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Author: Mary Kathleen Brennan Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
Arctic sea ice has undergone rapid declines in recent decades. Given the short satellite record (1979–present), disentangling the relative role of natural variability and anthropogenic forcing on recent declines remains an important unresolved problem. In order to acquire a longer, reliable record of Arctic sea ice we employ data assimilation to combine temperature observations and climate model output. This technique results in fully gridded spatial fields of various climate variables throughout the Instrumental Era (1850-present). Specifically, the goal of this research is to reconstruct Arctic sea ice coverage and thickness on both annual and monthly timescales. We first reconstruct Arctic sea ice on annual timescales using an offline approach where each time step is independent from one another. This work reveals larger declines in total Arctic sea ice extent during the early 20th century (1900–1940) than previously estimated. Next, we build a Linear Inverse Model to forecast Arctic sea ice and other climate conditions on monthly timescales. We find that the Linear Inverse Model is able to skillfully forecast Arctic climate conditions during statistically stable time periods and is thus most useful when used as a model emulator. We then embed the Linear Inverse Model into a data assimilation scheme to produce monthly reconstructions of Arctic climate throughout the Instrumental Era.
Author: Mary Kathleen Brennan Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
Arctic sea ice has undergone rapid declines in recent decades. Given the short satellite record (1979–present), disentangling the relative role of natural variability and anthropogenic forcing on recent declines remains an important unresolved problem. In order to acquire a longer, reliable record of Arctic sea ice we employ data assimilation to combine temperature observations and climate model output. This technique results in fully gridded spatial fields of various climate variables throughout the Instrumental Era (1850-present). Specifically, the goal of this research is to reconstruct Arctic sea ice coverage and thickness on both annual and monthly timescales. We first reconstruct Arctic sea ice on annual timescales using an offline approach where each time step is independent from one another. This work reveals larger declines in total Arctic sea ice extent during the early 20th century (1900–1940) than previously estimated. Next, we build a Linear Inverse Model to forecast Arctic sea ice and other climate conditions on monthly timescales. We find that the Linear Inverse Model is able to skillfully forecast Arctic climate conditions during statistically stable time periods and is thus most useful when used as a model emulator. We then embed the Linear Inverse Model into a data assimilation scheme to produce monthly reconstructions of Arctic climate throughout the Instrumental Era.
Author: Mary Kathleen Brennan Publisher: ISBN: Category : Languages : en Pages : 57
Book Description
Arctic sea ice concentrations have undergone rapid declines in recent decades. Many factors have been shown to contribute to this decline, and much of it has been attributed to greenhouse gas forcing and natural variability. In order to understand the relative roles of these factors on Arctic sea ice decline, a longer record of spatially complete data is needed. This project employs data assimilation to combine climate model output and proxy records to reconstruct past climate fields using the Last Millennium Reanalysis (LMR) framework, resulting in spatially complete gridded fields with annual resolution over the last two millennia. First the use of the LMR framework to reconstruct Arctic sea ice concentrations is tested through two methods: pseudo proxy experiments and comparing real proxy reconstructions to other records. Pseudo proxy results indicate strong performance in reconstructing Arctic sea ice. Correlation coefficients between the true and reconstructed values range between 0.63 and 0.77 depending on the climate model output used in the assimilation. The total Arctic sea ice extent reconstructed with the LMR using real proxy data compare well with satellite observations with correlation coefficients ranging between 0.54 and 0.84 depending on the climate model data used in the assimilation. These reconstructions were also compared to other records that precede satellite data and the LMR reconstructions show larger and longer lasting sea ice decline in response to early 20th century warming. The total sea ice extent minimum observed in these reconstructions between 1920-1960 is similar to the values observed in the 1990s. Next, two major questions are investigated using the 2000-year Arctic sea ice reconstruction: (1) Are the current sea ice changes unprecedented? and (2) Does sea ice respond to volcanic eruptions? The first is investigated through examining the distribution of total Arctic sea ice extent. The results indicate that both the trends and values of sea ice extent observed in the satellite era are unprecedented with respect to the LMR reconstruction of the last 1000 years. The second question is investigated through a composite average of sea ice extent before and after the 23 largest volcanic eruptions. These results show a statistically significant increase in total Arctic sea ice extent one year after an eruption. Finally, the sensitivity of these reconstructions to proxy location, model prior and the number of prior ensemble members used in the data assimilation scheme is examined. These experiments indicate that the proxies in the Arctic region (above 60N) explain most of the variance in the LMR sea ice reconstructions as expected. The role of the model prior is investigated by comparing the covariance between surface air temperature and Arctic sea ice across four different models. Overall the covariance is very similar except in some isolated regions in central Russia and China, in the North Atlantic and the central Pacific. In these regions the correlation coefficient is positive, but the coefficient of efficiency is negative indicating that there is a difference in the mean or variance in the covariance across models. 200 ensemble members are found to be sufficient in representing the variance in the full 1000 year last millennium model runs.
Author: Eric T. DeWeaver Publisher: John Wiley & Sons ISBN: 1118671589 Category : Science Languages : en Pages : 431
Book Description
Published by the American Geophysical Union as part of the Geophysical Monograph Series, Volume 180. This volume addresses the rapid decline of Arctic sea ice, placing recent sea ice decline in the context of past observations, climate model simulations and projections, and simple models of the climate sensitivity of sea ice. Highlights of the work presented here include An appraisal of the role played by wind forcing in driving the decline; A reconstruction of Arctic sea ice conditions prior to human observations, based on proxy data from sediments; A modeling approach for assessing the impact of sea ice decline on polar bears, used as input to the U.S. Fish and Wildlife Service's decision to list the polar bear as a threatened species under the Endangered Species Act; Contrasting studies on the existence of a "tipping point," beyond which Arctic sea ice decline will become (or has already become) irreversible, including an examination of the role of the small ice cap instability in global warming simulations; A significant summertime atmospheric response to sea ice reduction in an atmospheric general circulation model, suggesting a positive feedback and the potential for short-term climate prediction. The book will be of interest to researchers attempting to understand the recent behavior of Arctic sea ice, model projections of future sea ice loss, and the consequences of sea ice loss for the natural and human systems of the Arctic.
