile networks, graphics, and hybrid computation.




Natural Climate Variability on Decade-to-Century Time Scales


Book Description

This volume reflects the current state of scientific knowledge about natural climate variability on decade-to-century time scales. It covers a wide range of relevant subjects, including the characteristics of the atmosphere and ocean environments as well as the methods used to describe and analyze them, such as proxy data and numerical models. They clearly demonstrate the range, persistence, and magnitude of climate variability as represented by many different indicators. Not only do natural climate variations have important socioeconomic effects, but they must be better understood before possible anthropogenic effects (from greenhouse gas emissions, for instance) can be evaluated. A topical essay introduces each of the disciplines represented, providing the nonscientist with a perspective on the field and linking the papers to the larger issues in climate research. In its conclusions section, the book evaluates progress in the different areas and makes recommendations for the direction and conduct of future climate research. This book, while consisting of technical papers, is also accessible to the interested layperson.




The Regional Impacts of Climate Change


Book Description

Cambridge, UK : Cambridge University Press, 1998.




Statistical Downscaling and Bias Correction for Climate Research


Book Description

A comprehensive and practical guide, providing technical background and user context for researchers, graduate students, practitioners and decision makers. This book presents the main approaches and describes their underlying assumptions, skill and limitations. Guidelines for the application of downscaling and the use of downscaled information in practice complete the volume.




Climate Impacts on Energy Systems


Book Description

"While the energy sector is a primary target of efforts to arrest and reverse the growth of greenhouse gas emissions and lower the carbon footprint of development, it is also expected to be increasingly affected by unavoidable climate consequences from the damage already induced in the biosphere. Energy services and resources, as well as seasonal demand, will be increasingly affected by changing trends, increasing variability, greater extremes and large inter-annual variations in climate parameters in some regions. All evidence suggests that adaptation is not an optional add-on but an essential reckoning on par with other business risks. Existing energy infrastructure, new infrastructure and future planning need to consider emerging climate conditions and impacts on design, construction, operation, and maintenance. Integrated risk-based planning processes will be critical to address the climate change impacts and harmonize actions within and across sectors. Also, awareness, knowledge, and capacity impede mainstreaming of climate adaptation into the energy sector. However, the formal knowledge base is still nascent?information needs are complex and to a certain extent regionally and sector specific. This report provides an up-to-date compendium of what is known about weather variability and projected climate trends and their impacts on energy service provision and demand. It discusses emerging practices and tools for managing these impacts and integrating climate considerations into planning processes and operational practices in an environment of uncertainty. It focuses on energy sector adaptation, rather than mitigation which is not discussed in this report. This report draws largely on available scientific and peer-reviewed literature in the public domain and takes the perspective of the developing world to the extent possible."