Skillful Coupled Atmosphere-ocean Forecasts on Interannual to Decadal Timescales Using a Linear Inverse Model PDF Download

Author: Lindsey Michelle Taylor
Publisher:
ISBN:
Category :
Languages : en
Pages : 46

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Book Description
Improvements to forecasts on interannual to decadal timescales face two major challenges: (1) consistently initializing the coupled system so that variability is not dominated by initial imbalances, and (2) having a large sample of different initial conditions on which to test forecast skill. The second challenge requires consideration of time periods not only outside the recent period of intensive ocean observation, but also before the instrumental era, which increases the importance of the first challenge. Forecasting atmospheric and oceanic conditions prior to the 1850s isolates internally generated sources of variability by removing the majority of anthropogenic forcing, yet the sparse observational record cannot capture low-frequency variability, further emphasizing the importance of both challenges and paleoclimate proxy data. This research addresses these two challenges by using a multivariate linear inverse model (LIM) and recent data assimilation (DA) results that extend the observational record with annually-resolved atmospheric and oceanic variables via a low-cost forecast that taps into ocean memory. The reconstructions provide data throughout the last millennium to initialize, validate, and calibrate the LIM. This work tests the forecast skill of LIMs trained on GCM simulations and on paleo-data assimilated reconstructions. Forecasts are initialized and verified on the reconstructions over 1000-2000 C.E. Both the DA and GCM-analog LIMs are found to have skill on interannual to decadal timescales that surpasses damped persistence for global mean sea surface temperature, as well as widespread significant positive spatial skill for 1-year forecasts of all atmosphere and ocean variables. For cross validation on global mean instrumental data, the LIM trained on paleo-data outperforms a LIM trained on the CCSM4 last millennium simulation beyond 4-year lead forecasts, with the CCSM4-LIM reaching climatological variance before the paleo-informed LIM. The paleo-data LIM requires consistent OHC states that, when provided, increase forecast skill outperformance over the GCM-informed LIMs.

Author: Walter Andre Perkins
Publisher:
ISBN:
Category :
Languages : en
Pages : 129

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Book Description
Coupled interactions between oceans and the atmosphere are fundamental to low-frequency variability of the Earth System. While the instrumental record provides an account of this coupled variability over time, the length of record often hinders investigation of the mechanisms of variability on decadal and longer timescales. Paleoclimate data assimilation offers an objective method to investigate dynamic field variability of the past constrained by climate proxies and climate model information. This dissertation presents results from coupled atmosphere-ocean field reconstructions over the last millennium using online data assimilation (DA). To achieve online DA-based reconstructions, we implement and examine a linear inverse model (LIM) as a climate model forecast approximation to constrain temporal dynamics of coupled fields. We find LIMs skillfully capture underlying dynamics from coupled global climate models (GCMs) for ensemble climate forecasts. Additionally, the efficiency allows us to perform experiments using large ensembles over long periods, which is not possible with GCMs. When employing LIMs as a forecast model for online paleoclimate DA, we find reconstructions display significantly improved consistency for upper-ocean heat content variability and that they maintain dynamical consistency for specific field relationships when less proxy information is available. These reconstructions also validate well against instrumental ocean data for both spatial and aggregate measures. We find that the reconstructed large-scale temperature averages tend to be cooler than previous reconstructions, especially during the early period (1000-1200 C.E.). However, despite cooler global-scale temperatures, we find early periods of decadal-scale warmth over high-latitude Europe in agreement with previous documentary and proxy-based evidence. Overall, the annually-resolved multivariate reconstructions produced in this dissertation present a more comprehensive account of low-frequency atmosphere-ocean variability over the last millennium. Furthermore, the generality of the presented methodology allows for continued refinement of the reconstruction product over time as the availability of proxy information grows and GCMs improve.

