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E. P. Lozowski
,
R. B. Charlton
,
C. D. Nguyen
, and
J. D. Wilson

Abstract

The Edmonton monthly mean temperature record has been examined using the concept of the cumulative high frequency monthly mean temperature anomaly, I. The time sequence of I is shown to exhibit bounded, oscillatory, nonperiodic behavior.

At times features such as annual and quasi-triennial cycles and sudden reversals are exhibited. Some implications of these observations for interannual climate modeling and forecasting are discussed.

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Lucie J. Lücke
,
Gabriele C. Hegerl
,
Andrew P. Schurer
, and
Rob Wilson

Abstract

Quantifying past climate variation and attributing its causes improves our understanding of the natural variability of the climate system. Tree-ring-based proxies have provided skillful and highly resolved reconstructions of temperature and hydroclimate of the last millennium. However, like all proxies, they are subject to uncertainties arising from varying data quality, coverage, and reconstruction methodology. Previous studies have suggested that biological-based memory processes could cause spectral biases in climate reconstructions. This study determines the effects of such biases on reconstructed temperature variability and the resultant implications for detection and attribution studies. We find that introducing persistent memory, reflecting the spectral properties of tree-ring data, can change the variability of pseudoproxy reconstructions compared to the surrogate climate and resolve certain model–proxy discrepancies. This is especially the case for proxies based on ring-width data. Such memory inflates the difference between the Medieval Climate Anomaly and the Little Ice Age and suppresses and extends the cooling in response to volcanic eruptions. When accounting for memory effects, climate model data can reproduce long-term cooling after volcanic eruptions, as seen in proxy reconstructions. Results of detection and attribution studies show that signals in reconstructions as well as residual unforced variability are consistent with those in climate models when the model fingerprints are adjusted to reflect autoregressive memory as found in tree rings.

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L. C. Shaffrey
,
I. Stevens
,
W. A. Norton
,
M. J. Roberts
,
P. L. Vidale
,
J. D. Harle
,
A. Jrrar
,
D. P. Stevens
,
M. J. Woodage
,
M. E. Demory
,
J. Donners
,
D. B. Clark
,
A. Clayton
,
J. W. Cole
,
S. S. Wilson
,
W. M. Connolley
,
T. M. Davies
,
A. M. Iwi
,
T. C. Johns
,
J. C. King
,
A. L. New
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J. M. Slingo
,
A. Slingo
,
L. Steenman-Clark
, and
G. M. Martin

Abstract

This article describes the development and evaluation of the U.K.’s new High-Resolution Global Environmental Model (HiGEM), which is based on the latest climate configuration of the Met Office Unified Model, known as the Hadley Centre Global Environmental Model, version 1 (HadGEM1). In HiGEM, the horizontal resolution has been increased to 0.83° latitude × 1.25° longitude for the atmosphere, and 1/3° × 1/3° globally for the ocean. Multidecadal integrations of HiGEM, and the lower-resolution HadGEM, are used to explore the impact of resolution on the fidelity of climate simulations.

Generally, SST errors are reduced in HiGEM. Cold SST errors associated with the path of the North Atlantic drift improve, and warm SST errors are reduced in upwelling stratocumulus regions where the simulation of low-level cloud is better at higher resolution. The ocean model in HiGEM allows ocean eddies to be partially resolved, which dramatically improves the representation of sea surface height variability. In the Southern Ocean, most of the heat transports in HiGEM is achieved by resolved eddy motions, which replaces the parameterized eddy heat transport in the lower-resolution model. HiGEM is also able to more realistically simulate small-scale features in the wind stress curl around islands and oceanic SST fronts, which may have implications for oceanic upwelling and ocean biology.

Higher resolution in both the atmosphere and the ocean allows coupling to occur on small spatial scales. In particular, the small-scale interaction recently seen in satellite imagery between the atmosphere and tropical instability waves in the tropical Pacific Ocean is realistically captured in HiGEM. Tropical instability waves play a role in improving the simulation of the mean state of the tropical Pacific, which has important implications for climate variability. In particular, all aspects of the simulation of ENSO (spatial patterns, the time scales at which ENSO occurs, and global teleconnections) are much improved in HiGEM.

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Leo J. Donner
,
Bruce L. Wyman
,
Richard S. Hemler
,
Larry W. Horowitz
,
Yi Ming
,
Ming Zhao
,
Jean-Christophe Golaz
,
Paul Ginoux
,
S.-J. Lin
,
M. Daniel Schwarzkopf
,
John Austin
,
Ghassan Alaka
,
William F. Cooke
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Thomas L. Delworth
,
Stuart M. Freidenreich
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C. T. Gordon
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Stephen M. Griffies
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Isaac M. Held
,
William J. Hurlin
,
Stephen A. Klein
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Thomas R. Knutson
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Amy R. Langenhorst
,
Hyun-Chul Lee
,
Yanluan Lin
,
Brian I. Magi
,
Sergey L. Malyshev
,
P. C. D. Milly
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Vaishali Naik
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Mary J. Nath
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Robert Pincus
,
Jeffrey J. Ploshay
,
V. Ramaswamy
,
Charles J. Seman
,
Elena Shevliakova
,
Joseph J. Sirutis
,
William F. Stern
,
Ronald J. Stouffer
,
R. John Wilson
,
Michael Winton
,
Andrew T. Wittenberg
, and
Fanrong Zeng

Abstract

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for the atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol–cloud interactions, chemistry–climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical system component of earth system models and models for decadal prediction in the near-term future—for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud droplet activation by aerosols, subgrid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with ecosystem dynamics and hydrology. Its horizontal resolution is approximately 200 km, and its vertical resolution ranges approximately from 70 m near the earth’s surface to 1 to 1.5 km near the tropopause and 3 to 4 km in much of the stratosphere. Most basic circulation features in AM3 are simulated as realistically, or more so, as in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks remains problematic, as in AM2. The most intense 0.2% of precipitation rates occur less frequently in AM3 than observed. The last two decades of the twentieth century warm in CM3 by 0.32°C relative to 1881–1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of 0.56° and 0.52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol–cloud interactions, and its warming by the late twentieth century is somewhat less realistic than in CM2.1, which warmed 0.66°C but did not include aerosol–cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud–aerosol interactions to limit greenhouse gas warming.

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