Correction of Single Frequency Altimeter Measurements for Ionosphere Delay

This study is a preliminary analysis of the accuracy of various ionosphere models to correct single frequency altimeter height measurements for Ionospheric path delay. In particular, research focused on adjusting empirical and parameterized ionosphere models in the parameterized real-time ionospheric specification model (PRISM) 1.2 using total electron content (TEC) data from the global positioning system (GPS). The types of GPS data used to adjust PRISM included GPS line-of-sight (LOS) TEC data mapped to the vertical, and a grid of GPS derived TEC data in a sun-fixed longitude frame. The adjusted PRISM TEC values, as well as predictions by IRI-90, a climatotogical model, were compared to TOPEX/Poseidon (T/P) TEC measurements from the dual-frequency altimeter for a number of T/P tracks. When adjusted with GPS LOS data, the PRISM empirical model predicted TEC over 24 1 h data sets for a given local time to with in a global error of 8.60 TECU rms during a midnight centered ionosphere and 9.74 TECU rms during a noon centered ionosphere. Using GPS derived sun-fixed TEC data, the PRISM parameterized model predicted TEC within an error of 8.47 TECU rms centered at midnight and 12.83 TECU rms centered at noon. From these best results, it is clear that the proposed requirement of 3-4 TECU global rms for TOPEX/Poseidon Follow-On will be very difficult to meet, even with a substantial increase in the number of GPS ground stations, with any realizable combination of the aforementioned models or data assimilation schemes

Generating water level time series from satellite altimetry measurements for inland applications

Inland surface water bodies, e.g. lakes and rivers, play vital roles in the nature and in the society. To understand the impact of the human activities and climate change on these vulnerable water resources, monitoring the water level variations with a finer spatial and temporal resolutions is a primary issue. On the other hand, the global available and free accessible in-situ gauge databases are unsatisfactory and insufficient. The spatial distribution of gauge stations is severely uneven and the data accuracy is highly dependent on processing method. Therefore, it is an essential requisite to have a constantly and reliable data stream. Over the past two decades, satellite altimetry has shown the capability to provide repeatable monitoring results for hydrologic cycle and inland water bodies. Several researches and studies are carried out with respect to the improvements on multi-mission data fusion, retracking methods, error estimation and outliers rejection. In this thesis, we take advantage of this state-of-art inland surface water level monitoring technique to generate the water level time series over Amazon River, Benue River and Tsimlyansk Reservoir. Initially, we investigate the measurement principle, corrections and retracking algorithms of radar altimeter throughly. Afterwards, the processing scheme for water level time series is divided into three steps: data selection, correction and result generation. In this thesis, we have chosen Jason-2 measurement data and the on-board Ice retracker. A validation has been performed between our results and the time series from other databases, e.g. DAHITI and Hydroweb. The comparisons showed a feasible and acceptable outcomes regarding to correlation coefficient and root-mean-square error (RMSE). The best result was given by Benue River case with 0:98 and 0:96 of correlation coefficient against DAHITI and Hydroweb, respectively. Also, the minimum RMSE difference, 17.1 cm, was achieved between our time series and the one from DAHITI. We also examined the potential error sources when encountering disagreements with others. Furthermore, possible solutions for error elimination and further improvements were also discussed in experiments and outlook

Sea level rise estimation and interpretation in Malaysian region using multi-sensor techniques

Rise in sea level is one of the disastrous effects of climate change. A relatively small increase in sea level could affect the natural coastal system. This study presents an approach to estimate before interpreting the precise sea level trend based on a combination of multi-sensor techniques in the Malaysian region over a period of 19 years. In the study, six altimeter missions were used to derive the absolute sea levels which were processed in the Radar Altimeter Database System. Next, 21 tide gauge stations along the coastlines of Malaysia were utilised to derive the rate of relative sea levels that took into account sea level changes and vertical land motions. To obtain absolute sea level at tide gauge, vertical land motions at these stations were removed by employing three techniques, namely GPS, Persistent Scatterers Interferometric Synthetic Aperture Radar and altimeter minus tide gauge. Bernese software with double difference strategy was employed to process data from 87 local and 30 international GPS stations. Using Persistent Scatterers Interferometric Synthetic Aperture Radar, the Stanford Method for Persistent Scatterer software processed 111 images. Besides that, the satellite altimeter and tide gauges were used to retrieve the differential rates estimated by altimetry and tidal data to obtain the rate of vertical land motion. Following that, absolute sea level rates from the tide gauge stations and multi-satellite altimeter missions were combined. This combination produced the regional sea level trend of the Malaysian seas. The findings from the multi-sensor techniques showed that the regional sea level trend has been rising at a rate of 2.65 ± 0.86 mm/yr to 6.03 ± 0.79 mm/yr for the chosen sub-areas, with an overall mean of 4.47 ± 0.71 mm/yr. Upon completion of the study, a Sea Level Information System for the Malaysian seas was developed to facilitate users in analysing, manipulating and interpreting sea level and vertical land motion data. This system is expected to be valuable for a wide variety of climatic applications to study environmental issues related to flood and global warming in Malaysia

Mapping of ionospheric total electron content using global navigation satellite systems

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