The short-term prediction of universal time and length of day using atmospheric angular momentum

Details The short-term prediction of universal time and length of day using atmospheric angular momentum The short-term prediction of universal time and length of day using atmospheric angular momentum

Apr 1994

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994jgr....99.6981f&link_type=abstract

Journal of Geophysical Research (ISSN 0148-0227), vol. 99, no. B4, p. 6981-6996

Mathematics

Logic

13

Angular Momentum, Atmospheric Effects, Earth Rotation, Numerical Weather Forecasting, Spacecraft Tracking, Universal Time, Geodesy, Geodetic Accuracy, Kalman Filters, Real Time Operation, Stochastic Processes, Time Series Analysis

Scientific paper

The ability to predict short-term variations in the Earth's rotation has gained importance in recent years owing to more precise spacecraft tracking requirements. Universal time (UT1), that component of the Earth's orientation corresponding to the rotation angle, can be measured by number of high-precision space geodetic techniques. A Kalman filter developed at the Jet Propulsion Laboratory (JPL) optimally combines these different data sets and generates a smoothed times series and a set of predictions for UT1, as well as for additional Earth orientation components. These UT1 predictions utilize an empirically derived random walk stochastic model for the length of the day (LOD) and require frequent and up-to-date measurements of either UT1 or LOD to keep errors from quickly accumulating. Recent studies have shown that LOD variations are correlated with changes in the Earth's axial atmospheric angular momentum (AAM) over timescales of several years down to as little as 8 days. AAM estimates and forecasts out to 10 days are routinely available from meteorological analysis centers; these data can supplement geodetic measurements to improve the short-term prediction of LOD and have therefore been incorporated as independent data types in the JPL Kalman filter. We find that AAM and, to a lesser extent, AAM forecast data are extremely helpful in generating accurate near-real-time estimates of UT1 and LOD and in improving short-term predictions of these quantities out to about 10 days.

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