Ice-atmosphere Interactions and Sea Ice Predictability at Multiple Resolutions in the Community Earth System Model PDF Download

Author: Ana Ordonez
Publisher:
ISBN:
Category :
Languages : en
Pages : 72

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Book Description
This work introduces a high resolution (0.1° ocean), slab ocean version of the Community Earth System Model (CESM1(CAM5)). This model is used to investigate ice/atmosphere interactions through comparison with a standard resolution (1° ocean) control run. Differences in the mean ice fields are dominated by differences in the model climates. The high resolution model is warmer and slightly favors thinner ice and lower ice concentrations. The atmospheric boundary layer responds to these changes, with larger boundary layer heights and weaker inversions over winter ice in the high resolution model. A kernel feedback analysis shows that despite some effects on the atmospheric structure, resolution does not appear to change climate feedbacks. Finally, the new slab ocean model is compared with the CESM Large Ensemble control runs and the PetaApps runs to investigate the effects of resolution and ocean model on monthly sea ice predictability from persistence. Resolution does not have a large effect. The dynamical ocean models generally have better predictability in ice area than slab ocean models in the Arctic. The effects of ocean dynamics are more complicated in the Antarctic.

Author: National Research Council
Publisher: National Academies Press
ISBN: 0309265290
Category : Science
Languages : en
Pages : 93

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Book Description
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: 0309388805
Category : Science
Languages : en
Pages : 351

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Book Description
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.

Author: Tom Carrieres
Publisher: Cambridge University Press
ISBN: 1108417426
Category : Science
Languages : en
Pages : 263

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Book Description
A comprehensive overview of the science involved in automated prediction of sea ice, for sea ice analysts, researchers, and professionals.

Author: Edward Blanchard- Wrigglesworth
Publisher:
ISBN:
Category : Sea ice
Languages : en
Pages : 121

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Book Description
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

Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 030938883X
Category : Science
Languages : en
Pages : 351

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Book Description
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.

Author: Miles McPhee
Publisher: Springer Science & Business Media
ISBN: 0387783350
Category : Science
Languages : en
Pages : 218

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Book Description
At a time when the polar regions are undergoing rapid and unprecedented change, understanding exchanges of momentum, heat and salt at the ice-ocean interface is critical for realistically predicting the future state of sea ice. By offering a measurement platform largely unaffected by surface waves, drifting sea ice provides a unique laboratory for studying aspects of geophysical boundary layer flows that are extremely difficult to measure elsewhere. This book draws on both extensive observations and theoretical principles to develop a concise description of the impact of stress, rotation, and buoyancy on the turbulence scales that control exchanges between the atmosphere and underlying ocean when sea ice is present. Several interesting and unique observational data sets are used to illustrate different aspects of ice-ocean interaction ranging from the impact of salt on melting in the Greenland Sea marginal ice zone, to how nonlinearities in the equation of state for seawater affect mixing in the Weddell Sea. The book’s content, developed from a series of lectures, may be appropriate additional material for upper-level undergraduates and first-year graduate students studying the geophysics of sea ice and planetary boundary layers.

Author: Александр Евгеньевич Семенов
Publisher:
ISBN:
Category : Cyclones
Languages : en
Pages : 194

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Book Description
The goal of this study is to improve understanding of atmosphere, sea ice, and ocean interactions in the context of Arctic storm activities. The reduction of Arctic sea ice extent, increase in ocean water temperatures, and changes of atmospheric circulation have been manifested in the Arctic Ocean along with the large surface air temperature increase during recent decades. All of these changes may change the way in which atmosphere, sea ice, and ocean interact, which may in turn feedback to Arctic surface air warming. To achieve the goal, we employed an integrative approach including analysis of modeling simulation results and conducting specifically designed model sensitivity experiments. The novelty of this study is linking synoptic scale storms to large-scale changes in sea ice and atmospheric circulation. The models were used in this study range from the regional fully coupled Arctic climate model HIRHAM-NAOSIM to the ocean-sea ice component model of the Community Earth System Model CESM and the Weather Research and Forecasting (WRF) model. Analysis of HIRHAM-NAOSIM simulation outputs shows regionally dependent variability of storm count with a higher number of storms over the Atlantic side than over the Pacific side. High-resolution simulations also reproduce higher number of storms than lower resolution reanalysis dataset. This is because the high-resolution model may capture more shallow and small size storms. As an integrated consequence, the composite analysis shows that more numerous intense storms produce low-pressure systems centered over the Barents-Kara-Laptev seas and the Chukchi-East Siberian seas, leading to anomalous cyclonic circulation over the Atlantic Arctic Ocean and Pacific Arctic Ocean. Correspondingly, anomalous sea ice transport occurs, enhancing sea ice outflow out of the Barents-Kara-Laptev sea ice and weakening sea ice inflow into the Chukchi-Beaufort seas from the thick ice area north of the Canadian Archipelago. This change in sea ice transport causes a decrease in sea ice concentration and thickness in these two areas. However, energy budget analysis exhibits a decrease in downward net sea ice heat fluxes, reducing sea ice melt, when more numerous intense storms occur. This decrease could be attributed to increased cloudiness and destabilized atmospheric boundary layer associated with intense storms, which can result in a decrease in downward shortwave radiation and an increase in upward turbulent heat fluxes. The sea ice-ocean component CICE-POP of Community Earth System Model (CESM) was used to conduct sensitivity experiment to examine impacts of two selected storms on sea ice. CICE-POP is generally able to simulate the observed spatial distribution of the Arctic sea-ice concentration, thickness, and motion, and interannual variability of the Arctic sea ice area for the period 1979 to 2011. However, some biases still exit, including overestimated sea-ice drift speeds, particularly in the Transpolar Drift Stream, and overestimated sea-ice concentration in the Atlantic Arctic but slightly underestimated sea ice concentration in the Pacific Arctic. Analysis of CICE-POP sensitivity experiments suggests that dynamic forcing associated with the storms plays more important driving role in causing sea ice changes than thermodynamics does in the case of storm in March 2011, while both thermodynamic and dynamic forcings have comparable impacts on sea ice decrease in the case of the August 2012. In case of March 2011 storm, increased surface winds caused the reduction of sea ice area in the Barents and Kara Seas by forcing sea ice to move eastward. Sea ice reduction was primarily driven by mechanical processes rather than ice melting. On the contrary, the case study of August 2012 storm, that occurred during the Arctic summer, exemplified the case of equal contribution of mechanical sea ice redistribution of sea ice in the Chukchi - East Siberian - Beaufort seas and melt in sea ice reduction. To understand the impacts of the changed Arctic environment on storm dynamics, we carried out WRF model simulations for a selected Arctic storm that occurred in March 2011. Model output highlight the importance of both increased surface turbulent heat fluxes due to sea ice retreat and self-enhanced warm and moist air advection from the North Atlantic into the Arctic. These external forcing factor and internal dynamic process sustain and even strengthen atmospheric baroclinicity, supporting the storm to develop and intensify. Additional sensitivity experiments further suggest that latent heat release resulting from condensation/precipitation within the storm enhances baroclinicity aloft and, in turn, causes a re-intensification of the storm from its decaying phase.

