Sea Ice Analysis And Forecasting
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Sea Ice Analysis And Forecasting
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Author : Tom Carrieres
language : en
Publisher: Cambridge University Press
Release Date : 2017-10-05
Sea Ice Analysis And Forecasting written by Tom Carrieres and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-05 with Science categories.
A comprehensive overview of the science involved in automated prediction of sea ice, for sea ice analysts, researchers, and professionals.
Sea Ice Analysis And Forecasting
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Author : Tom Carrieres
language : en
Publisher:
Release Date : 2017
Sea Ice Analysis And Forecasting written by Tom Carrieres and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Sea ice categories.
A comprehensive overview of the science involved in automated prediction of sea ice, for sea ice analysts, researchers, and professionals.
Handbook For Sea Ice Analysis And Forecasting
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Author : William J. Stringer
language : en
Publisher:
Release Date : 1984
Handbook For Sea Ice Analysis And Forecasting written by William J. Stringer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Sea ice categories.
Meeting On Handbook Analysis And Forecasting Of Sea Ice Final Report Leningrad 23 26 July 1991
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Author : World Meteorological Organization
language : en
Publisher:
Release Date : 1991
Meeting On Handbook Analysis And Forecasting Of Sea Ice Final Report Leningrad 23 26 July 1991 written by World Meteorological Organization and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Glaciology categories.
Statistical Analysis And Forecasting Of Sea Ice Conditions In Canadian Waters
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Author : Laurent Garrigues
language : en
Publisher:
Release Date : 2001
Statistical Analysis And Forecasting Of Sea Ice Conditions In Canadian Waters written by Laurent Garrigues and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.
"Historical data of sea ice concentration in Canadian waters are analysed using projections methods (Principal Component Analysis, Singular Value Decomposition, Canonical Correlation Analysis and Projection on Latent Structures) to identify the main patterns of evolution in the sea ice cover. Three different areas of interest are studied: (1) the Gulf of St Lawrence, (2) the Beaufort Sea and (3) the Labrador Sea down to the east coast of Newfoundland. Forcing parameters that drive the evolution of the sea ice cover such as surface air temperature and wind field are also analysed in order to explain some of the variability observed in the sea ice field. Only qualitative correlations have been identified, essentially because of the singular nature of the sea ice concentration itself and the accuracy of available data. However, several statistical models based on identified patterns have been developed showing forecasting skills far better than those of the persistence assumption, which currently remains one of the best 'model' available. Forecasts are tested over periods of time ranging from a few days to several weeks. Some of these models constitute innovative approaches in the context of statistical sea ice forecasting. Some others models have been developed using a probabilistic approach. These models provide forecasts in terms of sea ice severity (low-medium-high), which is often accurate enough for navigation purposes for the three areas of interest. Forecasting skills of these models are also better than the persistence assumption. Finally, an existing dynamic sea-ice model has been adapted and used to predict sea ice conditions in the Gulf of St Lawrence during the Winter season 1992-1993. Simulations provided by this model are compared to the forecasts of different statistical models over the same period of time." --
A Basis For Forecasting The Arctic Sea Ice Over A Few Months To Many Years
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Author : H. H. Lamb
language : en
Publisher:
Release Date : 1979
A Basis For Forecasting The Arctic Sea Ice Over A Few Months To Many Years written by H. H. Lamb and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with categories.
An 80-year set of sea-ice data has been collected and digitized, and work is in progress to verify this data set. Principal component analysis has been used to identify 'typical' mean sea level (MSL) pressure anomaly patterns and their temporal variations, and these have been correlated with long series of sea ice indices for various regions. Time series analysis of these sea ice and MSL pressure data has revealed characteristic time scales of variation, as well as significant long-term trends. In addition, studies have been made of various mechanisms which may have been responsible for the fluctuations in the atmospheric circulation and sea ice. (Author).
Ice Edge Verification
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Author : Bimochan Niraula
language : en
Publisher:
Release Date : 2023
Ice Edge Verification written by Bimochan Niraula and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Sea ice is one of the most crucial components of the polar system. Alongside its effects on the climate and weather, it also impacts human lives and operations in these regions. Climate scientists, as well as other stakeholders (such as marine industries, mining operations, governmental authorities as well as local/aboriginal population), have a high interest in getting accurate observation and prediction of sea ice presence, and its effective border - the ice edge. In this context, this thesis is focused on the verification of ice presence and ice edge, across different datasets. We do this by describing a new method of generating reference forecasts of the ice edge (as benchmark for predictions at sub-seasonal to seasonal timescales), analysing initial state errors in forecasts and analysis from ECMWF, and comparing the ice presence and ice edge difference between several observational and analysis datasets. Operational systems generating sea ice forecasts at sub-seasonal timescales are mostly compared against simple references based solely on climatological or initial states, which can lead to a potential overestimation of their prediction skill. In chapter 1, we describe the Spatial Damped Anomaly Persistence (SDAP) method, which combines historical sea ice probability with the initial ice edge anomalies to generate probabilistic reference forecasts of the ice edge. The SDAP forecasts outperform both traditional references, as well as most dynamical forecast models from the Sub-seasonal to Seasonal (S2S) project at long lead times, establishing a more challenging benchmark for operational forecast systems. Within the S2S database, forecasts from the European Centre for Medium- Range Weather Forecasts (ECMWF) have the highest prediction skill compared to both traditional references and SDAP forecasts, but show significant initial error. In chapter 2, we analyse this initial state issue in the ECMWF forecasts, as well as corresponding analysis from ORAS5, by measuring the errors against observations from OSISAF. We find that the initial state errors are partly due to interpolation issues, and partly systematic underestimation, especially in the summer. We show the spatial distribution of the mean bias and provide evidence that between 10 to 20% of the error can be reduced simply by subtracting the mean bias. While forecast verification methods assume observations to be 'the truth', observational records also have inconsistencies that have previously only been discussed in concentration or ice extent terms. In chapter 3, we analyse differences in ice presence between several observational and analysis datasets by measuring the Integrated Ice Edge Error and bias between each pair. We find significant mismatch between observations, particularly in the summer, and identify regions where certain observations disagrees with all other. Our results show that observational records from OSISAF potentially overestimate ice presence, while those from AMSR-E/2 potentially underestimate it. In the last chapter, we discuss the results from the different studies in context of each other and mention how the inconsistencies in observations cast doubt on the forecast errors we initially measured, offering the possibility of a probabilistic observation and reemphasizing the need for accurate sea ice edge measurements and forecasts.
