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Kalb, V. L.

Publications and source records attributed to Kalb, V. L..

Comparison Between Vortices Created and Evolving During Fixed and Dynamic Solar Wind Conditions

We employ Magnetohydrodynamic (MHD) simulations to examine the creation and evolution of plasma vortices within the Earth's magnetosphere for steady solar wind plasma conditions. Very few vortices form during intervals of such solar wind conditions. Those that do remain in fixed positions for long periods (often hours) and exhibit rotation axes that point primarily in the x or y direction, parallel (or antiparallel) to the local magnetospheric magnetic field direction. Occasionally, the orientation of the axes rotates from the x direction to another direction. We compare our results with simulations previously done for unsteady solar wind conditions. By contrast, these vortices that form during intervals of varying solar wind conditions exhibit durations ranging from seconds (in the case of those with axes in the x or y direction) to minutes (in the case of those with axes in the z direction) and convect antisunward. The local-time dependent sense of rotation seen in these previously reported vortices suggests an interpretation in terms of the Kelvin-Helmholtz instability. For steady conditions, the biggest vortices developed on the dayside (about 6R(E) in diameter), had their rotation axes aligned with the y direction and had the longest periods of duration. We attribute these vortices to the flows set up by reconnection on the high latitude magnetopause during intervals of northward Interplanetary Magnetic Field (IMF) orientation. This is the first time that vortices due to high-latitude reconnection have been visualized. The model also successfully predicts the principal characteristics of previously reported plasma vortices within the magnetosphere, namely their dimension, flow velocities, and durations.

solar wind↗

Cloud-screening for Africa using a geographically and seasonally variable infrared threshold

A spatially variable monthly, infrared cloud-threshold data base has been used to screen cloud-contaminated observations from radiances measured by the NOAA-9 AVHRR over Africa. Cloud-screening through a monthly average infrared threshold based on measured surface air temperature, which is geographically dependent, shows an improvement over using a seasonally and geographically independent thermal cloud threshold of 287 K. It is found that differences in cloud-screening for these two thresholds occur for cases of lower altitude clouds or subpixel clouds where the radiative temperature is higher than the 287 K infrared threshold, yet colder than the variable threshold developed by Stowe et al. (1988) for the Nimbus-7 global cloud climatology. The variable IR threshold is shown to be effective over persistently cloud-covered regions, such as the coastal region of the Gulf of Guinea, but may introduce some erroneous cloud identifications over mountains.

Eck, T. F.↗

Representation of vegetation by continental data sets derived from NOAA-AVHRR data

Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.

Justice, C. O.↗