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The spatial and temporal variability of water vapour in the atmosphere influences the earth weather, climate system, quality of spatial positioning and radio waves propagation of communications signals amongst others. It is therefore imperative to periodically monitor and map the water vapour phenomenon over specific areas of interest across the globe. This study therefore investigates the time-series variability of the atmospheric water vapour contents (AWVC) over Nigeria from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim (ERA-I) and National Centre for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data. The 2007-2017 daily/monthly mean data sets of ERA-I and NCEP/NCAR were visualised and extracted with Panoply version 4.8.6 and MATLAB 2018b for the 37 states capital in Nigeria. The months of minimum and maximum AWVC for all sampled locations were determined and compared, and the best fit trend equations for six cities (one city from each of the six geopolitical zones) were developed. The monthly means of AWVC over the study area showed spatial heterogeneity trend. The latitudinal variations in both ERA-I and NCEP/NCAR data sets showed that AWVC over Nigeria increases as latitude decreases towards the equator, and vice versa, irrespective of the month or time of the year. The study showed that May-September and November-February of 2007-2017 represent the periods with highest and lowest values of AWVC over Nigeria, respectively, which are the expected wet and dry seasons in the study area, and with peak months of August and January, respectively. The linear regression of the ERA-I and NCEP/NCAR data sets gave a coefficient of correlation of about 96.37%, coefficient of determination (R 2) of about 92.9% and a coefficient of efficiency of 87.83%, which indicate that ERA-I and NCEP/NCAR data sets have close values and the relationship between them in estimating AWVC over any selected location is statistically significant and valid. The coefficient of efficiency (E) of about 87.8% shows high level of internal efficiency of the ERA-I and NCEP/NCAR data sets used in this study. The best line of fit from polynomial models showed a range of the R 2 results for the best line-of-fit determination ranging between 78.36% and 95.75% for ERA-I, and 81.24% and 94.13% for NCEP/NCAR. The models and time-series spatial maps of AWVC produced in the study are recommended for use in the empirical estimation of AWVC and validations of other independent water vapour retrieval solutions such as GNSS and aerospace radiometry over the study area.

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Atmospheric water vapour is the most variable component of the atmosphere. It plays a crucial role in Earth‘s energy balance and hydrological cycles. Because of its temporal and spatial variability, accurate measurement of atmospheric water vapour has been very challenging in meteorology. However, the Global Positioning System (GPS) offers detailed coverage, all weather and continuous observations. Therefore, exploring this potential to deliver atmospheric information is now termed ‗GPS meteorology‘. This paper presents a brief overview of global trend in GPS meteorology while discussing GPS meteorology research efforts in Malaysia. A summary of the current research activity towards realisation of operational use of GPS meteorology in Malaysia is also highlighted.

Dense 3D point clouds provided by terrestrial laser scanner (TLS) has demonstrated significant reliability of TLS in landslide monitoring. However, existence of errors in measurement is inevitable which eventually has decreased the quality of TLS data. To concretely measure the capability of TLS in landslide monitoring, this study has performed two epoch measurements using tacheometry (for benchmarking) and TLS (Topcon GLS-2000) at Kulim Techno City, Kedah, Malaysia. Sixteen (16) artificial targets were well-distributed on the slope to determine the accuracy of the employed TLS. Results obtained revealed that Topcon GLS-2000 provides 0.006m of accuracy. However, the presence of high incidence angles in TLS measurement has limited the capability to identify the significant displacement of the targets.