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A. Anav
,
P. Friedlingstein
,
M. Kidston
,
L. Bopp
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P. Ciais
,
P. Cox
,
C. Jones
,
M. Jung
,
R. Myneni
, and
Z. Zhu

Abstract

The authors assess the ability of 18 Earth system models to simulate the land and ocean carbon cycle for the present climate. These models will be used in the next Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) for climate projections, and such evaluation allows identification of the strengths and weaknesses of individual coupled carbon–climate models as well as identification of systematic biases of the models. Results show that models correctly reproduce the main climatic variables controlling the spatial and temporal characteristics of the carbon cycle. The seasonal evolution of the variables under examination is well captured. However, weaknesses appear when reproducing specific fields: in particular, considering the land carbon cycle, a general overestimation of photosynthesis and leaf area index is found for most of the models, while the ocean evaluation shows that quite a few models underestimate the primary production.The authors also propose climate and carbon cycle performance metrics in order to assess whether there is a set of consistently better models for reproducing the carbon cycle. Averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles and PDFs from different observed datasets. Although the metrics used in this study allow identification of some models as better or worse than the average, the ranking of this study is partially subjective because of the choice of the variables under examination and also can be sensitive to the choice of reference data. In addition, it was found that the model performances show significant regional variations.

Full access
A. Manderson
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M. D. Rayson
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E. Cripps
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M. Girolami
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J. P. Gosling
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M. Hodkiewicz
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G. N. Ivey
, and
N. L. Jones

Abstract

We present a statistical method for reconstructing continuous background density profiles that embeds incomplete measurements and a physically intuitive density stratification model within a Bayesian hierarchal framework. A double hyperbolic tangent function is used as a parametric density stratification model that captures various pycnocline structures in the upper ocean and offers insight into several density profile characteristics (e.g., pycnocline depth). The posterior distribution is used to quantify uncertainty and is estimated using recent advances in Markov chain Monte Carlo sampling. Temporally evolving posterior distributions of density profile characteristics, isopycnal heights, and nonlinear ocean process models for internal gravity waves are presented as examples of how uncertainty propagates through models dependent on the density stratification. The results show 0.95 posterior interval widths that ranged from 2.5% to 4% of the expected values for the linear internal wave phase speed and 15%–40% for the nonlinear internal wave steepening parameter. The data, collected over a year from a through-the-column mooring, and code, implemented in the software package Stan, accompany the article.

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R. A. Pielke
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L. R. Bernardet
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P. J. Fitzpatrick
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R. F. Hertenstein
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A. S. Jones
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X. Lin
,
J. E. Nachamkin
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U. S. Nair
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J. M. Papineau
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G. S. Poulos
,
M. H. Savoie
, and
P. L. Vidale

In order to assist in comparing the computational techniques used in different models, the authors propose a standardized set of one-dimensional numerical experiments that could be completed for each model. The results of these experiments, with a simplified form of the computational representation for advection, diffusion, pressure gradient term, Coriolis term, and filter used in the models, should be reported in the peer-reviewed literature. Specific recommendations are described in this paper.

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B. W. Golding
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S. P. Ballard
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K. Mylne
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N. Roberts
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A. Saulter
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C. Wilson
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P. Agnew
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L. S. Davis
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J. Trice
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C. Jones
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D. Simonin
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Z. Li
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C. Pierce
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A. Bennett
,
M. Weeks
, and
S. Moseley