Author: Daniela Faggiani Dias
Publisher:
ISBN:
Category :
Languages : en
Pages : 164

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Book Description
Climate variations on seasonal to decadal time scales can have enormous social, economical and environmental impacts. As such, the ability to make skilful and reliable climate predictions at these time scales offers many benefits for climate preparedness, adaptation and resilience. In the recent years, major progress has been made in the development of such predictions with the advent of simulations with global climate models that are initialized from the current climate state. However, many challenges remain including an understanding of the underlying physical mechanisms for skilful predictions and whether such predictions could be improved. The purpose of this thesis is to establish new benchmarks for seasonal to decadal predictions in diverse components of the climate system and to provide some pieces of evidence that help to understand what are the drivers for these predictable patterns. Specifically, we use a suite of empirical models to perform predictions of oceanic and atmospheric variables together with initialized climate predictions to: 1. Understand the contribution of remote and local factors to the predictability of North and Tropical Pacific Oceans Sea Surface Temperature and Land Surface Temperature over Western North America; 2. Provide a higher baseline level skill for the state-of-art global prediction systems, from seasonal to decadal time scales; 3. Explore possible sources of errors in the global climate model simulations using statistical predictive models. First, we isolate contributions to the forecast skill from different spatial and time scales in the Pacific Ocean using a Liner Inverse Modelling (LIM) approach, showing the importance of temporal scale interactions in improving the predictions on decadal time scales. Specifically, we show that the Extratropical North Pacific is a source of predictability for the tropics on seasonal to interannual time scales, while the tropics enhance the forecast skill for the decadal component. We then show that the skill for an empirically-built LIM is comparable to and sometimes better than that from two state-of-art global prediction systems, from seasonal to decadal timescales and for several regions around the globe. These results indicate that the evolution of the system in those areas may not be not fully driven by unpredictable dynamics and that there may be some room for improvement in the dynamical models predictions, given that a low-dimensional linear model is able to generate better skill than the fully-coupled nonlinear model. Bearing that in mind, we use the LIM linear feedback matrix to explore possible sources of errors in the dynamical model simulations and we find that some of the simulated atmospheric and oceanic local and remote feedbacks differ in several key regions from that obtained with observations. These results may indicate sources of error in the dynamical models and therefore in its prediction skill that merit focused attention. We then investigate the role of remote and local predictors in seasonal predictors of minimum and maximum air temperatures over the Western North America, using a Canonical Correlation Analysis approach. We show that remote predictors, in the form of Pacific climate modes, provide the best predictive skill for temperature over land, particularly during wintertime. Lastly, considering that persistence is the widely-used measure when evaluating the predictive skill for dynamical models, we suggest the use of CCA as a much higher benchmark for seasonal predictions of land surface air temperatures.

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: Andrew Robertson
Publisher: Elsevier
ISBN: 012811715X
Category : Science
Languages : en
Pages : 588

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Book Description
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

Author: Jason Curtis Goodman
Publisher:
ISBN:
Category :
Languages : en
Pages : 151

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Author: Gang Wang
Publisher:
ISBN:
Category :
Languages : en
Pages : 171

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Book Description
The Southern Ocean has a critical influence on the global climate, and any long-term variability in the Southern Ocean can have both regional and global impacts significantly. However, sparse observations limit the study of the long-term variation. To test the quality of models simulating the natural sea surface temperature (SST) variability, the SST variability in the global oceans is evaluated in simulations of the Climate Model Intercomparison Project Phase 3 (CMIP3) and CMIP5 models. The result shows that some models demonstrate good skill in simulating the observed spatial structure of the SST variability in the tropical domains and less so in the extra-tropical domains. The CMIP5 ensemble exhibits some improvement over the CMIP3 ensemble, mostly in the tropical domains on SST variability simulation. Further, the spatial structure of the SST modes of the CMIP3 and CMIP5 super ensemble is more realistic than any single model, which is mostly used for the following study. Several SST leading modes in the Southern Ocean are discussed on decadal and even larger time scales using CMIP5 data set based on EOF analysis. We compare the modes against several simple null hypotheses, such as isotropic diffusion (red noise) and a Slab Ocean model, to investigate the sources of decadal variability and the factors affecting the propagation and decay of long-term anomalies. The result reveals that the annular mode with largest amplitudes in the Pacific, the basin-wide monopole mode and South Pacific dipole are the principle patterns with low-frequency variability, which contain the dual effects of internal intrinsic processes as well as external forcing and teleconnections. The annular mode is mostly affected by El Niño Southern Oscillation (ENSO) via teleconnection especially in the South Pacific domain and by local Southern Annular Mode (SAM) over the whole Southern Ocean. The monopole mode and South Pacific dipole mode, while they both demonstrate pronounced multi-decadal and longer time scales variability, are firstly inducted by the Wave-3 patterns in the atmosphere and further developed via ocean dynamics. The causes and characteristics of interannual-decadal SST variability in the Southern Ocean are further investigated with an ocean general circulation model and a simplified band ocean model. Possible factors are examined affecting the generation, propagation and decay of long-term anomalies with a series of sensitivity experiments. We found that the atmospheric forcing not only affects the SST modes on shorter time-scales directly, but also shows its influence on longer time scales via air-sea interaction, amplification and oceanic feedback. The deep mixed layer in the Southern Ocean is an essential element to maintain the long-term SST variability. The ocean dynamics connect the entire ocean and create the homogeneous-like spatial patterns. The ocean advection is the key factor to create SST spectral structure, which concentrates the spectrum on interannnual scale synchronizing with the transport of Antarctic Circumpolar Current (ACC).

