THE SHORT-TERM PREDICTION OF UNIVERSAL TIME AND LENGTH OF DAY USING ATMOSPHERIC ANGULAR-MOMENTUM

The ability to predict short-term variations in the Earth's rotation h as gained importance in recent years owing to more precise spacecraft tracking requirements. Universal time (UT1), that component of the Ear th's orientation corresponding to the rotation angle, can be measured by a number of high-precision space geodetic techniques. A Kalman filt er developed at the Jet Propulsion Laboratory (JPL) optimally combines these different data sets and generates a smoothed time series and a set of predictions for UT1, as well as for additional Earth orientatio n components. These UT1 predictions utilize an empirically derived ran dom 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 erro rs from quickly accumulating. Recent studies have shown that LOD varia tions are correlated with changes in the Earth's axial atmospheric ang ular momentum (AAM) over timescales of several years down to as little as 8 days. AAM estimates and forecasts out to 10 days are routinely a vailable from meteorological analysis centers; these data can suppleme nt geodetic measurements to improve the short-term prediction of LOD a nd have therefore been incorporated as independent data types in the J PL Kalman filter. We find that AAM and, to a lesser extent, AAM foreca st data are extremely helpful in generating accurate near-real-time es timates of UT1 and LOD and in improving short-term predictions of thes e quantities out to about 10 days.