Pressure effects on martian crustal magnetization near large impact basins

Abstract— Martian crust endured several large meteoroid impacts subsequent to the demise of an early global magnetic field. Shock pressures associated with these impacts demagnetized parts of the crust, to an extent determined by shock resistance of magnetic materials in the crust. Impacts that form large basins generate pressures in excess of 1 GPa within a few crater radii of their impact sites. Crustal materials near the surface experience significantly reduced impact pressure, which varies with depth and distance from the impact point. We present new demagnetization experiments on magnetite (Fe₃O₄), hematite (α‐Fe₂O₃), and titanohematite (Fe_2‐xTi_xO₃ where x <0.2). Our measurements show that pressures of ?1 GPa are sufficient to partially demagnetize all of these minerals. The efficiency of demagnetization by impact pressure is proportional to the logarithm of the minerals' magnetic coercivity. The impact pressure magnetic response from exsolved titanohematite samples is consistent with the magnetization decay near Prometheus impact basin and may point to an oxidized igneous rock in Terra Sirenum region at the time of acquisition of magnetic remanence. The remaining magnetic anomalies near large impact basins suggest moderate crustal coercivity. These anomalies point to titanomagnetite as a magnetic carrier and more reduced condition during crustal formation.     

An example of attenuation by wet snow on a radar dome

Abstract

A case study of the degradation of weather radar data by the accretion of wet snow on a radar dome is presented as a precautionary example to radar users. During the ERICA field program in 1989, accumulated precipitation on the radome at Halifax, Nova Scotia, attenuated signal in a distinctive, pie‐shaped sector on the upwind side of the radar.     

Recent progress in the operational forecasting of summer severe weather

Abstract

Summer severe weather (SSW) can strike suddenly and unexpectedly with disastrous consequences for human activity. Considerable progress has been made in the past ten years in the operational forecasting of SSW. Traditionally, SSW was defined to consist of tornadoes, strong winds, hail, lightning and heavy rain. Hazardous types of strong winds have recently been expanded to include microbursts, macrobursts and surfacing rear inflow jet damage behind mesoscale convective systems. Doppler radar was used to relate surface damage to the appropriate atmospheric phenomena, first diagnostically and then prognostically. This improvement in classification has fedback to and improved the forecast process. Concurrent progress has been made in the use of synoptic observations. The concept of helical wind profiles and improved knowledge of the role of dry mid‐level air has improved the forecasting of tornadoes and strong gusty winds. Moisture flux convergence, derived from surface measurements, shows great promise in identifying areas of storm initiation. Satellite imagery has been used to identify dynamical atmospheric boundaries. Numerical modelling of the interaction of environmental wind profiles and individual thunderstorms has greatly contributed to the understanding of SSW. Studies of spatial and temporal patterns of lightning, both specific cases and climatology, contribute to the forecasting of severe storms. Polarization radar results have shown progress in separating the signals of hail from those of rain and in the improved measurement of heavy rainfalls. Radar observation of clear air boundaries and their interactions show potential for the forecasting of thunderstorm initiation. Though not traditionally considered part of SSW, hurricanes that evolve into extra‐tropical storms share many of the same hazardous features. The progress in computing, communications and display technologies has also made substantial contributions to operational forecasting and to the dissemination of weather warnings.     

Probabilistic estimates of future changes in California temperature and precipitation using statistical and dynamical downscaling

Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly of similar magnitude to the projected T changes. In the monthly average, July temperatures shift enough that that the hottest July found in any simulation over the historical period becomes a modestly cool July in the future period. Januarys as cold as any found in the historical period are still found in the 2060s, but the median and maximum monthly average temperatures increase notably. Annual and seasonal P changes are small compared to interannual or intermodel variability. However, the annual change is composed of seasonally varying changes that are themselves much larger, but tend to cancel in the annual mean. Winters show modestly wetter conditions in the North of the state, while spring and autumn show less precipitation. The dynamical downscaling techniques project increasing precipitation in the Southeastern part of the state, which is influenced by the North American monsoon, a feature that is not captured by the statistical downscaling.     

Evaluating a modified point-based method to downscale cell-based climate variable data to high-resolution grids

To address the demand for high spatial resolution gridded climate data, we have advanced the Daymet point-based interpolation algorithm for downscaling global, coarsely gridded data with additional output variables. The updated algorithm, High-Resolution Climate Downscaler (HRCD), performs very good downscaling of daily, global, historical reanalysis data from 1° input resolution to 2.5 arcmin output resolution for day length, downward longwave radiation, pressure, maximum and minimum temperature, and vapor pressure deficit. It gives good results for monthly and yearly cumulative precipitation and fair results for wind speed distributions and modeled downward shortwave radiation. Over complex terrain, 2.5 arcmin resolution is likely too low and aggregating it up to 15 arcmin preserves accuracy. HRCD performs comparably to existing daily and monthly US datasets but with a global extent for nine daily climate variables spanning 1948–2006. Furthermore, HRCD can readily be applied to other gridded climate datasets.     

Cosmic microwave background polarization due to scattering in clusters

Scattering of the cosmic microwave background (CMB) in clusters of galaxies polarizes the radiation. We explore several polarization components which have their origin in the kinematic quadrupole moments induced by the motion of the scattering electrons, either directed or random. Polarization levels and patterns are determined in a cluster simulated by the hydrodynamical enzo code. We find that polarization signals can be as high as  ∼1 μK  , a level that may be detectable by upcoming CMB experiments.     

APEX-SZ a Sunyaev–Zel’dovich galaxy cluster survey

The APEX-SZ experiment is a sky survey designed to discover galaxy clusters via the Sunyaev–Zel’dovich effect at millimeter wavelengths. We describe the components of the instrument, including the 12 m Atacama Pathfinder Experiment telescope, optics, Transition-edge sensor bolometer array and SQUID readout. APEX-SZ will begin observations in 2004.