P. D. Jones

Representing Twentieth-Century Space-Time Climate Variability. Part II: Development of 1901-96 Monthly Grids of Terrestrial Surface Climate

The authors describe the construction of a 0.58 lat‐long gridded dataset of monthly terrestrial surface climate for the period of 1901‐96. The dataset comprises a suite of seven climate elements: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapor pressure, cloud cover, and ground frost frequency. The spatial coverage extends over all land areas, including oceanic islands but excluding Antarctica. Fields of monthly climate anomalies, relative to the 1961‐90 mean, were interpolated from surface climate data. The anomaly grids were then combined with a 1961‐90 mean monthly climatology (described in Part I) to arrive at grids of monthly climate over the 96-yr period. The primary variables—precipitation, mean temperature, and diurnal temperature range—were interpolated directly from station observations. The resulting time series are compared with other coarser-resolution datasets of similar temporal extent. The remaining climatic elements, termed secondary variables,were interpolated from merged datasets comprising station observations and, in regions where there were no station data, synthetic data estimated using predictive relationships with the primary variables. These predictive relationships are described and evaluated. It is argued that this new dataset represents an advance over other products because (i) it has higher spatial resolution than other datasets of similar temporal extent, (ii) it has longer temporal coverage than other products of similar spatial resolution, (iii) it encompasses a more extensive suite of surface climate variables than available elsewhere, and (iv) the construction method ensures that strict temporal fidelity is maintained. The dataset should be of particular relevance to a number of applications in applied climatology, including large-scale biogeochemical and hydrological modeling, climate change scenario construction, evaluation of regional climate models, and comparison with satellite products. The dataset is available from the Climatic Research Unit and is currently being updated to 1998.

Representing Twentieth-Century Space–Time Climate Variability. Part I: Development of a 1961–90 Mean Monthly Terrestrial Climatology

Abstract The construction of a 0.5° lat × 0.5° long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wet-day frequency, mean temperature, diurnal temperature range, vapor pressure, sunshine, cloud cover, ground frost frequency, and wind speed. The climate surfaces have been constructed from a new dataset of station 1961–90 climatological normals, numbering between 19 800 (precipitation) and 3615 (wind speed). The station data were interpolated as a function of latitude, longitude, and elevation using thin-plate splines. The accuracy of the interpolations are assessed using cross validation and by comparison with other climatologies. This new climatology represents an advance over earlier published global terrestrial climatologies in that it is strictly constrained to the period 1961–90, describes an extended suite of surface climate variables, explicitly incorporates elevation...

A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006

We present a European land-only daily high-resolution gridded data set for precipitation and minimum, maximum, and mean surface temperature for the period 1950-2006. This data set improves on previous products in its spatial resolution and extent, time period, number of contributing stations, and attention to finding the most appropriate method for spatial interpolation of daily climate observations. The gridded data are delivered on four spatial resolutions to match the grids used in previous products as well as many of the rotated pole Regional Climate Models (RCMs) currently in use. Each data set has been designed to provide the best estimate of grid box averages rather than point values to enable direct comparison with RCMs. We employ a three-step process of interpolation, by first interpolating the monthly precipitation totals and monthly mean temperature using three-dimensional thin-plate splines, then interpolating the daily anomalies using indicator and universal kriging for precipitation and kriging with an external drift for temperature, then combining the monthly and daily estimates. Interpolation uncertainty is quantified by the provision of daily standard errors for every grid square. The daily uncertainty averaged across the entire region is shown to be largely dependent on the season and number of contributing observations. We examine the effect that interpolation has on the magnitude of the extremes in the observations by calculating areal reduction factors for daily maximum temperature and precipitation events with return periods up to 10 years. Copyright 2008 by the American Geophysical Union.