Author: National Research Council
Publisher: National Academies Press
ISBN: 0309174325
Category : Science
Languages : en
Pages : 621

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Book Description
How can we understand and rise to the environmental challenges of global change? One clear answer is to understand the science of global change, not solely in terms of the processes that control changes in climate and the composition of the atmosphere, but in how ecosystems and human society interact with these changes. In the last two decades of the twentieth century, a number of such research effortsâ€"supported by computer and satellite technologyâ€"have been launched. Yet many opportunities for integration remain unexploited, and many fundamental questions remain about the earth's capacity to support a growing human population. This volume encourages a renewed commitment to understanding global change and sets a direction for research in the decade ahead. Through case studies the book explores what can be learned from the lessons of the past 20 years and what are the outstanding scientific questions. Highlights include: Research imperatives and strategies for investigators in the areas of atmospheric chemistry, climate, ecosystem studies, and human dimensions of global change. The context of climate change, including lessons to be gleaned from paleoclimatology. Human responses toâ€"and forcing ofâ€"projected global change. This book offers a comprehensive overview of global change research to date and provides a framework for answering urgent questions.

Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309467578
Category : Science
Languages : en
Pages : 717

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Book Description
We live on a dynamic Earth shaped by both natural processes and the impacts of humans on their environment. It is in our collective interest to observe and understand our planet, and to predict future behavior to the extent possible, in order to effectively manage resources, successfully respond to threats from natural and human-induced environmental change, and capitalize on the opportunities â€" social, economic, security, and more â€" that such knowledge can bring. By continuously monitoring and exploring Earth, developing a deep understanding of its evolving behavior, and characterizing the processes that shape and reshape the environment in which we live, we not only advance knowledge and basic discovery about our planet, but we further develop the foundation upon which benefits to society are built. Thriving on Our Changing Planet presents prioritized science, applications, and observations, along with related strategic and programmatic guidance, to support the U.S. civil space Earth observation program over the coming decade.

Author: Tim Palmer
Publisher: Cambridge University Press
ISBN: 9781107414853
Category : Science
Languages : en
Pages : 0

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Book Description
The topic of predictability in weather and climate has advanced significantly in recent years, both in understanding the phenomena that affect weather and climate and in techniques used to model and forecast them. This book, first published in 2006, brings together some of the world's leading experts on predicting weather and climate. It addresses predictability from the theoretical to the practical, on timescales from days to decades. Topics such as the predictability of weather phenomena, coupled ocean-atmosphere systems and anthropogenic climate change are among those included. Ensemble systems for forecasting predictability are discussed extensively. Ed Lorenz, father of chaos theory, makes a contribution to theoretical analysis with a previously unpublished paper. This well-balanced volume will be a valuable resource for many years. High-calibre chapter authors and extensive subject coverage make it valuable to people with an interest in weather and climate forecasting and environmental science, from graduate students to researchers.