Breeding vectors and predictability in the Oxford Mars GCM

A breeding vectors approach is used to study the intrinsic predictability of the Martian atmosphere using the Oxford Mars General Circulation Model (MGCM). The approach, described in detail below, is first tested using a terrestrial general circulation model, the United Kingdom Meteorological Office's Unified Model (UM), and results show growing modes of instability at mid to high latitudes on spatial scales of less than ~1,000km, in qualitative agreement with previous studies performed using terrestrial models. For the Martian atmosphere, and in the absence of radiatively active dust transport (so using a typical background dust distribution for each time of year), the technique reveals model states with approximately zero growth factors, and modes of instability on relatively large (up to ~5,000km) spatial scales. The implications of this for the predictability of the Martian atmosphere and for the usage of ensemble forecasting methods on Mars are also discussed

Results on dust storms and stationary waves in three Mars years of data assimilation

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Southern California fisheries monitoring summary for 1993 and 1994

The southern California Monitoring and Management Units collectively gathered 803 discrete samples of 7,329 marine finfishes and invertebrates from local commercial fish markets or authorized fish transporters in 1993. Nineteen different species were sampled and biological information recorded for future summarization and use in formulating fisheries management strategies and decisions. Increased sampling efforts in 1994 resulted in 801 samples of 14,566 marine finfish and invertebrates representing 44 different species. Fisheries trends and threats to local fishing opportunities were identified. Results of Marine Recreational Fishery Statistics Survey interviews were also incorporated for a more complete overview of species targeted by both the sport and commercial industries. (26pp.

Data assimilation for Mars: an overview of results from the Mars Global Surveyor period, proposals for future plans and requirements for open access to assimilation output

Abstract not available. From the introduction: 'The Thermal Emission Spectrometer (TES) aboard Mars Global Surveyor (MGS) has produced an extensive atmospheric data set, both during the initial aerobraking hiatus and later from the scientific mapping phase of the mission which lasted almost three complete Martian seasonal cycles. Thermal profiles for the atmosphere below about 40 km, and total dust and water ice opacities, have been retrieved from TES spectra (Conrath et al., 2000, Smith et al., 2000)...'

Dust cycles and storms in a Mars GCM

A number of different dust lifting parameterizations have been used to model the injection of dust from the Martian surface into the atmosphere, and the form of the resulting dust cycles and dust storms produced are found to be highly dependent on the precise form of the parameterization used, provided that it includes some threshold dependence, and particularly where radiatively active dust transport is employed. This talk will review the most interesting results from previous work. We have recently altered a key factor which particularly affects the dust lifting due to near-surface wind stress, however, so we will also present results using the new dust lifting formulation, and make some comparisons

GCM simulations of the martian water cycle

Results from the Viking Orbiter Mars Atmospheric Water Detectors (MAWD) have long been the definitive data set for observations of the Martian water cycle (Farmer et al., 1977). The ongoing Mars Global Surveyor Thermal Emission Spectrometer (TES) observations are providing new insights into the current water cycle, with detailed longitude-latitude dependence of water vapour (Figure 1) and water cloud (Figure 2) with time, as well as information on vertical distribution of water vapour and ice cloud (Smith, 2001). The described results are derived from an ongoing project to model the currentwater cycle using the Oxford version of the European Mars General Circulation Model (MGCM) (Forget et al., 1999), which was developed in colaboration with LMD, Paris

Assessing atmospheric predictability on Mars using numerical weather prediction and data assimilation

Introduction: Studies of the time series of surface measurements of wind, pressure and temperature at the two Viking landers by Barnes [1], [2] revealed that baroclinic transient travelling waves on Mars occur mostly during northern hemisphere autumn, winter and early spring, and typically take the form of highly coherent patterns with planetary wavenumbers 1-3 that can persist for intervals of up to 30-60 sols before changing erratically. Such behaviour is almost unknown on Earth, where individual baroclinic weather systems typically persist for no longer than 5-10 days and seldom remain coherent around entire latitude circles. This occurrence of planetary-scale coherent baroclinic wave-like weather systems on Mars led to suggestions [3] that Mars' atmospheric circulation operates in a quite different dynamical regime to that of the Earth, one that tends to favour regular, symmetrical baroclinic wave activity in a manner reminiscent of the regular wave regimes found in laboratory fluid dynamics experiments on sloping convection in a rotating, thermally-driven fluid annulus (e.g. [4], [5]). In its extreme form, this hypothetical comparison would suggest the possibility of a fully non-chaotic atmospheric circulation on Mars, though subsequent modelling work [6] indicated that perturbations due to the thermal tide would lead to chaotic transitions back and forth between different intransitive wave states. This form of (relatively low-dimensional) chaotic modeflipping appeared to be consistent with the Viking observations of Mars, suggesting nevertheless that the intrinsic predictability of Mars' mid-latitude meteorology was qualitatively and quantitatively quite different from that of the Earth

Atmospheric predictability of the martian atmosphere: from low-dimensional dynamics to operational forecasting?

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Climatology on Mars: interannual variability of mean fields

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