Michael Kendra

The thermospheric semiannual density response to solar EUV heating

The goal of this study was to characterize the thermospheric semiannual density response to solar heating during the last 35 years. Historical radar observational data have been processed with special orbit perturbations on 28 satellites with perigee heights ranging from 200 to 1100 km. Approximately 225,000 very accurate average daily density values at perigee have been obtained for all satellites using orbit energy dissipation rates. The semiannual variation has been found to be extremely variable from year to year. The magnitude of the maximum yearly difference, from the July minimum to the October maximum, is used to characterize the yearly semiannual variability. It has been found that this maximum difference can vary by as much as 100% from one year to the next. A high correlation has been found between this maximum difference and solar EUV data. The semiannual variation for each year has been characterized based on analyses of annual and semiannual cycles, using Fourier analysis, and equations have been developed to characterize this yearly variability. The use of new solar indices in the EUV and FUV wavelengths is shown to very accurately describe the semiannual July minimum phase shifting and the variations in the observed yearly semiannual amplitude.

Midcourse Space Experiment (MSX): plans and capability for the measurement of infrared earthlimb and terrestrial backgrounds

A major objective of the MSX program is to obtain global data of atmospheric and terrestrial backgrounds simultaneously in the infrared (2.6 to 28 micrometers ) and short wave (0.11 to 0.9 micrometers ) spectral regions. This paper presents an overview of the plans and capabilities to measure infrared earthlimb and terrestrial backgrounds with the cryogenic infrared MSX sensor, the spatial Infrared Imaging Telescope (SPIRIT) III sensor. Of particular importance is the characterization of the spatial-temporal structure and the global distribution of mean radiometric levels and spectral content of both quiescent atmospheric and terrestrial backgrounds as well as the backgrounds associated with aurora, mesospheric and noctilucent clouds, stratospheric warmings, wave phenomena, scatter and thermal emissions from clouds, terrain, and other sources. Experiments are planned to collect data as a function of latitude, season, diurnal conditions, magnetic activity and altitude, up to tangent heights of 300 km over a period of 18 months for the infrared (cryogen lifetime) and 5 years for the visible and ultraviolet sensors. Coordinated experiments are planned with ground sites and in conjunction with other satellites. Automated processing will provide rapid data reduction and the generation of data products.

Earth limb infrared clutter model from measurements

Mid-Course Space Experiment (MSX) infrared (IR) observations in the earth limb were used to obtain spatial power spectral densities (PSDs) for five sensor bands over a wide range of earth limb background clutter conditions. These backgrounds include daytime, nighttime, terminator, aurora, polar mesospheric cloud, atmospheric gravity wave, stratospheric warming, airglow, and other observations collected over approximately 100 episodic data collection events. Using a subset of detectors and restricting detector tangent altitude variations, a total of more than 33,000 high-quality PSDs were generated. For infrared detection of unresolved objects where the solid angle of the object is much smaller than the instantaneous field-of-view of a sensor element, the spectral component at high spatial frequencies is a critical metric. PSDs were therefore constructed in the spatial domain using one minute data segments, which allowed spatial scale assessment from 0.01-10 cycles/km. PSDs that met the clutter model selection criteria were identified, accumulated, and processed to obtain a small set of empirical, altitude-based model parameters. We describe the MSX sensor bands, data and data processing employed for PSD generation and final reduction to obtain model parameters. Key model features are discussed with emphasis on object detection against stressing limb backgrounds. The model was constructed in a way that facilitates optical design and system engineering application. In particular, it may be used to address Space Situational Awareness (SSA) questions.