Abstract
A Geostationary Microwave Sounder: Design, Implementation and Performance
Highlights
During the latter half of 2020 a detailed study of a geostationary microwave sounder concept and its projected performance was undertaken at the Jet Propulsion Laboratory (JPL) as one of several such studies commissioned by the National Oceanic and Atmospheric Administration (NOAA) to assist in configuring NOAA’s generation of earth environmental and weather satellite systems
geostationary earth orbit (GEO) orbits are almost 50 times higher than the low earth orbit (LEO) orbits that Advanced Microwave Sounding Unit (AMSU) and Advanced Technology Microwave Sounder (ATMS) operate from, and the corresponding scaling of aperture size required to maintain spatial resolution had stymied the development of such a sensor for many decades in spite of an expectation in the atmospheric science community that a geostationary microwave sounder would revolutionize the field
The simulation studies discussed here present strong evidence that a geostationary microwave sounder can provide a number of important measurements of atmospheric parameters, ranging from temperature and water vapor to vertical profiles
Summary
GeoSTAR can be thought of as “AMSU in GEO”, i.e. it has capabilities in geostationary earth orbit (GEO) similar to those of microwave sounders currently operating in low earth orbit (LEO). Having such a capability in GEO will add tremendously to our ability to observe dynamic atmospheric phenomena, such as hurricanes and severe storms, monsoonal moisture flow, atmospheric rivers, etc. By tracking water vapor patterns it is possible to derive atmospheric wind speed and direction at altitudes from the surface to 10-15 km. All of this can be done regardless of cloud cover and weather conditions. We present a summary of our findings, including instrument characteristics, measurement accuracy and precision, and expected impact on weather prediction and applications
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More From: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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