Author: Lorenzo Zampieri
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
In addition to observations and lab experiments, the scientific investigation of the Arctic and Antarctic sea ice is conducted through the employment of geophysical models. These models describe in a numerical framework the physical behavior of sea ice and its interactions with the atmosphere, ocean, and polar biogeochemical systems. Sea-ice models find application in the quantification of the past, present, and future sea-ice evolution, which becomes particularly relevant in the context of a warming climate system that causes the reduction of the Arctic sea ice cover. Because of the sea-ice decline, the navigation in the Arctic ocean increased substantially in the recent past, a trend that is expected to continue in the next decades and that requires the formulation of reliable sea-ice predictions at various timescales. Sea-ice predictions can be delivered by modern forecast systems that feature dynamical sea-ice models. The simulation of sea ice is at the center of this thesis: A coupled climate model with a simple sea-ice component is used to quantify potential impacts of a geoengineering approach termed "Arctic Ice Management"; the skill of current operational subseasonal-to-seasonal sea-ice forecasts, based on global models with a varying degree of sea-ice model complexity, is evaluated; and, lastly, an unstructured-grid ocean model is equipped with state-of-the-art sea-ice thermodynamics to study the impact of sea-ice model complexity on model performance. In chapter 2, I examine the potential of a geoengineering strategy to restore the Arctic sea ice and to mitigate the warming of the Arctic and global climate throughout the 21st century. The results, obtained with a fully coupled climate model, indicate that it is theoretically possible to delay the melting of the Arctic sea ice by ~60 years, but that this does not reduce global warming. In chapters 3 and 4, I assess the skill of global operational ensemble prediction systems in forecasting the evolution of the Arctic and Antarctic sea-ice edge position at subseasonal timescales. I find that some systems produce skillful forecasts more than 1.5 months ahead, but I also find evidence of substantial model biases and issues concerning data assimilation and model formulation. Chapter 5 deals with the impact of sea-ice model complexity on model performance. I present a new formulation of the FESOM2 sea-ice/ocean model with a revised description of the sea-ice thermodynamics, including various parameterizations of physical processes at the subgrid-scale. The model formulation grants substantial modularity in terms of sea-ice physics and resolution. The new system is used for assessing the impact of the sea-ice model complexity on the FESOM2 performance in different atmosphere-forced setups with a specific parameter-tuning approach and a special focus on sea-ice related variables. The results evidence that a more sophisticated model formulation is beneficial for the model representation of the sea-ice concentration and snow thickness, while less relevant for sea-ice thickness and drift. I also highlight a dependence of the model performance on the atmospheric forcing product used as boundary conditions. In the final part of this thesis, I formulate recommendations for future developments in the field of sea-ice modeling, with particular emphasis on FESOM2 and, more generally, on the modeling infrastructure under development at the Alfred Wegener Institute.

Author: Tianjun Zhou
Publisher: Springer Science & Business Media
ISBN: 3642418015
Category : Science
Languages : en
Pages : 468

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Book Description
Coupled climate system models are of central importance for climate studies. A new model known as FGOALS ( the Flexible Global Ocean-Atmosphere-Land System model), has been developed by the Sate Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP, CAS), a first-tier national geophysical laboratory. It serves as a powerful tool, both for deepening our understanding of fundamental mechanisms of the climate system and for making decadal prediction and scenario projections of future climate change. "Flexible Global Ocean-Atmosphere-Land System Model: A Modeling Tool for the Climate Change Research Community” is the first book to offer systematic evaluations of this model’s performance. It is comprehensive in scope, covering both developmental and application-oriented aspects of this climate system model. It also provides an outlook of future development of FGOALS and offers an overview of how to employ the model. It represents a valuable reference work for researchers and professionals working within the related areas of climate variability and change. Prof. Tianjun Zhou, Yongqiang Yu, Yimin Liu and Bin Wang work at LASG, the Institute of Atmospheric Physics, Chinese Academy of Sciences, China.