We have studied the muon neutrino and antineutrino quasi-elastic (QEL) scattering reactions (ν μ n → μ − p andν μ p → μ + n) using a set of experimental data collected by the NOMAD Collaboration. We have performed measurements of the cross-section of these processes on a nuclear target (mainly carbon) normalizing it to the total ν μ (ν μ ) charged-current cross section. The results for the flux-averaged QEL cross sections in the (anti)neutrino energy interval 3-100 GeV are σ qel ν μ = (0.92 ± 0.02(stat) ± 0.06(syst)) × 10 −38 cm 2 and σ qel ν μ = (0.81 ± 0.05(stat) ± 0.09(syst)) × 10 −38 cm 2 for neutrino and antineutrino, respectively. The axial mass parameter M A was extracted from the measured quasi-elastic neutrino cross section. The corresponding result is M A = 1.05±0.02(stat)±0.06(syst) GeV. It is consistent with the axial mass values recalculated from the antineutrino cross section and extracted from the pure Q 2 shape analysis of the high purity sample of ν μ quasielastic 2-track events, but has smaller systematic error and should be quoted as the main result of this work. Our measured M A is found to be in good agreement with the world average value obtained in previous deuterium filled bubble chamber experiments. The NOMAD measurement of M A is lower than those recently published by K2K and MiniBooNE Collaborations. However, within the large errors quoted by these experiments on M A , these results are compatible with the more precise NOMAD value.PACS 13.15.+g · 25.30.Pt

Clouds cover about 70% of the Earth's surface and playa dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and Capsule:Cloud properties derived from space observations are immensely valuable for climate studies and model evaluati~n; this assessment has revealed how their statistics may be affected by instrument capabilities and/or retrieval methods but also highlight those well determined.2

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We present the results of a search for ν µ → ν e oscillations in the NOMAD experiment at CERN. The experiment looked for the appearance of ν e in a predominantly ν µ wide-band neutrino beam at the CERN SPS. No evidence for oscillations was found. The 90% confidence limits obtained are m 2 < 0.4 eV 2 for maximal mixing and sin 2 (2θ) < 1.4 × 10 −3 for large m 2. This result excludes the LSND allowed region of oscillation parameters with m 2 10 eV 2 .

The infrared limb spectra of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Envisat satellite include detailed information on tropospheric clouds and polar stratospheric clouds (PSC). However, no consolidated cloud product is available for the scientific community. Here we describe a fast prototype processor for cloud parameter retrieval from MIPAS (MIPclouds). Retrieval of parameters such as cloud top height, temperature, and extinction are implemented, as well as retrieval of microphysical parameters, e.g. effective radius and the integrated quantities over the limb path (surface area density and volume density). MIPclouds classifies clouds as either liquid or ice cloud in the upper troposphere and polar stratospheric clouds types in the stratosphere based on statistical combinations of colour ratios and brightness temperature differences. <br><br> Comparison of limb measurements of clouds with model results or cloud parameters from nadir looking instruments is often difficult due to different observation geometries. We therefore introduce a new concept, the limb-integrated surface area density path (ADP). By means of validation and radiative transfer calculations of realistic 2-D cloud fields as input for a blind test retrieval (BTR), we demonstrate that ADP is an extremely valuable parameter for future comparison with model data of ice water content, when applying limb integration (ray tracing) through the model fields. In addition, ADP is used for a more objective definition of detection thresholds of the applied detection methods. Based on BTR, a detection threshold of ADP = 10⁷ μm² cm⁻² and an ice water content of 10^&minus;5 g m⁻³ is estimated, depending on the horizontal and vertical extent of the cloud. <br><br> Intensive validation of the cloud detection methods shows that the limb-sounding MIPAS instrument has a sensitivity in detecting stratospheric and tropospheric clouds similar to that of space- and ground-based lidars, with a tendency for higher cloud top heights and consequently higher sensitivity for some of the MIPAS detection methods. For the high cloud amount (HCA, pressure levels below 440 hPa) on global scales the sensitivity of MIPAS is significantly greater than that of passive nadir viewers. This means that the high cloud fraction will be underestimated in the ISCCP dataset compared to the amount of high clouds deduced by MIPAS. Good correspondence in seasonal variability and geographical distribution of cloud occurrence and zonal means of cloud top height is found in a detailed comparison with a climatology for subvisible cirrus clouds from the Stratospheric Aerosol and Gas Experiment II (SAGE II) limb sounder. Overall, validation with various sensors shows the need to consider differences in sensitivity, and especially the viewing geometries and field-of-view size, to make the datasets comparable (e.g. applyin...