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The Effect Of Enso On Arctic Sea Ice As A Source Of Predictability
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Book Synopsis The Effect of ENSO on Arctic Sea Ice as a Source of Predictability by : Robin Clancy
Download or read book The Effect of ENSO on Arctic Sea Ice as a Source of Predictability written by Robin Clancy and published by . This book was released on 2019 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: ENSO is the primary mode of global climate variability but its links to Arctic sea ice are uncertain, in part due to the short observational record. The Community Earth System Model is used to constrain the effect of ENSO on Arctic sea ice concentration and thickness, as well as the sea level pressure, atmospheric temperature and snowfall patterns which drive this response. A deepened Aleutian Low and high pressure over the central Arctic appear to drive a redistribution of the sea ice in the winter and spring following an El Niño compared to a La Niña. El Niño years experience warmer Arctic air temperature and increased melting during summer when compared to La Niña years. These effects are validated, where possible, using satellite and reanalysis data. The shifting ice edge results in variations in the predictability of Arctic sea ice in some regions.
Book Synopsis Seasonal to Decadal Predictions of Arctic Sea Ice by : National Research Council
Download or read book Seasonal to Decadal Predictions of Arctic Sea Ice written by National Research Council and published by National Academies Press. This book was released on 2013-01-03 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent well documented reductions in the thickness and extent of Arctic sea ice cover, which can be linked to the warming climate, are affecting the global climate system and are also affecting the global economic system as marine access to the Arctic region and natural resource development increase. Satellite data show that during each of the past six summers, sea ice cover has shrunk to its smallest in three decades. The composition of the ice is also changing, now containing a higher fraction of thin first-year ice instead of thicker multi-year ice. Understanding and projecting future sea ice conditions is important to a growing number of stakeholders, including local populations, natural resource industries, fishing communities, commercial shippers, marine tourism operators, national security organizations, regulatory agencies, and the scientific research community. However, gaps in understanding the interactions between Arctic sea ice, oceans, and the atmosphere, along with an increasing rate of change in the nature and quantity of sea ice, is hampering accurate predictions. Although modeling has steadily improved, projections by every major modeling group failed to predict the record breaking drop in summer sea ice extent in September 2012. Establishing sustained communication between the user, modeling, and observation communities could help reveal gaps in understanding, help balance the needs and expectations of different stakeholders, and ensure that resources are allocated to address the most pressing sea ice data needs. Seasonal-to-Decadal Predictions of Arctic Sea Ice: Challenges and Strategies explores these topics.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309388805 Total Pages :351 pages Book Rating :4.3/5 (93 download)
Book Synopsis Next Generation Earth System Prediction by : National Academies of Sciences, Engineering, and Medicine
Download or read book Next Generation Earth System Prediction written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-08-22 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the nation's economic activities, security concerns, and stewardship of natural resources become increasingly complex and globally interrelated, they become ever more sensitive to adverse impacts from weather, climate, and other natural phenomena. For several decades, forecasts with lead times of a few days for weather and other environmental phenomena have yielded valuable information to improve decision-making across all sectors of society. Developing the capability to forecast environmental conditions and disruptive events several weeks and months in advance could dramatically increase the value and benefit of environmental predictions, saving lives, protecting property, increasing economic vitality, protecting the environment, and informing policy choices. Over the past decade, the ability to forecast weather and climate conditions on subseasonal to seasonal (S2S) timescales, i.e., two to fifty-two weeks in advance, has improved substantially. Although significant progress has been made, much work remains to make S2S predictions skillful enough, as well as optimally tailored and communicated, to enable widespread use. Next Generation Earth System Predictions presents a ten-year U.S. research agenda that increases the nation's S2S research and modeling capability, advances S2S forecasting, and aids in decision making at medium and extended lead times.
