Solar system

Abstract:

The Rosetta spacecraft accomplished a flyby of Mars on its way to 67P/Churyumov-Gerasimenko on 25 February 2007. In this paper we describe the measurements obtained by the M channel of the Visual and Infrared Thermal Imaging Spectrometer (VIRTIS-M) and the first scientific results derived from their analysis. The broad spectral coverage of the VIRTIS-M in the IR permitted the study of various phenomena occurring in the Martian atmosphere; observations were further exploited to achieve accurate absolute radiometric calibration. Nighttime data from the VIRTIS-M constrain the air temperature profile in the lower atmosphere (5-30 km), using variations in CO2 opacity at 4.3 mm. A comparison of this data with the global circulation model (GCM) by Forget et al. (1999) shows a trend of slightly higher air temperature in the VIRTIS-M retrievals; this is accompanied by the presence of moderate decreases (∼5 K) in large sections of the equatorial region. This is potentially related to the occurrence of water ice cl uds. Daytime data from the VIRTIS-M reveal CO 2 non-local thermodynamic equilibrium emission in the high atmosphere. A mapping of emission intensity confirms its strict dependence on solar zenith angle. Additionally, devoted limb observations allowed the retrieval of vertical emission intensity profiles, indicating a peak around 105 km in southern tropical regions. Ozone content can be effectively monitored by the emission of O2 (a¹Δg) at 1.27 μm. Retrieved emission intensity shows that polar regions are particularly rich in ozone. Aerosol scattering was observed in the 1-2.5 μm region above the night region above the night disk, suggesting the occurrence of very high noctilucent clouds. Copyright 2010 by the American Geophysical Union.

Abstract:

Coupled climate models are multiphysics models comprising multi-ple separately developed codes that are combined into a single physical system. This composition of codes is amenable to a scripting solution, and Python is a language that offers many desirable properties for this task. We have prototyped a Python coupling and control infrastruc-ture for version 3.0 of the Community Climate System Model (ccsm3). Our objective was to improve dramatically ccsm3's already exible coupling facilities to enable research uses of the model not currently supported. We report the progress in the first steps in this effort: the construction of Python bindings for the Model Coupling Toolkit, a key piece of third-party coupling middleware used in ccsm3, and a Python-based ccsm3 coupler (pypcl) application. We report prelim-inary performance results for this new system, which we call pyccsm. We find pyccsm is significantly slower than its Fortran counterpart, and explain how pypcl's performance may be improved to support production runs. We believe our results augur well for the use of Python in the top-level coupling and organisation of large parallel multiphysics and multiscale applications.