Surface air temperature and its changes over the past 150 years

We review the surface air temperature record of the past 150 years, considering the homogeneity of the basic data and the standard errors of estimation of the average hemispheric and global estimates. We present global fields of surface temperature change over the two 20-year periods of greatest warming this century, 1925–1944 and 1978–1997. Over these periods, global temperatures rose by 0.37° and 0.32°C, respectively. The twentieth-century warming has been accompanied by a decrease in those areas of the world affected by exceptionally cool temperatures and to a lesser extent by increases in areas affected by exceptionally warm temperatures. In recent decades there have been much greater increases in night minimum temperatures than in day maximum temperatures, so that over 1950–1993 the diurnal temperature range has decreased by 0.08°C per decade. We discuss the recent divergence of surface and satellite temperature measurements of the lower troposphere and consider the last 150 years in the context of the last millennium. We then provide a globally complete absolute surface air temperature climatology on a 1° × 1° grid. This is primarily based on data for 1961–1990. Extensive interpolation had to be undertaken over both polar regions and in a few other regions where basic data are scarce, but we believe the climatology is the most consistent and reliable of absolute surface air temperature conditions over the world. The climatology indicates that the annual average surface temperature of the world is 14.0°C (14.6°C in the Northern Hemisphere (NH) and 13.4°C for the Southern Hemisphere). The annual cycle of global mean temperatures follows that of the land-dominated NH, with a maximum in July of 15.9°C and a minimum in January of 12.2°C.

Hemispheric and large-scale surface air temperature variations: An extensive revision and an update to 2001

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 58 latitude 3 58 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 0.078C decade21 (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.

Clinical Presentation, Etiology, and Outcome of Infective Endocarditis in the 21st Century: The International Collaboration on Endocarditis–Prospective Cohort Study

BACKGROUND We sought to provide a contemporary picture of the presentation, etiology, and outcome of infective endocarditis (IE) in a large patient cohort from multiple locations worldwide. METHODS Prospective cohort study of 2781 adults with definite IE who were admitted to 58 hospitals in 25 countries from June 1, 2000, through September 1, 2005. RESULTS The median age of the cohort was 57.9 (interquartile range, 43.2-71.8) years, and 72.1% had native valve IE. Most patients (77.0%) presented early in the disease (<30 days) with few of the classic clinical hallmarks of IE. Recent health care exposure was found in one-quarter of patients. Staphylococcus aureus was the most common pathogen (31.2%). The mitral (41.1%) and aortic (37.6%) valves were infected most commonly. The following complications were common: stroke (16.9%), embolization other than stroke (22.6%), heart failure (32.3%), and intracardiac abscess (14.4%). Surgical therapy was common (48.2%), and in-hospital mortality remained high (17.7%). Prosthetic valve involvement (odds ratio, 1.47; 95% confidence interval, 1.13-1.90), increasing age (1.30; 1.17-1.46 per 10-year interval), pulmonary edema (1.79; 1.39-2.30), S aureus infection (1.54; 1.14-2.08), coagulase-negative staphylococcal infection (1.50; 1.07-2.10), mitral valve vegetation (1.34; 1.06-1.68), and paravalvular complications (2.25; 1.64-3.09) were associated with an increased risk of in-hospital death, whereas viridans streptococcal infection (0.52; 0.33-0.81) and surgery (0.61; 0.44-0.83) were associated with a decreased risk. CONCLUSIONS In the early 21st century, IE is more often an acute disease, characterized by a high rate of S aureus infection. Mortality remains relatively high.

InterPro in 2011: new developments in the family and domain prediction database

InterPro (http://www.ebi.ac.uk/interpro/) is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.

