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P. A. Jones
and
A. Henderson-Sellers

Abstract

Historical records of mean monthly cloud amount over Australia have been studied to determine whether there is any long-term trend. Of 318 stations with more than 30 years of data, 252 show an increase and 66 a decrease. The cloud amount shows a rise of 5% between 1910 and 1989, when averaged over all stations. The trend is not uniform, however, with a slight fall in cloud between 1910 and 1930 and with most of the rise between 1930 and 1980. Sunshine records were used to check the cloud record for systematic errors. Monthly average cloud and sunshine fractions are correlated with coefficient r=−0.87 and with best-fit slope −1.00. The sum of cloud and sunshine fractions is around 1.2, whereas it may be expected that the sun should be 1.0 if the cloud and sunshine fractions are complementary. The sunshine and cloud variations are in close agreement for the period 1950 to 1989. The subset of stations that have sunshine records shows no overall change in cloudiness or sunshine over this period, with 31 stations showing an increase in cloud and 28 a decrease. An independent dataset of 41 stations, mostly airports, shows no significant trend over the period from 1940 to 1988, with 24 stations showing a decrease in cloud and only 17 showing an increase over this period. It is suggested that there is an overall long-term increase in total cloud amount over Australia, but that it does not occur uniformly for all stations, so that some groups of stations show no increase. However, the overall trend must remain tentative until the reason for the differences between the datasets is clarified.

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P. D. Jones
and
A. Moberg

Abstract

This study is an extensive revision of the Climatic Research Unit (CRU) land station temperature database that is used to produce a gridbox dataset of 5° latitude × 5° longitude temperature anomalies. The new database comprises 5159 station records, of which 4167 have enough data for the 1961–90 period to calculate or estimate the necessary averages. Apart from the increase in station numbers compared to the earlier study in 1994, many station records have had their data replaced by newly homogenized series that have been produced by several recent studies. New versions of all the gridded datasets currently available on the CRU Web site (http://www.cru.uea.ac.uk) have been developed. This includes combinations with marine (sea surface temperature anomalies) data over the oceans and versions with adjustment of the variance of individual gridbox series to remove the effects of changing station numbers through time.

Hemispheric and global temperature averages for land areas developed with the new dataset differ slightly from those developed in 1994. Possible reasons for the differences between the new and the earlier analysis and those from the National Climatic Data Center and the Goddard Institute for Space Studies are discussed. Differences are greatest over the Southern Hemisphere and at the beginnings and ends of each time series and relate to gridbox sizes and data availability. The rate of annual warming for global land areas over the 1901–2000 period is estimated by least squares to be 0.07°C decade−1 (significant at better than the 99.9% level). Warming is not continuous but occurs principally over two periods (about 1920–45 and since 1975). Annual temperature series for the seven continents and the Arctic all show significant warming over the twentieth century, with significant (95%) warming for 1920–44 for North America, the Arctic, Africa, and South America, and all continents except Australia and the Antarctic since 1977. Cooling is significant during the intervening period (1945–76) for North America, the Arctic, and Africa.

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Robert E. Davis
,
Bruce P. Hayden
,
David A. Gay
,
William L. Phillips
, and
Gregory V. Jones

Abstract

The semipermanent subtropical anticyclone over the North Atlantic basin (the “Azores high”) has a major influence on the weather and climate of much of North America, western Europe, and northwestern Africa. The authors develop a climatology of the Azores high by examining its spatial and temporal changes since 1899. Using gridded surface pressure values, anticyclones are identified when the daily pressure is ≥1020 mb and frequencies are tabulated for each half month from 1899 to 1990. Principal components analysis is applied to analyze the anticyclone’s spatial variance structure.

The Azores high is dominated by two spatial modes: a summer pattern, in which high pressure dominates the Atlantic basin, and a winter pattern, in which anticyclones are present over eastern North America and northwestern Africa. Century-long declines in these two modes indicate that there has been a net removal of atmospheric mass over the subtropical Atlantic. Other modes include a meridional versus zonal circulation pattern and omega blocks. Time series of the mean annual principal component scores indicate that meridional flow has been increasing over the Atlantic and that blocking anticyclones have become more prevalent over west-central Europe and less common over the northeastern Atlantic and the British Isles.

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A. Philipp
,
P. M. Della-Marta
,
J. Jacobeit
,
D. R. Fereday
,
P. D. Jones
,
A. Moberg
, and
H. Wanner