The provision of weather forecasts for the London Olympic and Paralympic Games in 2012 offered the opportunity for the Met Office to accelerate the transition to operations of several advanced numerical modeling capabilities and to demonstrate their performance to external scientists. It was also an event that captured public interest, providing an opportunity to educate and build trust in the weather forecasting enterprise in the United Kingdom and beyond. The baseline NWP guidance for the duration of the Olympic Games came from three main configurations of the Met Office Unified Model: global 25-km deterministic, North Atlantic/Europe 18-km ensemble, and U.K. 1.5-km deterministic. The advanced capabilities demonstrated during the Olympic Games consisted of a rapid-update hourly cycle of a 1.5-km grid length configuration for the southern United Kingdom using four-dimensional variational data assimilation (4D-Var) and enhanced observations; a 2.2-km grid length U.K. ensemble; a 333-m grid length configuration of the Unified Model and 250-m configuration of the Simulating Waves Nearshore (SWAN) ocean wave model for Weymouth Bay; and a 12-km grid length configuration of Air Quality in the Unified Model with prognostic aerosols and chemistry. Despite their different levels of maturity, each of the new capabilities provided useful additional guidance to Met Office weather advisors, contributing to an outstanding service to the Olympic Games organizers and the public. The website provided layered access to information about the science and to selected real-time products, substantially raising the profile of Met Office weather forecasting research among the United Kingdom and overseas public.

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N. R. P. Harris
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L. J. Carpenter
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J. D. Lee
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G. Vaughan
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M. T. Filus
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R. L. Jones
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B. OuYang
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J. A. Pyle
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A. D. Robinson
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S. J. Andrews
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A. C. Lewis
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J. Minaeian
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A. Vaughan
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J. R. Dorsey
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M. W. Gallagher
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M. Le Breton
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R. Newton
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C. J. Percival
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H. M. A. Ricketts
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S. J.-B. Bauguitte
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G. J. Nott
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A. Wellpott
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M. J. Ashfold
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J. Flemming
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R. Butler
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P. I. Palmer
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P. H. Kaye
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C. Stopford
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C. Chemel
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H. Boesch
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N. Humpage
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A. Vick
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A. R. MacKenzie
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R. Hyde
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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
W. J. Gutowski Jr.
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P. A. Ullrich
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A. Hall
,
L. R. Leung
,
T. A. O’Brien
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C. M. Patricola
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R. W. Arritt
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M. S. Bukovsky
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K. V. Calvin
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Z. Feng
,
A. D. Jones
,
G. J. Kooperman
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E. Monier
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M. S. Pritchard
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S. C. Pryor
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Y. Qian
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A. M. Rhoades
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A. F. Roberts
,
K. Sakaguchi
,
N. Urban
, and
C. Zarzycki
Full access
W. J. Gutowski Jr
,
P. A. Ullrich
,
A. Hall
,
L. R. Leung
,
T. A. O’Brien
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C. M. Patricola
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R. W. Arritt
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M. S. Bukovsky
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K. V. Calvin
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Z. Feng
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A. D. Jones
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G. J. Kooperman
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E. Monier
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M. S. Pritchard
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S. C. Pryor
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Y. Qian
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A. M. Rhoades
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A. F. Roberts
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K. Sakaguchi
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N. Urban
, and
C. Zarzycki

ABSTRACT

Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.

Free access
D. N. Williams
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R. Ananthakrishnan
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D. E. Bernholdt
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S. Bharathi
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D. Brown
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M. Chen
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A. L. Chervenak
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L. Cinquini
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R. Drach
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I. T. Foster
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P. Fox
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D. Fraser
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J. Garcia
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S. Hankin
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P. Jones
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D. E. Middleton
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J. Schwidder
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R. Schweitzer
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R. Schuler
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A. Shoshani
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F. Siebenlist
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A. Sim
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W. G. Strand
,
M. Su
, and
N. Wilhelmi

By leveraging current technologies to manage distributed climate data in a unified virtual environment, the Earth System Grid (ESG) project is promoting data sharing between international research centers and diverse users. In transforming these data into a collaborative community resource, ESG is changing the way global climate research is conducted.

Since ESG's production beginnings in 2004, its most notable accomplishment was to efficiently store and distribute climate simulation data of some 20 global coupled ocean-atmosphere models to the scores of scientific contributors to the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC); the IPCC collective scientific achievement was recognized by the award of a 2007 Nobel Peace Prize. Other international climate stakeholders such as the North American Regional Climate Change Assessment Program (NARCCAP) and the developers of the Community Climate System Model (CCSM) and of the Climate Science Computational End Station (CCES) also have endorsed ESG technologies for disseminating data to their respective user communities. In coming years, the recently created Earth System Grid Center for Enabling Technology (ESG-CET) will extend these methods to assist the international climate community in its efforts to better understand the global climate system.