High-resolution palaeoclimatic records for the last millennium: interpretation, integration and comparison with General Circulation Model control-run temperatures:

Palaeoclimatology provides our only means of assessing climatic variations before the beginning of instrumental records. The various proxy variables used, however, have a number of limitations which must be adequately addressed and understood. Besides their obvious spatial and seasonal limitations, different proxies are also potentially limited in their ability to represent climatic variations over a range of different timescales. Simple correlations with instrumental data over the period since ad 1881 give some guide to which are the better proxies, indicating that coral- and ice-core-based reconstructions are poorer than tree-ring and historical ones. However, the quality of many proxy time series can deteriorate during earlier times. Suggestions are made for assessing proxy quality over longer periods than the last century by intercomparing neighbouring proxies and, by comparisons with less temporally resolved proxies such as borehole temperatures. We have averaged 17 temperature reconstructions (representing various seasons of the year), all extending back at least to the mid-seventeenth century, to form two annually resolved hemispheric series (NH10 and SH7). Over the 1901–91 period, NH10 has 36% variance in common with average NH summer (June to August) temperatures and 70% on decadal timescales. SH7 has 16% variance in common with average SH summer (December to February) temperatures and 49% on decadal timescales, markedly poorer than the reconstructed NH series. The coldest year of the millennium over the NH is ad 1601, the coldest decade 1691–1700 and the seventeenth is the coldest century. A Principal Components Analysis (PCA) is performed on yearly values for the 17 reconstructions over the period ad 1660–1970. The correlation between PC1 and NH10 is 0.92, even though PC1 explains only 13.6% of the total variance of all 17 series. Similar PCA is performed on thousand-year-long General Circulation Model (GCM) data from the Geophysical Fluid Dynamics Laboratory (GFDL) and the Hadley Centre (HADCM2), sampling these for the same locations and seasons as the proxy data. For GFDL, the correlation between its PC1 and its NH10 is 0.89, while for HADCM2 the PCs group markedly differently. Cross-spectral analyses are performed on the proxy data and the GFDL model data at two different frequency bands (0.02 and 0.03 cycles per year). Both analyses suggest that there is no large-scale coherency in the series on these timescales. This implies that if the proxy data are meaningful, it should be relatively straightforward to detect a coherent near-global anthropogenic signal in surface temperature data.

A New Perspective on Recent Global Warming: Asymmetric Trends of Daily Maximum and Minimum Temperature

Abstract Monthly mean maximum and minimum temperatures for over 50% (10%) of the Northern (Southern) Hemisphere landmass, accounting for 37% of the global landmass, indicate that the rise of the minimum temperature has occurred at a rate three times that of the maximum temperature during the period 1951–90 (0.84°C versus 0.28°C). The decrease of the diurnal temperature range is approximately equal to the increase of mean temperature. The asymmetry is detectable in all seasons and in most of the regions studied. The decrease in the daily temperature range is partially related to increases in cloud cover. Furthermore, a large number of atmospheric and surface boundary conditions are shown to differentially affect the maximum and minimum temperature. Linkages of the observed changes in the diurnal temperature range to large-scale climate forcings, such as anthropogenic increases in sulfate aerosols, greenhouse gases, or biomass burning (smoke), remain tentative. Nonetheless, the observed decrease of the diur...

HOMOGENEITY ADJUSTMENTS OF IN SITU ATMOSPHERIC CLIMATE DATA: A REVIEW

Long-term in situ observations are widely used in a variety of climate analyses. Unfortunately, most decade- to century-scale time series of atmospheric data have been adversely impacted by inhomogeneities caused by, for example, changes in instrumentation, station moves, changes in the local environment such as urbanization, or the introduction of different observing practices like a new formula for calculating mean daily temperature or different observation times. If these inhomogeneities are not accounted for properly, the results of climate analyses using these data can be erroneous. Over the last decade, many climatologists have put a great deal of effort into developing techniques to identify inhomogeneities and adjust climatic time series to compensate for the biases produced by the inhomogeneities. It is important for users of homogeneity-adjusted data to understand how the data were adjusted and what impacts these adjustments are likely to make on their analyses. And it is important for developers of homogeneity-adjusted data sets to compare readily the different techniques most commonly used today. Therefore, this paper reviews the methods and techniques developed for homogeneity adjustments and describes many different approaches and philosophies involved in adjusting in situ climate data.