Abstract

Reconstructed daily mean sea level pressure patterns of the North Atlantic–European region are classified for the period 1850 to 2003 to explore long-term changes of the atmospheric circulation and its impact on long-term temperature variability in the central European region. Commonly used k-means clustering algorithms resulted in classifications of low quality because of methodological deficiencies leading to local optima by chance for complex datasets. In contrast, a newly implemented clustering scheme combining the concepts of simulated annealing and diversified randomization (SANDRA) is able to reduce substantially the influence of chance in the cluster assignment, leading to partitions that are noticeably nearer to the global optimum and more stable. The differences between conventional cluster analysis and the SANDRA scheme are significant for subsequent analyses of single clusters—in particular, for trend analysis. Conventional indices used to determine the appropriate number of clusters failed to provide clear guidance, indicating that no distinct separation between clusters of circulation types exists in the dataset. Therefore, the number of clusters is determined by an external indicator, the so-called dominance criteria for t-mode principal component analysis. Nevertheless, the resulting partitions are stable for certain numbers of clusters and provide meaningful and reproducible clusters. The resulting types of pressure patterns reveal pronounced long-term variability and various significant trends of the time series of seasonal cluster frequency. Tentative estimations of central European temperature changes based solely on seasonal cluster frequencies can explain between 33.9% (summer) and 59.0% (winter) of temperature variance on the seasonal time scale. However, the signs of long-term changes in temperature are correctly reproduced even on multidecadal–centennial time scales. Moreover, linear warming trends are reproduced, implying from one-third up to one-half of the observed temperature increase between 1851/52 and 2003 (except for summer, but with significant trends for spring and autumn), indicating that changes in daily circulation patterns contribute to the observed overall long-term warming in the central European region.

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G. P. Können
,
M. Zaiki
,
A. P. M. Baede
,
T. Mikami
,
P. D. Jones
, and
T. Tsukahara

Abstract

Instrumental observations from Dejima (Nagasaki), Japan, taken under the responsibility of the Dutch, covering the periods 1819–28, 1845–58, and 1871–78, have been recovered. The Dejima series overlaps by six months the modern Nagasaki Observatory series, which covers 1878–present. The recovered data extend the start of the instrumental Japanese series back from 1872 to 1819, leaving major gaps during 1829–44 and 1859–71.

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A. Anav
,
P. Friedlingstein
,
M. Kidston
,
L. Bopp
,
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.

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P. Friedlingstein
,
P. Cox
,
R. Betts
,
L. Bopp
,
W. von Bloh
,
V. Brovkin
,
P. Cadule
,
S. Doney
,
M. Eby
,
I. Fung
,
G. Bala
,
J. John
,
C. Jones
,
F. Joos
,
T. Kato
,
M. Kawamiya
,
W. Knorr
,
K. Lindsay
,
H. D. Matthews
,
T. Raddatz
,
P. Rayner
,
C. Reick
,
E. Roeckner
,
K.-G. Schnitzler
,
R. Schnur
,
K. Strassmann
,
A. J. Weaver
,
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
,
P. D. Jones
,
R. J. Allan
,
D. Lister
,
D. E. Parker
,
M. Brunet
,
A. Moberg
,
J. Jacobeit
,
P. Brohan
,
N. A. Rayner
,
E. Aguilar
,
H. Alexandersson
,
M. Barriendos
,
T. Brandsma
,
N. J. Cox
,
P. M. Della-Marta
,
A. Drebs
,
D. Founda
,
F. Gerstengarbe
,
K. Hickey
,
T. Jónsson
,
J. Luterbacher
,
Ø. Nordli
,
H. Oesterle
,
M. Petrakis
,
A. Philipp
,
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.

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L. C. Slivinski
,
G. P. Compo
,
P. D. Sardeshmukh
,
J. S. Whitaker
,
C. McColl
,
R. J. Allan
,
P. Brohan
,
X. Yin
,
C. A. Smith
,
L. J. Spencer
,
R. S. Vose
,
M. Rohrer
,
R. P. Conroy
,
D. C. Schuster
,
J. J. Kennedy
,
L. Ashcroft
,
S. Brönnimann
,
M. Brunet
,
D. Camuffo
,
R. Cornes
,
T. A. Cram
,
F. Domínguez-Castro
,
J. E. Freeman
,
J. Gergis
,
E. Hawkins
,
P. D. Jones
,
H. Kubota
,
T. C. Lee
,
A. M. Lorrey
,
J. Luterbacher
,
C. J. Mock
,
R. K. Przybylak
,
C. Pudmenzky
,
V. C. Slonosky
,
B. Tinz
,
B. Trewin
,
X. L. Wang
,
C. Wilkinson
,
K. Wood
, and
P. Wyszyński

Abstract

The performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a “best estimate” of the weather, including extreme events, it also provides an estimate of its confidence through the use of an ensemble. Surface pressure statistics suggest that these confidence estimates are reliable. Comparisons with independent upper-air observations in the Northern Hemisphere demonstrate that 20CRv3 has skill throughout the twentieth century. Upper-air fields from 20CRv3 in the late twentieth century and early twenty-first century correlate well with full-input reanalyses, and the correlation is predicted by the confidence fields from 20CRv3. The skill of analyzed 500-hPa geopotential heights from 20CRv3 for 1979–2015 is comparable to that of modern operational 3–4-day forecasts. Finally, 20CRv3 performs well on climate time scales. Long time series and multidecadal averages of mass, circulation, and precipitation fields agree well with modern reanalyses and station- and satellite-based products. 20CRv3 is also able to capture trends in tropospheric-layer temperatures that correlate well with independent products in the twentieth century, placing recent trends in a longer historical context.

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