SUMMARY 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 * Corresponding author: European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9AX, UK. e-mail: adrian.simmons@ecmwf. 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.

This study investigates in detail the spatial correlations of random errors in Atmospheric Motion Vectors (AMVs). A good specification of the observation error is essential to assimilate any kind of observation for Numerical Weather Prediction in a near-optimal way. For AMVs, height assignment, quality control procedures, and other factors introduce spatially correlated errors. The spatial structure of the error correlations is investigated based on a one-year dataset of pairs of collocations between AMVs and radiosonde observations. Assuming spatially uncorrelated sonde errors, the spatial AMV error correlations are obtained over dense sonde networks. Results for operational IR and WV wind datasets from METEOSAT-5 and 7, GOES-8 and 10, and GMS-5 are presented. Winds from all five datasets show statistically significant spatial error correlations for distances up to about 800 km, with little difference between satellites, channels, or vertical levels. Broader correlations are found for tropical regions. The correlations exhibit anisotropic structures with, for instance, longer correlation scales in South-North direction for the v-wind component. The study estimates the spatially correlated part of the annual mean AMV wind component error for high-level Northern Hemisphere winds as about 2.7-3.5 m/s. The findings have a number of important implications for the use of AMVs in data assimilation.

16Global simulations with 1.45 km grid-spacing are presented that were per-17 formed with the Integrated Forecasting System (IFS) of the European Cen-18 tre for Medium-Range Weather Forecasts (ECMWF). Simulations are un-19 coupled (without ocean, sea-ice or wave model), using 62 or 137 vertical lev-20 els and the full complexity of weather forecast simulations including recent 21 date initial conditions, real-world topography, and state-of-the-art physical 22 parametrizations and diabatic forcing including shallow convection, turbu-23 lent diffusion, radiation and five categories for the water substance (vapour, 24 liquid, ice, rain, snow). Simulations are evaluated with regard to computa-25 tional efficiency and model fidelity. Scaling results are presented that were 26 performed on the fastest supercomputer in Europe -Piz Daint (Top 500, 27 Nov 2018). Important choices for the model configuration at this unprece-28 dented resolution for the IFS are discussed such as the use of hydrostatic 29 and non-hydrostatic equations or the time resolution of physical phenomena 30 which is defined by the length of the time step. 31 Our simulations indicate that the IFS model -based on spectral trans-32 forms with a semi-implicit, semi-Lagrangian time-stepping scheme in con-33 trast to more local discretisation techniques -can provide a meaningful 34 baseline reference for O(1) km global simulations.35 1

SUMMARYThis paper presents the operational implementation of a 1D+4D-Var assimilation system of rain-affected satellite observations at ECMWF performed on 28 June 2005. The first part describes the methodology and performance analysis of the 1D-Var retrieval scheme in clouds and precipitation that uses Special Sensor Microwave/Imager (SSM/I) microwave radiance observations for the estimation of total-column water vapour (TCWV). This part describes the technical implementation of the TCWV observations in 4D-Var as well as the impact analysis.The effect of the TCWV observations implied by precipitation on the 4D-Var analyses is significant and the total information content is comparable to that of the SSM/I, High-resolution InfraRed Sounder and Advanced Microwave Sounding Unit (AMSU-B) radiances. Regions with systematic drying in the analysis persist throughout the forecast while moistening is removed by precipitation after 1-2 days. The corresponding divergence increments reflect the feedback between moisture and dynamics. Forecast evaluation using model analyses exhibits mostly positive relative-humidity forecast scores, in particular at 700 hPa and in the Tropics. Some short-term negative forecast scores are observed for geopotential near 1000 hPa and in the southern hemisphere between days 2-4. Wind scores vary greatly between regions and different forecast lengths. Tropical cyclone tracking forecasts are only slightly affected by a reduced location error spread through the rain assimilation. Comparison to dropsonde observations of wind and temperature shows improvement as does TCWV analysis validation against independent observations from Jason radiometer data. The system has been implemented operationally in June 2005 and will be further developed towards a direct 4D-Var assimilation of radiances in clouds and precipitation.

In an attempt to advance the understanding of the Earth's weather and climate by representing deep convection explicitly, we present a global, four-month simulation (November 2018 to February 2019) with ECMWF's hydrostatic Integrated Forecasting System (IFS) at an average grid spacing of 1.4 km. The impact of explicitly simulating deep convection on the atmospheric circulation and its variability is assessed by comparing the 1.4 km simulation to the equivalent well-tested and calibrated global simulations at 9 km grid spacing with and without parametrized deep convection. The explicit simulation of deep convection at 1.4 km results in a realistic large-scale circulation, better representation of convective storm activity, and stronger convective gravity wave activity when compared to the 9 km simulation with parametrized deep convection. Comparison of the 1.4 km simulation to the 9 km simulation without parametrized deep convection shows that switching off deep convection parametrization at a too coarse resolution (i.e., 9 km) generates too strong convective gravity waves. Based on the limited statistics available, improvements to the Madden-Julian Oscillation or tropical precipitation are not observed at 1.4 km, suggesting that other Earth system model components and/or their interaction are important for an accurate representation of these processes and may well need adjusting at deep convection resolving resolutions. Overall, the good agreement of the 1.4 km simulation with the 9 km simulation with parametrized deep convection is remarkable, despite one of the most fundamental parametrizations being turned off at 1.4 km resolution and despite no adjustments being made to the remaining parametrizations. Plain Language Summary We present the world's first global simulation of an entire season of the Earth's atmosphere with 1.4 km average grid spacing and the top of the modeled atmosphere as high as 80 km. Albeit only a single realization due to its considerable computational cost, the resulting model output provides a reference and guidance for future simulations. For illustration we compare to simulations at 9 km grid spacing that represent the state of the art in numerical weather prediction and are still considerably finer when compared to models that are used for climate projections today. Thanks to its unprecedented detail, the simulation output will support future model development and satellite mission planning and may be seen as a prototype contribution to a future digital twin of our Earth.