The ERA-40 re-analysis

ERA-40 is a re-analysis of meteorological observations from September 1957 to August 2002 produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) in collaboration with many institutions. The observing system changed considerably over this re-analysis period, with assimilable data provided by a succession of satellite-borne instruments from the 1970s onwards, supplemented by increasing numbers of observations from aircraft, ocean-buoys and other surface platforms, but with a declining number of radiosonde ascents since the late 1980s. The observations used in ERA-40 were accumulated from many sources. The first part of this paper describes the data acquisition and the principal changes in data type and coverage over the period. It also describes the data assimilation system used for ERA-40. This benefited from many of the changes introduced into operational forecasting since the mid-1990s, when the systems used for the 15-year ECMWF re-analysis (ERA-15) and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis were implemented. Several of the improvements are discussed. General aspects of the production of the analyses are also summarized. A number of results indicative of the overall performance of the data assimilation system, and implicitly of the observing system, are presented and discussed. The comparison of background (short-range) forecasts and analyses with observations, the consistency of the global mass budget, the magnitude of differences between analysis and background fields and the accuracy of medium-range forecasts run from the ERA-40 analyses are illustrated. Several results demonstrate the marked improvement that was made to the observing system for the southern hemisphere in the 1970s, particularly towards the end of the decade. In contrast, the synoptic quality of the analysis for the northern hemisphere is sufficient to provide forecasts that remain skilful well into the medium range for all years. Two particular problems are also examined: excessive precipitation over tropical oceans and a too strong Brewer-Dobson circulation, both of which are pronounced in later years. Several other aspects of the quality of the re-analyses revealed by monitoring and validation studies are summarized. Expectations that the second-generation ERA-40 re-analysis would provide products that are better than those from the firstgeneration ERA-15 and NCEP/NCAR re-analyses are found to have been met in most cases. © Royal Meteorological Society, 2005. The contributions of N. A. Rayner and R. W. Saunders are Crown copyright.

Mersenne numbers

These notes have been issued on a small scale in 1983 and 1987 and on request at other times. This issue follows two items of news. First, WaIter Colquitt and Luther Welsh found the 'missed' Mersenne prime M110503 and advanced the frontier of complete Mp-testing to 139,267. In so doing, they terminated Slowinski's significant string of four consecutive Mersenne primes. Secondly, a team of five established a non-Mersenne number as the largest known prime. This result terminated the 1952-89 reign of Mersenne primes. All the original Mersenne numbers with p < 258 were factorised some time ago. The Sandia Laboratories team of Davis, Holdridge & Simmons with some little assistance from a CRAY machine cracked M211 in 1983 and M251 in 1984. They contributed their results to the 'Cunningham Project', care of Sam Wagstaff. That project is now moving apace thanks to developments in technology, factorisation and primality testing. New levels of computer power and new computer architectures motivated by the open-ended promise of parallelism are now available. Once again, the suppliers may be offering free buildings with the computer. However, the Sandia '84 CRAY-l implementation of the quadratic-sieve method is now outpowered by the number-field sieve technique. This is deployed on either purpose-built hardware or large syndicates, even distributed world-wide, of collaborating standard processors. New factorisation techniques of both special and general applicability have been defined and deployed. The elliptic-curve method finds large factors with helpful properties while the number-field sieve approach is breaking down composites with over one hundred digits. The material is updated on an occasional basis to follow the latest developments in primality-testing large Mp and factorising smaller Mp; all dates derive from the published literature or referenced private communications. Minor corrections, additions and changes merely advance the issue number after the decimal point. The reader is invited to report any errors and omissions that have escaped the proof-reading, to answer the unresolved questions noted and to suggest additional material associated with this subject.

Predicting the functional response of a farmland bird

1. Mechanistic models may be able to predict how changes in agricultural practice influence farmland bird populations. A key component of these models is the link between food and competitor densities and the rate at which birds consume food, i.e. the functional response. 2. This paper tests whether the functional response of a farmland bird, the rook Corvus frugilegus, can be predicted from three parameters: searching speed, food detection distance and handling time. It is often difficult to measure the functional response of farmland birds directly, but it may be possible to measure behavioural parameters more quickly. 3. We performed experiments in which rooks fed on a range of artificial food densities in two grass sward heights. Food detection distance was greater in the shorter sward, but sward height did not influence searching speed or handling time. The functional response could be accurately predicted in both sward heights. 4. We show that the functional response of a farmland bird can be predicted from parameters that can be measured more quickly than the alternative of measuring the functional response directly. This implies that the functional responses of other farmland birds may be predicted using a minimum of information.

The ERA-Interim reanalysis: configuration and performance of the data assimilation system

ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF

Atmospheric conservation properties in ERA-Interim

We study the global atmospheric budgets of mass, moisture, energy and angular momentum in the latest reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF), ERA-Interim, for the period 1989–2008 and compare with ERA-40. Most of the measures we use indicate that the ERA-Interim reanalysis is superior in quality to ERA-40. In ERA-Interim the standard deviation of the monthly mean global dry mass of 0.7 kg m−2 (0.007%) is slightly worse than in ERA-40, and long time-scale variations in dry mass originate predominately in the surface pressure field. The divergent winds are improved in ERA-Interim: the global standard deviation of the time-averaged dry mass budget residual is 10 kg m−2 day−1 and the quality of the cross-equatorial mass fluxes is improved. The temporal variations in the global evaporation minus precipitation (E − P) are too large but the global moisture budget residual is 0.003 kg m−2 day−1 with a spatial standard deviation of 0.3 kg m−2 day−1. Both the E − P over ocean and P − E over land are about 15% larger than the 1.1 Tg s−1 transport of water from ocean to land. The top of atmosphere (TOA) net energy losses are improved, with a value of 1 W m−2, but the meridional gradient of the TOA net energy flux is smaller than that from the Clouds and the Earth's Radiant Energy System (CERES) data. At the surface the global energy losses are worse, with a value of 7 W m−2. Over land however, the energy loss is only 0.5 W m−2. The downwelling thermal radiation at the surface in ERA-Interim of 341 W m−2 is towards the higher end of previous estimates. The global mass-adjusted energy budget residual is 8 W m−2 with a spatial standard deviation of 11 W m−2, and the mass-adjusted atmospheric energy transport from low to high latitudes (the sum for the two hemispheres) is 9.5 PW

An earth-system prediction initiative for the twenty-first century

The necessity and benefits for establishing the international Earth-system Prediction Initiative (EPI) are discussed by scientists associated with the World Meteorological Organization (WMO) World Weather Research Programme (WWRP), World Climate Research Programme (WCRP), International Geosphere–Biosphere Programme (IGBP), Global Climate Observing System (GCOS), and natural-hazards and socioeconomic communities. The proposed initiative will provide research and services to accelerate advances in weather, climate, and Earth system prediction and the use of this information by global societies. It will build upon the WMO, the Group on Earth Observations (GEO), the Global Earth Observation System of Systems (GEOSS) and the International Council for Science (ICSU) to coordinate the effort across the weather, climate, Earth system, natural-hazards, and socioeconomic disciplines. It will require (i) advanced high-performance computing facilities, supporting a worldwide network of research and operational modeling centers, and early warning systems; (ii) science, technology, and education projects to enhance knowledge, awareness, and utilization of weather, climate, environmental, and socioeconomic information; (iii) investments in maintaining existing and developing new observational capabilities; and (iv) infrastructure to transition achievements into operational products and services.