By the end of 2018, 42 years after the landing of the two Viking seismometers on Mars, InSight will deploy onto Mars’ surface the SEIS ( S eismic E xperiment for I nternal S tructure) instrument; a six-axes seismometer equipped with both a long-period three-axes Very Broad Band (VBB) instrument and a three-axes short-period (SP) instrument. These six sensors will cover a broad range of the seismic bandwidth, from 0.01 Hz to 50 Hz, with possible extension to longer periods. Data will be transmitted in the form of three continuous VBB components at 2 sample per second (sps), an estimation of the short period energy content from the SP at 1 sps and a continuous compound VBB/SP vertical axis at 10 sps. The continuous streams will be augmented by requested event data with sample rates from 20 to 100 sps. SEIS will improve upon the existing resolution of Viking’s Mars seismic monitoring by a factor of at 1 Hz and at 0.1 Hz. An additional major improvement is that, contrary to Viking, the seismometers will be deployed via a robotic arm directly onto Mars’ surface and will be protected against temperature and wind by highly efficient thermal and wind shielding. Based on existing knowledge of Mars, it is reasonable to infer a moment magnitude detection threshold of at epicentral distance and a potential to detect several tens of quakes and about five impacts per year. In this paper, we first describe the science goals of the experiment and the rationale used to define its requirements. We then provide a detailed description of the hardware, from the sensors to the deployment system and associated performance, including transfer functions of the seismic sensors and temperature sensors. We conclude by describing the experiment ground segment, including data processing services, outreach and education networks and provide a description of the format to be used for future data distribution. Electronic Supplementary Material The online version of this article (10.1007/s11214-018-0574-6) contains supplementary material, which is available to authorized users.

The Gemini Multi-conjugate adaptive optics System (GeMS) at the Gemini South telescope in Cerro Pachón is the first sodium-based multi-Laser Guide Star (LGS) adaptive optics system. It uses five LGSs and two deformable mirrors to measure and compensate for atmospheric distortions. The GeMS project started in 1999, and saw first light in 2011. It is now in regular operation, producing images close to the diffraction limit in the near infrared, with uniform quality over a field of view of two square arcminutes. The present paper (I) is the first one in a two-paper review of GeMS. It describes the system, explains why and how it was built, discusses the design choices and trade-offs, and presents the main issues encountered during the course of the project. Finally, we briefly present the results of the system first light.

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The authors investigated the relation between the width function and the regional variability of peak flows. The authors explored 34 width function descriptors (WFDs), in addition to drainage area, as potential candidates for explaining the regional peak flow variability. First, using hydrologic simulations of uniform rainfall events with variable rainfall duration and constant rainfall intensity for 147 watersheds across the state of Iowa, they demonstrated that WFDs are capable of explaining spatial variability of peak flows for individual rainfall‐runoff events under idealized physical conditions. This theoretical exercise indicates that the inclusion of WFDs should drastically improve regional peak flow estimates with a reduction of the root mean square error by more than half in comparison with a regression model based on drainage area only. The authors followed the simulation with an analysis of estimated peak flow quantiles from 94 stream gauges in Iowa to determine if the WFDs have a similar explanatory power. The correlations between WFDs and peak flow quantiles are not as high as those found for simulated events, which indicates that results from event scale simulations do not translate directly to peak flow quantiles. The spatial variability of peak flow quantiles is influenced by other physical and statistical processes that are also variable in space. These results are consistent with recent work on event‐based scaling of peak flows that shows that the spatiotemporal variability of flood mechanisms is larger than the one expected from geomorphology alone.

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