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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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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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A. Bodas-Salcedo, M. A. Ringer, and A. Jones

Abstract

The partitioning of the earth radiation budget (ERB) between its atmosphere and surface components is of crucial interest in climate studies as it has a significant role in the oceanic and atmospheric general circulation. An analysis of the present-day climate simulation of the surface radiation budget in the atmospheric component of the new Hadley Centre Global Environmental Model version 1 (HadGEM1) is presented, and the simulations are assessed by comparing the results with fluxes derived from satellite data from the International Satellite Cloud Climatology Project (ISCCP) and ground measurements from the Baseline Surface Radiation Network (BSRN).

Comparisons against radiative fluxes from satellite and ground observations show that the model tends to overestimate the surface incoming solar radiation (Ss,d). The model simulates Ss,d very well over the polar regions. Consistency in the comparisons against BSRN and ISCCP-FD suggests that the ISCCP-FD database is a good test for the performance of the surface downwelling solar radiation in climate model simulations. Overall, the simulation of downward longwave radiation is closer to observations than its shortwave counterpart. The model underestimates the downward longwave radiation with respect to BSRN measurements by 6.0 W m−2.

Comparisons of land surface albedo from the model and estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) show that HadGEM1 overestimates the land surface albedo over deserts and over midlatitude landmasses in the Northern Hemisphere in January. Analysis of the seasonal cycle of the land surface albedo in different regions shows that the amplitude and phase of the seasonal cycle are not well represented in the model, although a more extensive validation needs to be carried out.

Two decades of coupled model simulations of the twentieth-century climate are used to look into the model’s simulation of global dimming/brightening. The model results are in line with the conclusions of the studies that suggest that global dimming is far from being a uniform phenomenon across the globe.

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Roland A. Madden and Richard H. Jones

Abstract

No abstract available.

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Guillermo A. Baigorria and James W. Jones

Abstract

Weather generators are tools that create synthetic daily weather data over long periods of time. These tools have also been used for downscaling monthly to seasonal climate forecasts, from global and regional circulation models to daily values for use as inputs for crop and other environmental models. One main limitation of most weather generators is that they do not take into account the spatial structure of weather. Spatial correlation of daily rainfall is important when one aggregates, for example, simulated crop yields or hydrology in a watershed or region. A method was developed to generate realizations of daily rainfall for multiple sites in an area while preserving the spatial and temporal correlations among sites. A two-step method generates rainfall events at multiple sites followed by rainfall amounts at sites where generated rainfall events occur. The generation of rainfall events was based on a new orthogonal Markov chain for discrete distributions. For generating rainfall amounts, a vector of random numbers (from a uniform distribution), of order equal to the number of locations with rainfall events that were generated to occur in a day, was matrix-multiplied by the corresponding factorized correlation matrix to create spatially correlated random numbers. Elements from the resulting vector were transformed to a gamma distribution using cumulative probability functions for each location and rescaled to rainfall amounts. One study area was located in north-central Florida, where correlated rainfall data were generated for seven weather stations to evaluate its performance versus a widely used single-site weather generator. A second area was in North Carolina, where rainfall was generated for 25 weather stations to evaluate the effects of a larger number of stations in other regions. One thousand yearlong replications of daily rainfall data were generated for each area. Monthly spatial correlations of generated daily rainfall events and amounts among all pairs of weather stations closely matched their observed counterparts. For daily rainfall amounts the correlation coefficients between the observed pairwise correlation coefficients and the ones estimated from synthetic data among weather stations were 0.977 for Florida and 0.964 for North Carolina. The performance of the geospatial–temporal (GiST) weather generator was also analyzed by comparing the distributions of lengths of dry and wet spells, joint probabilities, Markov transitional probabilities, distance decay of correlation functions, and regionwide days without rainfall at any station. Multiannual mean and standard deviation of the number of rainy days per month and mean monthly rainfall were also calculated. All comparisons between observed and generated rainfall events and amounts using the GiST weather generator were highly correlated. The root-mean-square errors of pairwise correlation values ranged from 0.05 to 0.11 for rainfall events and from 0.03 to 0.06 for amounts.

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Roland A. Madden and Richard H. Jones
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Peter A. Stott, Gareth S. Jones, and John F. B. Mitchell

Abstract

Current attribution analyses that seek to determine the relative contributions of different forcing agents to observed near-surface temperature changes underestimate the importance of weak signals, such as that due to changes in solar irradiance. Here a new attribution method is applied that does not have a systematic bias against weak signals.

It is found that current climate models underestimate the observed climate response to solar forcing over the twentieth century as a whole, indicating that the climate system has a greater sensitivity to solar forcing than do models. The results from this research show that increases in solar irradiance are likely to have had a greater influence on global-mean temperatures in the first half of the twentieth century than the combined effects of changes in anthropogenic forcings. Nevertheless the results confirm previous analyses showing that greenhouse gas increases explain most of the global warming observed in the second half of the twentieth century.

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G. M. Martin, M. A. Ringer, V. D. Pope, A. Jones, C. Dearden, and T. J. Hinton

Abstract

The atmospheric component of the new Hadley Centre Global Environmental Model (HadGEM1) is described and an assessment of its mean climatology presented. HadGEM1 includes substantially improved representations of physical processes, increased functionality, and higher resolution than its predecessor, the Third Hadley Centre Coupled Ocean–Atmosphere General Circulation Model (HadCM3). Major developments are the use of semi-Lagrangian instead of Eulerian advection for both dynamical and tracer fields; new boundary layer, gravity wave drag, microphysics, and sea ice schemes; and major changes to the convection, land surface (including tiled surface characteristics), and cloud schemes. There is better coupling between the atmosphere, land, ocean, and sea ice subcomponents and the model includes an interactive aerosol scheme, representing both the first and second indirect effects. Particular focus has been placed on improving the processes (such as clouds and aerosol) that are most uncertain in projections of climate change.

These developments lead to a significantly more realistic simulation of the processes represented, the most notable improvements being in the hydrological cycle, cloud radiative properties, the boundary layer, the tropopause structure, and the representation of tracers.

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S. A. Good, G. K. Corlett, J. J. Remedios, E. J. Noyes, and D. T. Llewellyn-Jones

Abstract

The trend in sea surface temperature has been determined from 20 yr of Advanced Very High Resolution Radiometer Pathfinder data (version 5). The data span the period from January 1985 to December 2004, inclusive. The linear trends were calculated to be 0.18° ± 0.04° and 0.17° ± 0.05°C decade−1 from daytime and nighttime data, respectively. However, the measured trends were found to be somewhat smaller if version 4.1 of the Pathfinder data was used, or if the time series of data ended earlier. The influence of El Niño on global temperatures can be seen clearly in the data. However, it was not found to affect the trend measurements significantly. Evidence of cool temperatures after the eruption of Mount Pinatubo in 1991 was also observed.

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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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