On 19 March 2017, destructive tsunami-like waves impacted the northeast shore of the Persian Gulf (PG). The maximum surveyed runup of about 3 m was observed at Dayyer in southern Iran, where damaging waves inundated the land for a distance of * 1 km and resulted in the deaths of five people. Because the PG has always been considered safe from extreme oceanic waves, the event was totally unexpected. In this study, we examined sea level data from 12 stations across the PG and a variety of meteorological information, including satellite imagery, high-altitude isohypse maps and high-resolution air pressure records from 47 instruments along the PG. Our results show that the event was very local, with recorded maximum trough-to-crest wave heights of 197 cm at Dayyer and 234 cm at Asaluyeh, nearfield cities in Iran located * 80 km apart. The dominant wave periods were in the range of 15-20 min. At all distant tide gauges, the observed wave heights were \ 35 cm. No earthquakes or landslides were evident at the time of the event. On the other hand, atmospheric processes during 18-22 March were very active and 10 distinctive tsunamigenic air pressure disturbances were observed propagating over the PG, suggesting that the event of 19 March 2017 was a ''meteorological tsunami''. Atmospheric conditions over the PG were highly favourable for the generation of meteotsunamis and very similar to those that caused a chain of strong meteotsunamis in the Mediterranean and Black Sea regions during 23-27 June 2014. Based on the 500 hPa wind, we evaluated that the disturbances had propagation speeds of 21-38 m/s, with the disturbance at Dayyer having a speed of * 26 m/s toward 77°T rue. The Froude number, Fr (estimated as the ratio of the air disturbance speed to the long wave speed), on 19 March 2017 in the Dayyer/Asaluyeh region was close to resonance, Fr * 0.9 to 1.1, which is highly favourable for meteotsunami generation. Our findings indicate that the Dayyer/Asaluyeh area is a ''hot spot'' that is highly vulnerable to extreme, weather-induced tsunami-like waves.

The merging of a gravimetric quasigeoid model with GPS-levelling data using second-generation wavelets is considered so as to provide better transformation of GPS ellipsoidal heights to normal heights.Since GPS-levelling data are irregular in the space domain and the classical wavelet transform relies on Fourier theory, which is unable to deal with irregular data sets without prior gridding, the classical wavelet transform is not directly applicable to this problem. Instead, second-generation wavelets and their associated lifting scheme, which do not require regularly spaced data, are used to combine gravimetric quasigeoid models and GPS-levelling data over Norway and Australia, and the results are cross validated.Cross validation means that GPS-levelling points not used in the merging are used to assess the results, where one point is omitted from the merging and used to test the merged surface, which is repeated for all points in the dataset. The wavelet-based results are also compared to those from least squares collocation (LSC) merging. This comparison shows that the second-generation wavelet method can be used instead of LSC with similar results, but the assumption of stationarity for LSC is not required in the wavelet method.Specifically, it is not necessary to [somewhat arbitrarily] remove trends from the data before applying the wavelet method, as is the case for LSC. It is also shown that the wavelet method is better at decreasing the maximum and minimum differences between the merged geoid and the cross-validating GPS-levelling data.

The quasi-geoid/geoid can be determined from the Global Positioning System (GPS) ellipsoidal height and the normal/orthometric heights derived from levelling (GPS-levelling). In this study a gravimetric quasigeoid and GPS-levelling height differences are combined to develop a new surface, suitable for "levelling" by GPS. This new surface provides better conversion of GPS ellipsoidal heights to the national normal heights. Different combining procedures, a four-parameter solution, linear and cubic splines interpolations, as well as the least-squares collocation method were investigated and compared over entire Norway. More than 1700 GPS-levelling stations were used in this study. The combined surface provides significant accuracy improvement for the normal height transformation of GPS height data, as demonstrated by the post-fitting residuals. The best solution, based on the least-squares collocation, provided a conversion surface for the transformation of GPS heights into normal height in Norway with an accuracy of about 5 cm.