Length of day

HOW DAYS SHORTEN AND LENGTHEN IN CLUJ-NAPOCA. AN ANALYSIS OF THE LIGHT PHENOMENON. The article analises how daylight changes during the cold season in Cluj-Napoca, Romania. Average noon occurs here at 12:25 EET while the dotted curve is a graphical representation of the equation of time. Because of it, true solar noon can happen in Cluj-Napoca between 12:09-12:39 EET, meaning it gets pushed back to the morning hours up to 16 minutes in October – November and forward to the evening hours up to 14 minutes in February. Combined with the change in solar declination, autumn daylight decreases more abruptly towards the evening, but recovers sharply in the early weeks of New Year. Between November 27 and December 24 the Sun sets at about the same time (16:43 +/- 2 minutes) which means that afternoons preserve their duration for almost a month. Similarly, between December 19 and January 15, the Sun rises at about the same time (8:03 +/- 2 minutes) which means that in this period mornings remain almost unchanged. Another consequence of the equation of time is the fact that earliest sunsets occur before the solstice (10/11 December) and latest sunrises take place only after the solstice (January 1).

Tides have been a source of inquiry since the dawn of human civilization. It has been known for millennia that the Moon is a causative agent in the formation of tides, with the observation that lunar phases often correlated to changing tidal amplitudes. The precise mechanisms underlying the formation of tides and local tidal dynamics, however, have proven difficult to elucidate. Only with Newton's theory of gravitation in the 17th century was the correlation between lunar cycles and tides partially explained. Further work by Laplace and others resulted in a more dynamic theory that more closely matched observations and allowed for better prediction of local tidal behavior. Quantitative models derived from these methods have increased in precision and complexity (particularly with the advent of the electronic computer), and have allowed new insights into the nature of tidal dynamics and tidal dissipation.In more recent years scientists have analyzed deposits known as tidal bundles and tidal rhythmites in an attempt to extrapolate the history of tides from the geologic record. Tidal bundles are laterally accreted cyclic foreset beds separated by mud laminae. Tidal rhythmites are vertically accreted planar laminae that alternate between coarse and fine sediments forming couplets often composed of sands and muds. These deposits are characterized by bed/laminae thicknesses that vary rhythmically and preserve tidal periodicities, and are generally found in intertidal or subtidal depositional environments. The mode of deposition (e.g. sand or mud) is primarily determined by current velocity and tidal range, factors largely controlled by the tides in marginal marine settings.Quantitative analyses of tidal rhythmites may facilitate more precise elucidation of tidal periodicities encoded in the rock record. The partial reconstruction of the history of lunar recession from existing data and analyses indicates that the Earth is presently experiencing a high rate of tidal dissipation. Further data obtained from ancient tidal proxies may prove essential in constraining models of tidal dissipation, thereby revealing the mechanisms and dynamics present in the dissipation process controlling secular changes in the length of day and lunar orbit.

By subtracting computed atmospheric angular momentum from a time-series for length-of-day variations, we obtain a high-resolution time-series that is useful for studying the effects of the core on length-of-day variations. Features in this time-series are closely correlated with the time at which geomagnetic jerks have been observed, suggesting a role for the core in angular momentum exchange within the Earth system on timescales as short as one year, and that jerks are directly related to the processes responsible for changes in core angular momentum.

Stochastic prediction techniques including autocovariance, autoregressive, autoregressive moving average, and neural networks were applied to the UT1-UTC and Length of Day (LOD) International Earth Rotation and Reference Systems Servive (IERS) EOPC04 time series to evaluate the capabilities of each method. All known effects such as leap seconds and solid Earth zonal tides were first removed from the observed values of UT1-UTC and LOD. Two combination procedures were applied to predict the resulting LODR time series: 1) the combination of the least-squares (LS) extrapolation with a stochastic predition method, and 2) the combination of the discrete wavelet transform (DWT) filtering and a stochastic prediction method. The results of the combination of the LS extrapolation with different stochastic prediction techniques were compared with the results of the UT1-UTC prediction method currently used by the IERS Rapid Service/Prediction Centre (RS/PC). It was found that the prediction accuracy depends on the starting prediction epochs, and for the combined forecast methods, the mean prediction errors for 1 to about 70 days in the future are of the same order as those of the method used by the IERS RS/PC.

The Earth orientation parameters (EOP) are determined by space geodetic techniques with very high accuracy. However, the accuracy of their prediction, even for a few days in the future, is several times lower and still unsatisfactory for practical use. The main problem of each prediction technique is to predict simultaneously long and short period oscillations of the EOP. It has been shown that the combination of the prediction methods which are different for deterministic and stochastic components of the EOP can provide the best accuracy of prediction. Several prediction techniques, e.g. combination of the least-squares with autoregressive and autocovariance methods as well as combination of wavelet transform decomposition and autocovariance prediction, were used to predict x, y pole coordinates in polar coordinate system and UT 1− UTC or length of day (∆) data. Different prediction algorithms were compared considering the difference between the EOP data and their predictions at di...

