Recently, ring laser technology has provided the first consistent observations of rotational ground motions around a vertical axis induced by earthquakes. "Consistent," in this context, implies that the observed waveforms and amplitudes are compatible with collocated recordings of translational ground motions. In particular, transverse accelerations should be in phase with rotation rate and their ratio proportional to local horizontal phase velocity assuming plane-wave propagation. The ring laser installed at the Fundamentalstation Wettzell in the Bavarian Forest, Southeast Germany, is recording the rotation rate around a vertical axis, theoretically a linear combination of the space derivatives of the horizontal components of motion. This suggests that, in principle, rotation can be derived from seismic-array experiments by "finite differencing." This has been attempted previously in several studies; however, the accuracy of these observations could never be tested in the absence of direct measurements. We installed a double cross-shaped array of nine stations from December 2003 to March 2004 around the ring laser instrument and observed several large earthquakes on both the ring laser and the seismic array. Here we present for the first time a comparison of array-derived rotations with direct measurements of rotations for ground motions induced by the M 6.3 Al Hoceima, Morocco, earthquake of 24 February 2004. With complete 3D synthetic seismograms calculated for this event we show that even low levels of noise may considerably influence the accuracy of the array-derived rotations when the minimum number of required stations (three) is used. Nevertheless, when using all nine stations, the overall fit between direct and array-derived measurements is surprisingly good (maximum correlation coefficient of 0.94).

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Accurate precipitation observations are crucial for water resources management and as inputs for a gamut of hydrometeorological applications. Precipitation data from Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) have recently been widely used to complement traditional rain gauge systems. However, the satellite precipitation data needs to be validated before being widely used in the applications and this is still missing over the Indonesian maritime continent (IMC). We conducted a validation of the IMERG product version 6 for this region. The evaluation was carried out using gauge data in the period from 2016 to 2020 for three types of IMERG: Early (E), Late (L), and Final (F) from annual, monthly, daily and hourly data. In general, the annual and monthly data from IMERG showed a good correlation with the rain gauge, with the mean correlation coefficient (CC) approximately 0.54–0.78 and 0.62–0.79, respectively. About 80% of stations in the IMC area showed a very good correlation between gauge data and IMERG-F estimates (CC = 0.7–0.9). For the daily assessment, the CC value was in the range of 0.39 to 0.44 and about 40% of stations had a correlation of 0.5–0.7. IMERG had a fairly good ability to detect daily rain in which the average probability of detection (POD) for all stations was above 0.8. However, the false alarm ratio (FAR) value is quite high (<0.5). For hourly data, IMERG’s performance was still poor with CC around 0.03–0.28. For all assessments, IMERG generally overestimated rainfall in comparison with rain gauge. The accuracy of the three types of IMERG in IMC was also influenced by season and topography. The highest and lowest CC values were observed for June–July–August and December–January–February, respectively. However, categorical statistics (POD, FAR and critical success index) did not show any clear seasonal variation. The CC value decreased with higher altitude, but with slight difference for each IMERG type. For all assessments conducted, IMERG-F generally showed the best rainfall observations in IMC, but with slightly difference from IMERG-E and IMERG-L. Thus, IMERG-E and IMERG-L data that had a faster latency than IMERG-F show potential to be used in rainfall observations in IMC.

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