Author: Thomas Johannes Maierhofer Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
The short satellite-observed period from 1979 to 2023 has seen the Antarctic sea ice changedramatically. The sea ice generally increased until 2014 then precipitously decreased from 2014 to 2017. Record lows were then observed in February 2022 and February 2023. To evaluate these recent changes in the context of anthropogenic climate change requires information on Antarctic sea ice variability over the full 20th century. However, only temporally and spatially sparse data are available before 1979, creating a need for statistical reconstructions. We create a stochastic ensemble reconstruction of monthly Antarctic sea ice extent from 1900-1979 using a novel Bayesian spatio-temporal model. This model produces a set of 2500 plausible reconstructions of sea ice extent by sector. These reconstructions improve on prior approaches with realistic month-to-month changes and interdecadal trends as well as plausible interactions between the sectors. These unique features allow the direct computation of extreme event probabilities for the pre-satellite period of the 20th century. For example, we compute a 0.44% probability of reconstructing a decline in total Antarctic sea ice extent as extreme or more extreme than the 2014-2017 decline. We compute a 16% probability of observing a sea ice minimum as low or lower than the February 2022 minimum in total sea ice extent of 2.22 mio. km2, and a probability of 4% for the February 2023 minimum of 2.04 mio. km2. We also propose a novel approach to modeling the Antarctic sea ice edge using a functional regression model. The sea ice edge on a given day is treated as a continuous set of points circling the South Pole and the latitudes of these points are modeled as a function of their longitude. This enables the estimation and visualization of a circumpolar annual cycle and interannual development of the sea ice, providing novel insight into the regionality of sea ice variability. We develop statistical techniques for reconstructing 1966-1978 Antarctic sea ice extent using early satellite images in the visible and infrared spectrum. These images have not previously been analyzed due to severe missingness and cloud cover occluding the sea ice. Combining extensive preprocessing with modern statistical methods, we produce monthly sea ice concentration maps from which we compute historic sea ice extent.
Author: Jacqueline M. Grebmeier Publisher: Springer ISBN: 9401788634 Category : Science Languages : en Pages : 461
Book Description
The Pacific Arctic region is experiencing rapid sea ice retreat, seawater warming, ocean acidification and biological response. Physical and biogeochemical modeling indicates the potential for step-function changes to the overall marine ecosystem. This synthesis book was coordinated within the Pacific Arctic Group, a network of international partners working in the Pacific Arctic. Chapter topics range from atmospheric and physical sciences to chemical processing and biological response to changing environmental conditions. Physical and biogeochemical modeling results highlight the need for data collection and interdisciplinary modeling activities to track and forecast the changing ecosystem of the Pacific Arctic with climate change.
Author: National Research Council Publisher: National Academies Press ISBN: 0309102251 Category : Science Languages : en Pages : 160
Book Description
In response to a request from Congress, Surface Temperature Reconstructions for the Last 2,000 Years assesses the state of scientific efforts to reconstruct surface temperature records for Earth during approximately the last 2,000 years and the implications of these efforts for our understanding of global climate change. Because widespread, reliable temperature records are available only for the last 150 years, scientists estimate temperatures in the more distant past by analyzing "proxy evidence," which includes tree rings, corals, ocean and lake sediments, cave deposits, ice cores, boreholes, and glaciers. Starting in the late 1990s, scientists began using sophisticated methods to combine proxy evidence from many different locations in an effort to estimate surface temperature changes during the last few hundred to few thousand years. This book is an important resource in helping to understand the intricacies of global climate change.
Author: National Research Council Publisher: National Academies Press ISBN: 0309133041 Category : Science Languages : en Pages : 252
Book Description
The climate record for the past 100,000 years clearly indicates that the climate system has undergone periodic-and often extreme-shifts, sometimes in as little as a decade or less. The causes of abrupt climate changes have not been clearly established, but the triggering of events is likely to be the result of multiple natural processes. Abrupt climate changes of the magnitude seen in the past would have far-reaching implications for human society and ecosystems, including major impacts on energy consumption and water supply demands. Could such a change happen again? Are human activities exacerbating the likelihood of abrupt climate change? What are the potential societal consequences of such a change? Abrupt Climate Change: Inevitable Surprises looks at the current scientific evidence and theoretical understanding to describe what is currently known about abrupt climate change, including patterns and magnitudes, mechanisms, and probability of occurrence. It identifies critical knowledge gaps concerning the potential for future abrupt changes, including those aspects of change most important to society and economies, and outlines a research strategy to close those gaps. Based on the best and most current research available, this book surveys the history of climate change and makes a series of specific recommendations for the future.
Author: Ivan E. Frolov Publisher: Springer Science & Business Media ISBN: 3540376658 Category : Science Languages : en Pages : 305
Book Description
A group of authors from the Arctic and Antarctic Research Institute in St Petersburg, Russia, have all achieved individual doctoral theses on various aspects of Arctic and Antarctic research. This book is written by experienced group of researchers and authors.
Author: Mary Kathleen Brennan
Author: Mary Kathleen Brennan
Author: Mary Kathleen Brennan
Author: Eric T. DeWeaver
Author: Adam Philip
Author: Thomas Johannes Maierhofer
Author: Jacqueline M. Grebmeier
Author: National Research Council
Author: National Research Council
Author: Ivan E. Frolov
Author: Simona Masina