Monthly Mean Sea Ice Data From The Polar Ice Prediction System The Regional Polar Ice Prediction System Barents Sea And The Regional Polar Ice Prediction System Greenland Sea
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Author :
language : en
Publisher:
Release Date : 1994
Monthly Mean Sea Ice Data From The Polar Ice Prediction System The Regional Polar Ice Prediction System Barents Sea And The Regional Polar Ice Prediction System Greenland Sea written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
The Polar Ice Prediction System (PIPS), the Regional Polar Ice Prediction System - Barents (RPIPS-B) and the Regional Polar Ice Prediction System - Greenland Sea (RPIPS-G) are all operational sea ice forecasting systems that have been run daily at the Fleet Numerical Meteorology and Oceanography Center (FNMOC) since September 1987, June 1989, and October 1991, respectively. The basis for all three models is the Hibler ice model (Hibler, W.D. (1 979). A Dynamic Thermodynamic Sea Ice Model. Journal of Physical Oceanography 9:815-846; Hibler, W.D. (1 980). Modeling a Variable Thickness Sea Ice Cover. Monthly Weather Review 108:1944-1973). The ice models are driven by monthly mean ocean currents and deep ocean heat fluxes derived from the Hibler and Bryan (A diagnostic Ice-Ocean Model. Journal Physical Oceanography 17:987-1015 (1987) coupled ice-ocean model. They are also driven by atmospheric forcing from the Navy Operational Global Atmospheric Prediction System (NOGAPS) (Rosmond, T.E. (1981). NOGAPS: Navy Operational Global Atmospheric Prediction System. In Fifth Conference on Numerical Weather Prediction (Monterey, California), American Meteorological Society, Boston, Massachusetts, preprint volume, 74-79; Hogan et al. (1990). The Description of the Navy Operational Global Atmospheric Prediction System's Forecast Model. Naval Research Laboratory, Monterey, California, NOARL Report 13). Each day a 24-h forecast of PIPS, RPIPS-B, and RPIPS-G is submitted and archived by the Naval Research Laboratory. Sea ice forecasting, Sea ice models, Sea ice analysis.
Sea Ice In The Arctic
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Author : Ola M. Johannessen
language : en
Publisher: Springer Nature
Release Date : 2019-11-12
Sea Ice In The Arctic written by Ola M. Johannessen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-12 with Technology & Engineering categories.
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.
Monthly Mean Sea Ice Data From The Polar Ice Prediction System The Regional Polar Ice Prediction System Barents Sea
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Author : Pamela G. Posey
language : en
Publisher:
Release Date : 1990
Monthly Mean Sea Ice Data From The Polar Ice Prediction System The Regional Polar Ice Prediction System Barents Sea written by Pamela G. Posey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Ice categories.
The Polar Ice Prediction System (PIPS), the Regional Polar Ice Prediction System - Barents (RPIPS-B) and the Regional Polar Ice Prediction System - Greenland Sea (RPIPS-G) are all operational sea ice forecasting systems that have been run daily at the Fleet Numerical Meteorology and Oceanography Center (FNMOC) since September 1987, June 1989, and October 1991, respectively. The basis for all three models is the Hibler ice model (Hibler, W. D. (1 979). A Dynamic Thermodynamic Sea Ice Model. Journal of Physical Oceanography 9:815-846; Hibler, W. D. (1 980). Modeling a Variable Thickness Sea Ice Cover. Monthly Weather Review 108:1944-1973). The ice models are driven by monthly mean ocean currents and deep ocean heat fluxes derived from the Hibler and Bryan (A diagnostic Ice-Ocean Model. Journal Physical Oceanography 17:987-1015 (1987) coupled ice-ocean model. They are also driven by atmospheric forcing from the Navy Operational Global Atmospheric Prediction System (NOGAPS) (Rosmond, T. E. (1981). NOGAPS: Navy Operational Global Atmospheric Prediction System. In Fifth Conference on Numerical Weather Prediction (Monterey, California), American Meteorological Society, Boston, Massachusetts, preprint volume, 74-79; Hogan et al. (1990). The Description of the Navy Operational Global Atmospheric Prediction System's Forecast Model. Naval Research Laboratory, Monterey, California, NOARL Report 13). Each day a 24-h forecast of PIPS, RPIPS-B, and RPIPS-G is submitted and archived by the Naval Research Laboratory. Sea ice forecasting, Sea ice models, Sea ice analysis.