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ 3). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ 3 time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ 3 data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ 3 predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ 3 time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ 3 reveal the best accuracy for LS + AR.

This study presents subdaily resolved chemical records through fossil mollusk shell calcite. Trace element profiles resolve periodic variability across~40-μm-thin daily growth laminae in a Campanian Torreites sanchezi rudist bivalve. These high-resolution records are combined with seasonally resolved stable isotope and trace element records that allow shell-chemical variability to be discussed on both seasonal and daily scale. A combination of layer counting, spectral analysis of chemical cyclicity and chemical layer counting shows that the rudist precipitated 372 daily laminae per year, demonstrating that length of day has increased since the Late Cretaceous, as predicted by astronomical models. This new approach to determine the length of a solar day in geologic history through multiproxy chemical records at subdaily resolution yields considerably more control on the uncertainty of this estimate. Daily chemical variability exceeds seasonal variability in our records, and cannot be explained by diurnal temperature changes. Instead, we postulate that rudist shell chemistry is driven on a daily scale by changes in light intensity. These results together with those of stable isotope analyses provide strong evidence that Torreites rudists had photosymbionts. Bivalve shell calcite generally preserves well. Therefore, this study paves the way for daily-scale reconstructions of paleoenvironment and sunlight intensity on geologic time scales from bivalve shells, potentially allowing researchers to bridge the gap between climate and weather reconstructions. Such reconstructions improve shell chronologies, document environmental change in warm ecosystems, and widen our understanding of the magnitude of short-term changes during greenhouse climates.

We investigate the possibility of detecting non-linear low-dimensional deterministic processes in the time-series of the length of day (LOD) and polar motion components (PMX, PMY), filtered to keep the period range [ ~ 1 day-100 days]. After each time-series has been embedded in a pseudo-phase space with dimension D_E*=5 or 6 (see Frede & Mazzega 1999, hereafter referred to as Paper I) we extract the geometric and dynamical characteristics of the reconstructed orbit. Using a local false neighbours algorithm and an analysis of the data local covariance matrix eigenspectrum, we find a local dimension D_L=5 for the three EOP series. The principal Lyapunov exponents averaged over the ~ 27 years of observation (1970-1997) are positive. This result unambiguously indicates the chaotic nature of the Earth's rotational dynamical regime in this period range of fluctuations. As a consequence, some theoretical prediction horizons cannot be exceeded by any tentative forecast of the EOP evolution. Horizons of 11.3 days for LOD, 8.7 days for PMX and 8.1 days for PMY are found, beyond which prediction errors will be of the order of the s of the filtered EOP series, say 0.12 ms, 2.30 mas (milliarcsecond) and 1.57 mas respectively. From the Lyapunov spectra we estimate the Lyapunov dimension D_Lyap, which is an upper bound for the corresponding attractor dimension D_A. We find D_Lyap(LOD)=4.48, D_Lyap(PMX)=4.90 and D_Lyap(PMY)=4.97. These determinations are in broad agreement with those of the attractor dimensions obtained from correlation integrals, i.e. D_A(LOD)=4.5-5.5, D_A(PMX)=3.5-4.5, D_A(PMY)=4-5. We finally show that the Earth's rotational state experiences large changes in stability. Indeed, the local prediction horizons, as deduced from the local Lyapunov exponents, occasionally drop to about 3.3 days for LOD in the years 1982-1984, 2.6 days for PMX in 1972-1973 and 2.6 days for PMY in 1996-1997. Some of these momentary stability perturbations of the Earth's rotation are clearly related to El Niño events, although others lack an obvious source mechanism.

Very Long Baseline Interferometry (VLBI) is exclusively sensitive to the complete rotation matrix from the terrestrial to the quasi-inertial frame, while ring lasers being sensitive to the instantaneous Earth rotation vector in an Earth- fixed frame, i.e., to polar motion and length of day variations. Additionally, assuming a perfect knowledge of mass attraction variations, superconducting gravimeters (SG) permit to detect Earth rotation variations from the magnitude of the local gravity. The formula of the Sagnac frequency and gravity variation caused by the motion of the Earth's body w.r.t. the instantaneous Earth rotation vector will be presented and compared to VLBI parameterization. The potential of a combination of the three independent types of observables will be examined for sub-diurnal polar motion and universal time variations.

In this study, we develop a time--dependent description of the fluid flow at the core--mantle boundary over the last seven thousands years. Magnetic diffusion should be an essential ingredient of the observed secular variation and therefore has to be considered in the inversion of the induction equation for core--surface flows. First results suggest that the core-surface flow undergoes different regimes of zonal flow direction. Epochs of a mainly westward flow alternate with epochs of a eastward flow.Also,the mean velocity of the flow seems to fluctuate. These changes in the flow direction seem to recurring periodically, with a period of about 1000 years. While the mechanism causing this variation is unassigned, it should also reflect in the length of day variation, where due to core--mantle coupling angular momentum is transfered from the core to the mantle. A comparison between the deduced length of day variation from historical eclipses and the prediction of our model is given.