Book Synopsis Assessment of Intraseasonal to Interannual Climate Prediction and Predictability by : National Research Council
Download or read book Assessment of Intraseasonal to Interannual Climate Prediction and Predictability written by National Research Council and published by National Academies Press. This book was released on 2010-10-08 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: More accurate forecasts of climate conditions over time periods of weeks to a few years could help people plan agricultural activities, mitigate drought, and manage energy resources, amongst other activities; however, current forecast systems have limited ability on these time- scales. Models for such climate forecasts must take into account complex interactions among the ocean, atmosphere, and land surface. Such processes can be difficult to represent realistically. To improve the quality of forecasts, this book makes recommendations about the development of the tools used in forecasting and about specific research goals for improving understanding of sources of predictability. To improve the accessibility of these forecasts to decision-makers and researchers, this book also suggests best practices to improve how forecasts are made and disseminated.
Book Synopsis Sub-seasonal to Seasonal Prediction by : Andrew Robertson
Download or read book Sub-seasonal to Seasonal Prediction written by Andrew Robertson and published by Elsevier. This book was released on 2018-10-19 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Gap Between Weather and Climate Forecasting: Sub-seasonal to Seasonal Prediction is an ideal reference for researchers and practitioners across the range of disciplines involved in the science, modeling, forecasting and application of this new frontier in sub-seasonal to seasonal (S2S) prediction. It provides an accessible, yet rigorous, introduction to the scientific principles and sources of predictability through the unique challenges of numerical simulation and forecasting with state-of-science modeling codes and supercomputers. Additional coverage includes the prospects for developing applications to trigger early action decisions to lessen weather catastrophes, minimize costly damage, and optimize operator decisions. The book consists of a set of contributed chapters solicited from experts and leaders in the fields of S2S predictability science, numerical modeling, operational forecasting, and developing application sectors. The introduction and conclusion, written by the co-editors, provides historical perspective, unique synthesis and prospects, and emerging opportunities in this exciting, complex and interdisciplinary field. - Contains contributed chapters from leaders and experts in sub-seasonal to seasonal science, forecasting and applications - Provides a one-stop shop for graduate students, academic and applied researchers, and practitioners in an emerging and interdisciplinary field - Offers a synthesis of the state of S2S science through the use of concrete examples, enabling potential users of S2S forecasts to quickly grasp the potential for application in their own decision-making - Includes a broad set of topics, illustrated with graphic examples, that highlight interdisciplinary linkages
Book Synopsis On the Predictability of Sea Ice by : Edward Blanchard- Wrigglesworth
Download or read book On the Predictability of Sea Ice written by Edward Blanchard- Wrigglesworth and published by . This book was released on 2013 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: We investigate the persistence and predictability of sea ice in numerical models and observations. We first use the 3rd generation Community Climate System Model (CCSM3) General Circulation Model (GCM) to investigate the inherent persistence of sea-ice area and thickness. We find that sea-ice area anomalies have a seasonal decay timescale, exhibiting an initial decorrelation similar to a first order auto-regressive (AR1, or red noise) process. Beyond this initial loss of memory, there is a re-emergence of memory at certain times of the year. There are two distinct modes of re-emergence in the model, one driven by the seasonal coupling of area and thickness anomalies in the summer, the other by the persistence of upper ocean temperature anomalies that originate from ice anomalies in the melt season and then influence ice anomalies in the growth season. Comparison with satellite observations where available indicate these processes appear in nature. We then use the 4th generation CCSM (CCSM4) to investigate the partition of Arctic sea-ice predictability into its initial-value and boundary forced components under present day forcing conditions. We find that initial-value predictability lasts for 1-2 years for sea-ice area, and 3-4 years for sea-ice volume. Forced predictability arises after just 4-5 years for both area and volume. Initial-value predictability of sea-ice area during the summer hinges on the coupling between thickness and area