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The relationship between the length of day (LOD) and El-Niño Southern Oscillation (ENSO) has been well studied since the 1980s. LOD is the negative time-derivative of UT1-UTC, which is directly proportional to Earth Rotation Angle (ERA), one of the Earth Orientation Parameters (EOP). The EOP can be determined using Very Long Baseline Interferometry (VLBI), which is a space geodetic technique. In addition, satellite techniques such as the Global Navigation Satellite System (GNSS), Satellite Laser Ranging (SLR), Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) can provide Earth Rotation Parameters, i.e., polar motion and LOD. ENSO is a climate phenomenon occurring over the tropical eastern Pacific Ocean that mainly affects the tropics and the subtropics. Extreme ENSO events can cause extreme weather like flooding and droughts in many parts of the world. In this work, we investigated the effect of ENSO on the LOD from January 1979 to April 2022 using the wavelet coherence method. This method computes the coherence between the two non-stationary time-series in the time-frequency domain using the real-valued Morlet wavelet. We used the Multivariate ENSO index version 2 (MEI v.2) which is the most robust series as the climate index for the ENSO, and LOD time-series from IERS (EOP 14 C04 (IAU2000A)). We also used Oceanic Niño and Southern Oscillation index in this study for comparison. The results show strong coherence of 0.7 to 0.9 at major ENSO events for the periods 2–4 years between LOD and MEI.v2.

We introduce a static a priori gradient model (APG) based on a spherical harmonic expansion up to degree and order nine to describe the azimuthal asymmetry of tropospheric delays. APG is determined from climatology data of the European Centre for Medium-Range Weather Forecasts (ECMWF), and the refined model can be used in the analysis of observations from Global Navigation Satellite Systems (GNSS) and Very Long Baseline Interferometry (VLBI). Comparisons reveal that gradients estimated in GNSS analysis are mostly smaller than those provided by APG. This difference is also confirmed by station and source coordinate changes if APG is used in GNSS and VLBI analysis.

State-of-the-art modelling of the neutral atmosphere delays in GNSS (Global Navigation Satellite Systems), VLBI (Very Long Baseline Interferometry), and DORIS (Doppler Orbitography by Radiopositioning Integrated on Satellite) analyses requires information about the a priori hydrostatic zenith delays (or the pressure values, respectively) and the hydrostatic and wet mapping functions at the sites. We compare empirical models for the pressure (Global Pressure and Temperature, GPT) and for troposphere mapping functions (Global Mapping Functions, GMF) with discrete time series derived from numerical weather models for the hydrostatic zenith delays and mapping functions (Vienna Mapping Functions 1, VMF1) in terms of accuracy, precision and availability for the radio space geodetic techniques. Unlike prior models which have large deficiencies at around Antarctica, the empirical GPT does not cause significant station height biases, but the degradation of station height standard deviations when using the empirical models GPT and GMF instead of the discrete time series from the numerical weather models is by about 3 mm at the equator and 6 mm at ± 60° latitude.