[1] Meteorological models were used to retrieve annual accumulation, runoff, and surface mass balance on a 5 km  5 km grid for the Greenland ice sheet for . We present the first such history that provides insight into seasonal and interannual variability, which should prove useful for those studying the ice sheet. Derived runoff was validated by means of a control model run and independent in situ data. Modeled accumulation has already been validated using shallow ice core data. Surface mass balance (SMB) responds rapidly on a yearly basis to changing meteorological (surface air temperature and precipitation) forcing. There are distinct signals in runoff and SMB following three major volcanic eruptions. Runoff losses from the ice sheet were 264 (±26) km 3 yr À1 in 1961-1990 and 372 (±37) km 3 yr À1 in 1998-2003. Significantly rising runoff since the 1990s has been partly offset by increased precipitation. Our best estimate of overall mass balance declined from 22 (±51) km 3 yr À1 in 1961-1990 to À36 (±59) km 3 yr À1 in 1998-2003, which is not statistically significant. Additional dynamical factors that cause an acceleration of ice flow near the margins, and possible enhanced iceberg calving, may have led to a more negative mass balance in the past few years than suggested here. The implication is a significant and accelerating recent contribution from the ice sheet to global sea level rise, with 0.15 mm yr À1 from declining SMB alone over the last 6 years.

Annual and monthly snow accumulation for the Greenland Ice Sheet was derived from ECMWF forecasts [mainly 40-yr ECMWR Re-Analysis (ERA-40)] and further meteorological modeling. Modeled accumulation was validated using 58 ice core accumulation datasets across the ice sheet and was found to be 95% of the observed accumulation on average, with a mean correlation of 0.53 between modeled and observed. Many of the ice core datasets are new and are presented here for the first time. Central and northern interior parts of the ice sheet were found to be ϳ10%-30% too dry in ERA-40, in line with earlier ECMWF analysis, although too much (Ͼ50% locally) snow accumulation was modeled for interior southern parts of Greenland. Nevertheless, 47 of 58 sites show significant correlation in temporal variability of modeled with observed accumulation. The model also captures the absolute amount of snow accumulation at several sites, most notably Das1 and Das2 in southeast Greenland. Mean modeled accumulation over the ice sheet was 0.279 (standard deviation 0.034) m yr Ϫ1 for 1958-2003 with no significant trend for either the ice sheet or any of the core sites. Unusually high accumulation in southeast Greenland in 2002/03 leads the authors to study meteorological synoptic forcing patterns and comment on the prospect of enhanced climate variability leading to more such events as a result of global warming. There is good agreement between precipitation measured at coastal meteorological stations in southern Greenland and accumulation modeled for adjacent regions of the ice sheet. There is no significant persistent relation between the North Atlantic Oscillation index and whole or southern Greenland accumulation.

Abstract. Two-dimensional radiance maps from Channel 9 (∼60-90 hPa) of the Advanced Microwave Sounding Unit (AMSU-A), acquired over southern Scandinavia on 14 January 2003, show plane-wave-like oscillations with a wavelength λ h of ∼400-500 km and peak brightness temperature amplitudes of up to 0.9 K. The wave-like pattern is observed in AMSU-A radiances from 8 overpasses of this region by 4 different satellites, revealing a growth in the disturbance amplitude from 00:00 UTC to 12:00 UTC and a change in its horizontal structure between 12:00 UTC and 20:00 UTC. Forecast and hindcast runs for 14 January 2003 using highresolution global and regional numerical weather prediction (NWP) models generate a lower stratospheric mountain wave over southern Scandinavia with peak 90 hPa temperature amplitudes of ∼5-7 K at 12:00 UTC and a similar horizontal wavelength, packet width, phase structure and time evolution to the disturbance observed in AMSU-A radiances. The wave's vertical wavelength is ∼12 km. These NWP fields are validated against radiosonde wind and temperature profiles and airborne lidar profiles of temperature and aerosol backscatter ratios acquired from the NASA DC-8 during the second SAGE III Ozone Loss and Validation Experiment (SOLVE II). Both the amplitude and phase of the stratospheric mountain wave in the various NWP fields agree well with localized perturbation features in these suborbital measurements. In particular, we show that this wave formed the type II polar stratospheric clouds measured by the DC-8 lidar. To compare directly with the AMSU-A data, we convert these validated NWP temperature fields into swath-scanned brightness temperatures using three-dimensional Channel 9 weighting functions and the actual AMSU-A scan patterns from each of the 8 overpasses of this region. These NWPCorrespondence to: S. D. Eckermann (stephen.eckermann@nrl.navy.mil) based brightness temperatures contain two-dimensional oscillations due to this resolved stratospheric mountain wave that have an amplitude, wavelength, horizontal structure and time evolution that closely match those observed in the AMSU-A data. These comparisons not only verify gravity wave detection and horizontal imaging capabilities for AMSU-A Channel 9, but provide an absolute validation of the anticipated radiance signals for a given three-dimensional gravity wave, based on the modeling of Eckermann and Wu (2006).

Abstract. The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985–2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environmental Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the high performance computing center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE dataset. This dataset is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.

Abstract. The UPSCALE (UK on PRACE: weatherresolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley Centre Global Environment Model 3) atmosphereonly global climate simulations over the period 1985-2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a timeslice methodology to consider conditions at the end of this century.These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environment Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the High Performance Computing Center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage.In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE data set. This data set is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.