Full access
P. Friedlingstein
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P. Cox
,
R. Betts
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L. Bopp
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W. von Bloh
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V. Brovkin
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P. Cadule
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S. Doney
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M. Eby
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I. Fung
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G. Bala
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J. John
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C. Jones
,
F. Joos
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T. Kato
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M. Kawamiya
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W. Knorr
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K. Lindsay
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H. D. Matthews
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T. Raddatz
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P. Rayner
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C. Reick
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E. Roeckner
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K.-G. Schnitzler
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R. Schnur
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K. Strassmann
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A. J. Weaver
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C. Yoshikawa
, and
N. Zeng

Abstract

Eleven coupled climate–carbon cycle models used a common protocol to study the coupling between climate change and the carbon cycle. The models were forced by historical emissions and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 anthropogenic emissions of CO2 for the 1850–2100 time period. For each model, two simulations were performed in order to isolate the impact of climate change on the land and ocean carbon cycle, and therefore the climate feedback on the atmospheric CO2 concentration growth rate. There was unanimous agreement among the models that future climate change will reduce the efficiency of the earth system to absorb the anthropogenic carbon perturbation. A larger fraction of anthropogenic CO2 will stay airborne if climate change is accounted for. By the end of the twenty-first century, this additional CO2 varied between 20 and 200 ppm for the two extreme models, the majority of the models lying between 50 and 100 ppm. The higher CO2 levels led to an additional climate warming ranging between 0.1° and 1.5°C.

All models simulated a negative sensitivity for both the land and the ocean carbon cycle to future climate. However, there was still a large uncertainty on the magnitude of these sensitivities. Eight models attributed most of the changes to the land, while three attributed it to the ocean. Also, a majority of the models located the reduction of land carbon uptake in the Tropics. However, the attribution of the land sensitivity to changes in net primary productivity versus changes in respiration is still subject to debate; no consensus emerged among the models.

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T. J. Ansell
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P. D. Jones
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R. J. Allan
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D. Lister
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D. E. Parker
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M. Brunet
,
A. Moberg
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J. Jacobeit
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P. Brohan
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N. A. Rayner
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E. Aguilar
,
H. Alexandersson
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M. Barriendos
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T. Brandsma
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N. J. Cox
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P. M. Della-Marta
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A. Drebs
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D. Founda
,
F. Gerstengarbe
,
K. Hickey
,
T. Jónsson
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J. Luterbacher
,
Ø. Nordli
,
H. Oesterle
,
M. Petrakis
,
A. Philipp
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M. J. Rodwell
,
O. Saladie
,
J. Sigro
,
V. Slonosky
,
L. Srnec
,
V. Swail
,
A. M. García-Suárez
,
H. Tuomenvirta
,
X. Wang
,
H. Wanner
,
P. Werner
,
D. Wheeler
, and
E. Xoplaki

Abstract

The development of a daily historical European–North Atlantic mean sea level pressure dataset (EMSLP) for 1850–2003 on a 5° latitude by longitude grid is described. This product was produced using 86 continental and island stations distributed over the region 25°–70°N, 70°W–50°E blended with marine data from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS). The EMSLP fields for 1850–80 are based purely on the land station data and ship observations. From 1881, the blended land and marine fields are combined with already available daily Northern Hemisphere fields. Complete coverage is obtained by employing reduced space optimal interpolation. Squared correlations (r2) indicate that EMSLP generally captures 80%–90% of daily variability represented in an existing historical mean sea level pressure product and over 90% in modern 40-yr European Centre for Medium-Range Weather Forecasts Re-Analyses (ERA-40) over most of the region. A lack of sufficient observations over Greenland and the Middle East, however, has resulted in poorer reconstructions there. Error estimates, produced as part of the reconstruction technique, flag these as regions of low confidence. It is shown that the EMSLP daily fields and associated error estimates provide a unique opportunity to examine the circulation patterns associated with extreme events across the European–North Atlantic region, such as the 2003 heat wave, in the context of historical events.

Full access