anomalies during that season. We find that the loss of initial-value predictability with time is not uniform --- there is a rapid loss of predictability of sea-ice volume during the late spring early summer associated with snow melt and albedo feedbacks. At the same time, loss of predictability is not uniform across different regions. Given the usefulness of ice thickness as a predictor of summer sea-ice area, we obtain a hindcast of September sea-ice area initializing the GCM on May 1with an estimate of observed sea-ice thickness anomalies. We run the GCM in a slab-ocean model configuration and obtain predictability that is lower than expected from the perfect model fully coupled GCM. We next make use of models submitted to the CMIP5 archive to investigate the spatial and temporal characteristics of ice thickness anomalies, together with the CCSM3, CCSM4 and two forced ice-ocean models, PIOMAS and CCSM4 in ice-ocean mode. We find that there is a wide spread in the characteristics of ice thickness anomalies across models, partially explained by biases in mean thickness. Additionally, forced ice-ocean models show reduced ice-thickness variability. These results have significant implications for the initialization of fully-coupled GCMs from forced GCM output. Finally we investigate the initial-value predictability of Antarctic sea ice in the CCSM3. We find that Antarctic sea-ice anomaly persistence is comparable to that of Arctic sea-ice anomalies. High values of initial-value predictability of sea-ice area can last for up to two years, and tend to advect eastward in time. We also find memory re-emergence that is driven by upper ocean heat anomalies from the melt to the growth season. Unlike the Arctic, we do not find evidence for an ice-thickness driven mechanism of memory re-emergence
Book Synopsis Sea Ice Analysis and Forecasting by : Tom Carrieres
Download or read book Sea Ice Analysis and Forecasting written by Tom Carrieres and published by Cambridge University Press. This book was released on 2017-10-05 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an advanced introduction to the science behind automated prediction systems, focusing on sea ice analysis and forecasting. Starting from basic principles, fundamental concepts in sea ice physics, remote sensing, numerical methods, and statistics are explained at an accessible level. Existing operational automated prediction systems are described and their impacts on information providers and end clients are discussed. The book also provides insight into the likely future development of sea ice services and how they will evolve from mainly manual processes to increasing automation, with a consequent increase in the diversity and information content of new ice products. With contributions from world-leading experts in the fields of sea ice remote sensing, data assimilation, numerical modelling, and verification and operational prediction, this comprehensive reference is ideal for students, sea ice analysts, and researchers, as well as decision-makers and professionals working in the ice service industry.
Book Synopsis Initializing and Predictability of Arctic Sea Ice in a Global Climate Model by : Steffen Tietsche
Download or read book Initializing and Predictability of Arctic Sea Ice in a Global Climate Model written by Steffen Tietsche and published by . This book was released on 2012 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309456002 Total Pages :83 pages Book Rating :4.3/5 (94 download)
Book Synopsis Antarctic Sea Ice Variability in the Southern Ocean-Climate System by : National Academies of Sciences, Engineering, and Medicine
Download or read book Antarctic Sea Ice Variability in the Southern Ocean-Climate System written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-04-24 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sea ice surrounding Antarctica has increased in extent and concentration from the late 1970s, when satellite-based measurements began, until 2015. Although this increasing trend is modest, it is surprising given the overall warming of the global climate and the region. Indeed, climate models, which incorporate our best understanding of the processes affecting the region, generally simulate a decrease in sea ice. Moreover, sea ice in the Arctic has exhibited pronounced declines over the same period, consistent with global climate model simulations. For these reasons, the behavior of Antarctic sea ice has presented a conundrum for global climate change science. The National Academies of Sciences, Engineering, and Medicine held a workshop in January 2016, to bring together scientists with different sets of expertise and perspectives to further explore potential mechanisms driving the evolution of recent Antarctic sea ice variability and to discuss ways to advance understanding of Antarctic sea ice and its relationship to the broader ocean-climate system. This publication summarizes the presentations and discussions from the workshop.
