Evaluating Optical Clock Performance for GNSS Positioning.

Atomic clocks are highly precise timing devices used in numerous Positioning, Navigation, and Timing (PNT) applications on the ground and in outer space. In recent years, however, more precise timing solutions based on optical technology have been introduced as current technology capabilities advance. State-of-the-art optical clocks-predicted to be the next level of their predecessor atomic clocks-have achieved ultimate uncertainty of 1 × 10-18 and beyond, which exceeds the best atomic clock's performance by two orders of magnitude. Hence, the successful development of optical clocks has drawn significant attention in academia and industry to exploit many more opportunities. This paper first provides an overview of the emerging optical clock technology, its current development, and characteristics, followed by a clock stability analysis of some of the successfully developed optical clocks against current Global Navigation Satellite System (GNSS) satellite clocks to discuss the optical clock potentiality in GNSS positioning. The overlapping Allan Deviation (ADEV) method is applied to estimate the satellite clock stability from International GNSS Service (IGS) clock products, whereas the optical clock details are sourced from the existing literature. The findings are (a) the optical clocks are more stable than that of atomic clocks onboard GNSS satellites, though they may require further technological maturity to meet spacecraft payload requirements, and (b) in GNSS positioning, optical clocks could potentially offer less than a 1 mm range error (clock-related) in 30 s and at least 10 times better timing performance after 900 s in contrast to the Galileo satellite atomic clocks-which is determined in this study as the most stable GNSS atomic clock type used in satellite positioning.

Enhancing the Australian Gridded Climate Dataset rainfall analysis using satellite data.

Rainfall estimation over large areas is important for a thorough understanding of water availability, influencing societal decision-making, as well as being an input for scientific models. Traditionally, Australia utilizes a gauge-based analysis for rainfall estimation, but its performance can be severely limited over regions with low gauge density such as central parts of the continent. At the Australian Bureau of Meteorology, the current operational monthly rainfall component of the Australian Gridded Climate Dataset (AGCD) makes use of statistical interpolation (SI), also known as optimal interpolation (OI) to form an analysis from a background field of station climatology. In this study, satellite observations of rainfall were used as the background field instead of station climatology to produce improved monthly rainfall analyses. The performance of these monthly datasets was evaluated over the Australian domain from 2001 to 2020. Evaluated over the entire national domain, the satellite-based SI datasets had similar to slightly better performance than the station climatology-based SI datasets with some individual months being more realistically represented by the satellite-SI datasets. However, over gauge-sparse regions, there was a clear increase in performance. For a representative sub-domain, the Kling-Gupta Efficiency (KGE) value increased by + 8% (+ 12%) during the dry (wet) season. This study is an important step in enhancing operational rainfall analysis over Australia.