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T. N. Palmer

Meteorology is a wonderfully interdisciplinary subject. But can nonlinear thinking about predictability of weather and climate contribute usefully to issues in fundamental physics? Although this might seem extremely unlikely at first sight, an attempt is made to answer the question positively. The long-standing conceptual problems of quantum theory are outlined, focusing on indeterminacy and nonlocal causality, problems that led Einstein to reject quantum mechanics as a fundamental theory of physics (a glossary of some of the key terms used in this paper is given in the sidebar). These conceptual problems are considered in the light of both low-order chaos and the more radical (and less well known) paradigm of the finite-time predictability horizon associated with the self-similar upscale cascade of uncertainty in a turbulent fluid. The analysis of these dynamical systems calls into doubt one of the key pieces of logic used in quantum nonlocality theorems: that of counterfactual reasoning. By considering an idealization of the upscale cascade (which provides a novel representation of complex numbers and quaternions), a case is made for reinterpreting the quantum wave function as a set of intricately encoded binary sequences. In this reinterpretation, it is argued that the quantum world has no need for dice-playing deities, undead cats, multiple universes, or “spooky action at a distance.”

Full access
T. N. Palmer
and
A. Weisheimer

Abstract

Although the development of seamless prediction systems is becoming increasingly common, there is still confusion regarding the relevance of information from initial-value forecasts for assessing the trustworthiness of the climate system’s response to forcing. A simple system that mimics the real climate system through its regime structure is used to illustrate this potential relevance. The more complex version of this model defines “reality” and a simplified version of the system represents the “model.” The model’s response to forcing is profoundly incorrect. However, the untrustworthiness of the model’s response to forcing can be deduced from the model’s initial-value unreliability. The nonlinearity of the system is crucial in accounting for this result.

Open access
T. N. Palmer
,
F. J. Doblas-Reyes
,
A. Weisheimer
, and
M. J. Rodwell

Trustworthy probabilistic projections of regional climate are essential for society to plan for future climate change, and yet, by the nonlinear nature of climate, finite computational models of climate are inherently deficient in their ability to simulate regional climatic variability with complete accuracy. How can we determine whether specific regional climate projections may be untrustworthy in the light of such generic deficiencies? A calibration method is proposed whose basis lies in the emerging notion of seamless prediction. Specifically, calibrations of ensemblebased climate change probabilities are derived from analyses of the statistical reliability of ensemblebased forecast probabilities on seasonal time scales. The method is demonstrated by calibrating probabilistic projections from the multimodel ensembles used in the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), based on reliability analyses from the seasonal forecast Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) dataset. The focus in this paper is on climate change projections of regional precipitation, though the method is more general.

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J. Shukla
,
T. N. Palmer
,
R. Hagedorn
,
B. Hoskins
,
J. Kinter
,
J. Marotzke
,
M. Miller
, and
J. Slingo

The impending threat of global climate change and its regional manifestations is among the most important and urgent problems facing humanity. Society needs accurate and reliable estimates of changes in the probability of regional weather variations to develop science-based adaptation and mitigation strategies. Recent advances in weather prediction and in our understanding and ability to model the climate system suggest that it is both necessary and possible to revolutionize climate prediction to meet these societal needs. However, the scientific workforce and the computational capability required to bring about such a revolution is not available in any single nation. Motivated by the success of internationally funded infrastructure in other areas of science, this paper argues that, because of the complexity of the climate system, and because the regional manifestations of climate change are mainly through changes in the statistics of regional weather variations, the scientific and computational requirements to predict its behavior reliably are so enormous that the nations of the world should create a small number of multinational high-performance computing facilities dedicated to the grand challenges of developing the capabilities to predict climate variability and change on both global and regional scales over the coming decades. Such facilities will play a key role in the development of next-generation climate models, build global capacity in climate research, nurture a highly trained workforce, and engage the global user community, policymakers, and stakeholders. We recommend the creation of a small number of multinational facilities with computer capability at each facility of about 20 petaflops in the near term, about 200 petaflops within five years, and 1 exaflop by the end of the next decade. Each facility should have sufficient scientific workforce to develop and maintain the software and data analysis infrastructure. Such facilities will enable questions of what resolution, both horizontal and vertical, in atmospheric and ocean models, is necessary for more confident predictions at the regional and local level. Current limitations in computing power have placed severe limitations on such an investigation, which is now badly needed. These facilities will also provide the world's scientists with the computational laboratories for fundamental research on weather–climate interactions using 1-km resolution models and on atmospheric, terrestrial, cryospheric, and oceanic processes at even finer scales. Each facility should have enabling infrastructure including hardware, software, and data analysis support, and scientific capacity to interact with the national centers and other visitors. This will accelerate our understanding of how the climate system works and how to model it. It will ultimately enable the climate community to provide society with climate predictions, which are based on our best knowledge of science and the most advanced technology.