Book Synopsis Initialization and Predictability of Arctic Sea Ice in a Global Climate Model by : Steffen Tietsche
Download or read book Initialization and Predictability of Arctic Sea Ice in a Global Climate Model written by Steffen Tietsche and published by . This book was released on 2012 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Interacting Climates of Ocean Basins by : Carlos R. Mechoso
Download or read book Interacting Climates of Ocean Basins written by Carlos R. Mechoso and published by Cambridge University Press. This book was released on 2020-11-26 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review of interactions between the climates of different ocean basins and their key contributions to global climate variability and change. Providing essential theory and discussing outstanding examples as well as impacts on monsoons, it a useful resource for graduate students and researchers in the atmospheric and ocean sciences.
Book Synopsis Understanding the Predictability of the Arctic Climate by :
Download or read book Understanding the Predictability of the Arctic Climate written by and published by . This book was released on 2018 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Jackknife, the Bootstrap, and Other Resampling Plans by : Bradley Efron
Download or read book The Jackknife, the Bootstrap, and Other Resampling Plans written by Bradley Efron and published by SIAM. This book was released on 1982-01-01 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: The jackknife and the bootstrap are nonparametric methods for assessing the errors in a statistical estimation problem. They provide several advantages over the traditional parametric approach: the methods are easy to describe and they apply to arbitrarily complicated situations; distribution assumptions, such as normality, are never made. This monograph connects the jackknife, the bootstrap, and many other related ideas such as cross-validation, random subsampling, and balanced repeated replications into a unified exposition. The theoretical development is at an easy mathematical level and is supplemented by a large number of numerical examples. The methods described in this monograph form a useful set of tools for the applied statistician. They are particularly useful in problem areas where complicated data structures are common, for example, in censoring, missing data, and highly multivariate situations.
Book Synopsis Assessing the Predictability of the Beaufort Sea Minimum Ice Extent in a Changing Arctic Climate Regime by : Laura Marie Quirk
Download or read book Assessing the Predictability of the Beaufort Sea Minimum Ice Extent in a Changing Arctic Climate Regime written by Laura Marie Quirk and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the climatic drivers of changes in sea ice extent in the Arctic has become increasingly important as record minima in the September sea ice extent continue to be reached. This research therefore addresses the question of which synoptic scale climatological features are most important in affecting changes in sea ice extent in the Beaufort Sea. First, three measures of sea ice extent- the Barnett Severity Index, the Beaufort Sea minimum sea ice extent, and the Arctic-wide minimum sea ice extent- are compared to assess their degree of agreement and consistency using goodness of fit techniques. Secondly, a number of atmospheric predictor variables are analyzed using a composite approach to identify the most relevant predictors of sea ice in the region. Thirdly, monthly statistical forecast models are created based on multiple regressions and classification and regression trees (CART) to predict the minimum sea ice extent beginning in October of the previous year. Many differing measures have been used to quantify sea ice conditions in the Beaufort Sea, although no study has assessed these measures for consistency. When compared, all three measures indicate the same level of agreement according to the goodness of fit tests. This indicates that the choice of measure can be determined based on the specific application, as no measure outperforms another. In addition to differing measures of sea ice extent, differing predictor variables have been utilized to predict summer sea ice conditions. This study assesses all potentially relevant predictor variables and indicates that upper atmospheric air temperatures at 850 hPa, 700 hPa, and 500 hPa, monthly mean surface air temperatures, freezing degree days, thawing degree days, sea level pressure, total ice concentration, and multiyear ice concentration showed the strongest relationships with sea ice. Various teleconnection patterns including the Arctic Oscillation, the North Atlantic Oscillation, and the Pacific-North American pattern also showed strong relationships with these variables and are therefore believed also have some predictive utility. Finally, monthly multiple linear regression and CART models are created to predict the September sea ice extent using a number of climatic predictor variables. The results of these models suggest that antecedent sea ice conditions (total and multiyear ice concentration) and surface air temperature are the most important variables in predicting summer sea ice extent. The potential predictive power of the forecasts increases as predictions are made closer to the September minimum sea ice extent, with the most precise predictions made during July. This research confirms previous studies and provides a useful compilation of the state of the knowledge on the drivers of sea ice changes in the Beaufort Sea. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/152586
Book Synopsis Arctic Sea Ice Predictability and Prediction by : Chao-Yuan Yang
Download or read book Arctic Sea Ice Predictability and Prediction written by Chao-Yuan Yang and published by . This book was released on 2019 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sea Ice in the Arctic by : Ola M. Johannessen
Download or read book Sea Ice in the Arctic written by Ola M. Johannessen and published by Springer Nature. This book was released on 2019-11-12 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides in-depth information about the sea ice in the Arctic at scales from paleoenvironmental variability to more contemporary changes during the past and present centuries. The book is based on several decades of research related to sea ice in the Arctic and its variability, sea ice process studies as well as implications of the sea ice variability on human activities. The chapters provide an extensive overview of the research results related to sea ice in the Arctic at paleo-scales to more resent scales of variations as well as projections for changes during the 21st century. The authors have pioneered the satellite remote sensing monitoring of sea ice and used other monitoring data in order to study, monitor and model sea ice and its processes.
Book Synopsis Seasonal Forecast Skill and Potential Predictability of Arctic Sea Ice in Two Versions of a Dynamical Forecast System by : Joseph Zachary Martin
Download or read book Seasonal Forecast Skill and Potential Predictability of Arctic Sea Ice in Two Versions of a Dynamical Forecast System written by Joseph Zachary Martin and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As the decline in Arctic sea ice extent makes this region more accessible, the need is increasing for effective seasonal sea ice forecasting to facilitate operational planning. Recently, coupled global climate models (CGCMs) have been used to address the need for effective sea ice forecasting on seasonal time scales. This thesis assesses the operational utility of the Canadian Seasonal to Interannual Prediction System (CanSIPS) for seasonal sea ice forecasting. This assessment consists of two separate studies. The first uses hindcasting to analyze the skill of two versions of CanSIPS, as well as an intermediate version, on the pan-Arctic as well as regional scales. This approach allows for an overall assessment of the system's skill in addition to providing insight with regards to the features in each version which improved that skill. This study finds that the use of a new initialization procedure for sea ice concentration and thickness improved forecast skill on the pan-Arctic scale as well as in the Central Arctic, Barents Sea, Laptev Sea, and Sea of Okhotsk. This study also shows that the substitution of one of the constituent models in the system improved forecast skill on the pan-Arctic scale as well as in the GIN, Barents, Kara, East Siberian, Chukchi, Bering, and Beaufort Seas. Overall, the new version of CanSIPS was found to be generally more skillful than previous versions. The second study conducts a potential predictability experiment on CanCM4, the constituent CGCM common to all versions of CanSIPS considered in this study. This study follows the methodology introduced by \cite{Bushuk2018} which allows for a more complete assessment of the dependency of potential predictability on initialization month than previous studies and for comparisons to be made between potential predictability and operational skill. This analysis is again done on both the pan-Arctic and regional scale. The findings of this experiment show that CanCM4 has relatively low potential predictability relative to other models and explains results previously presented in a multi-model study by \cite{Day2016}. Further, the characteristics of CanCM4's potential predictability share similarities with other models including greater predictability at longer lead times for winter target months than summer target months, greater predictability in the Atlantic sector than the Pacific sector, and the presence of the spring predictability barrier on the pan-Arctic scale as well as in several regions. The comparison of operational skill to potential predictability provides a general overview of the ``skill gap" which may be closed with improvements in initialization procedures and model physics. This comparison does, however, come with some caveats due to differences in the statistical characteristics of the perfect model and the climate system it represents. Together, the operational skill assessment of different versions of CanSIPS and the potential predictability experiment conducted on one of its constituent models, CanCM4, demonstrate that while room for improvement exists, the recent development of this forecast system has clearly increased its operational utility as a seasonal sea ice forecasting tool.