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T. N. Palmer
,
A. Alessandri
,
U. Andersen
,
P. Cantelaube
,
M. Davey
,
P. Délécluse
,
M. Déqué
,
E. Díez
,
F. J. Doblas-Reyes
,
H. Feddersen
,
R. Graham
,
S. Gualdi
,
J.-F. Guérémy
,
R. Hagedorn
,
M. Hoshen
,
N. Keenlyside
,
M. Latif
,
A. Lazar
,
E. Maisonnave
,
V. Marletto
,
A. P. Morse
,
B. Orfila
,
P. Rogel
,
J.-M. Terres
, and
M. C. Thomson

A multi-model ensemble-based system for seasonal-to-interannual prediction has been developed in a joint European project known as DEMETER (Development of a European Multimodel Ensemble Prediction System for Seasonal to Interannual Prediction). The DEMETER system comprises seven global atmosphere–ocean coupled models, each running from an ensemble of initial conditions. Comprehensive hindcast evaluation demonstrates the enhanced reliability and skill of the multimodel ensemble over a more conventional single-model ensemble approach. In addition, innovative examples of the application of seasonal ensemble forecasts in malaria and crop yield prediction are discussed. The strategy followed in DEMETER deals with important problems such as communication across disciplines, downscaling of climate simulations, and use of probabilistic forecast information in the applications sector, illustrating the economic value of seasonal-to-interannual prediction for society as a whole.

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J. L. Kinter III
,
B. Cash
,
D. Achuthavarier
,
J. Adams
,
E. Altshuler
,
P. Dirmeyer
,
B. Doty
,
B. Huang
,
E. K. Jin
,
L. Marx
,
J. Manganello
,
C. Stan
,
T. Wakefield
,
T. Palmer
,
M. Hamrud
,
T. Jung
,
M. Miller
,
P. Towers
,
N. Wedi
,
M. Satoh
,
H. Tomita
,
C. Kodama
,
T. Nasuno
,
K. Oouchi
,
Y. Yamada
,
H. Taniguchi
,
P. Andrews
,
T. Baer
,
M. Ezell
,
C. Halloy
,
D. John
,
B. Loftis
,
R. Mohr
, and
K. Wong

The importance of using dedicated high-end computing resources to enable high spatial resolution in global climate models and advance knowledge of the climate system has been evaluated in an international collaboration called Project Athena. Inspired by the World Modeling Summit of 2008 and made possible by the availability of dedicated high-end computing resources provided by the National Science Foundation from October 2009 through March 2010, Project Athena demonstrated the sensitivity of climate simulations to spatial resolution and to the representation of subgrid-scale processes with horizontal resolutions up to 10 times higher than contemporary climate models. While many aspects of the mean climate were found to be reassuringly similar, beyond a suggested minimum resolution, the magnitudes and structure of regional effects can differ substantially. Project Athena served as a pilot project to demonstrate that an effective international collaboration can be formed to efficiently exploit dedicated supercomputing resources. The outcomes to date suggest that, in addition to substantial and dedicated computing resources, future climate modeling and prediction require a substantial research effort to efficiently explore the fidelity of climate models when explicitly resolving important atmospheric and oceanic processes.

Full access
N. R. P. Harris
,
L. J. Carpenter
,
J. D. Lee
,
G. Vaughan
,
M. T. Filus
,
R. L. Jones
,
B. OuYang
,
J. A. Pyle
,
A. D. Robinson
,
S. J. Andrews
,
A. C. Lewis
,
J. Minaeian
,
A. Vaughan
,
J. R. Dorsey
,
M. W. Gallagher
,
M. Le Breton
,
R. Newton
,
C. J. Percival
,
H. M. A. Ricketts
,
S. J.-B. Bauguitte
,
G. J. Nott
,
A. Wellpott
,
M. J. Ashfold
,
J. Flemming
,
R. Butler
,
P. I. Palmer
,
P. H. Kaye
,
C. Stopford
,
C. Chemel
,
H. Boesch
,
N. Humpage
,
A. Vick
,
A. R. MacKenzie
,
R. Hyde
,
P. Angelov
,
E. Meneguz
, and
A. J. Manning

Abstract

The main field activities of the Coordinated Airborne Studies in the Tropics (CAST) campaign took place in the west Pacific during January–February 2014. The field campaign was based in Guam (13.5°N, 144.8°E), using the U.K. Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 atmospheric research aircraft, and was coordinated with the Airborne Tropical Tropopause Experiment (ATTREX) project with an unmanned Global Hawk and the Convective Transport of Active Species in the Tropics (CONTRAST) campaign with a Gulfstream V aircraft. Together, the three aircraft were able to make detailed measurements of atmospheric structure and composition from the ocean surface to 20 km. These measurements are providing new information about the processes influencing halogen and ozone levels in the tropical west Pacific, as well as the importance of trace-gas transport in convection for the upper troposphere and stratosphere. The FAAM aircraft made a total of 25 flights in the region between 1°S and 14°N and 130° and 155°E. It was used to sample at altitudes below 8 km, with much of the time spent in the marine boundary layer. It measured a range of chemical species and sampled extensively within the region of main inflow into the strong west Pacific convection. The CAST team also made ground-based measurements of a number of species (including daily ozonesondes) at the Atmospheric Radiation Measurement Program site on Manus Island, Papua New Guinea (2.1°S, 147.4°E). This article presents an overview of the CAST project, focusing on the design and operation of the west Pacific experiment. It additionally discusses some new developments in CAST, including flights of new instruments on board the Global Hawk in February–March 2015.

Open access