It is believed that the continuing change in the Earth's climate will affect the viral activity and transmission of influenza over the coming decades. However, a consensus of the severity of the risk of an influenza epidemic in a warming climate has not been reached. It was previously reported that the warmer winter can reduce influenza epidemic caused mortality, but this relation cannot explain the deadly influenza epidemic in many countries over northern mid-latitudes in the winter of 2017-2018, one of the warmest winters in recent decades. Here, we reveal that the widely spread 2017-2018 influenza epidemic can be attributed to the abnormally strong rapid weather variability. We demonstrate, from historical data, that the large rapid weather variability in autumn can precondition the deadly influenza epidemic in the subsequent months in highly populated northern mid-latitudes; and the influenza epidemic season of 2017-2018 was a typical case. We further show that climate model projections reach a consensus that the rapid weather variability in autumn will continue to strengthen in some regions of northern mid-latitudes in a warming climate, implying that the risk of an influenza epidemic may increase 20% to 50% in some highly populated regions in the later 21st century.

Abstract. Galileo images have shown that grooved terrain on Ganymede consists of pervasive ridges and grooves at a variety of spatial scales, which complicates visual interpretation. We use Fourier analysis to separate complex surface deformation into its component dominant wavelengths (closely correlated to topographic wavelengths) to determine spatial relationships within and among grooved terrain units. We analyze groove lanes in four Galileo target sites (Uruk Sulcus, Byblus Sulcus, Tiamat Sulcus, and Nicholson Regio), spanning a range of resolutions and lighting geometries, and we find multiple dominant wavelengths in each. Fourier analysis of the complexly deformed Uruk Sulcus shows both similarities and differences in wavelength distribution among its tectono-stratigraphic subunits (a range of 0.5 to 6 km, with a concentration at 1.2 km); favorable comparison is made to a stereo-derived topographic model. Of the dominant wavelengths displayed by Byblus Sulcus (-• 1, 3.3, and 10 km), the longest wavelength is revealed by profiles across both high-and low-resolution images with very different lighting geometries. Tiamat Sulcus displays different dominant wavelengths north (5 to 10 km) and south (3 to 5 km) of the orthogonally trending Kishar Sulcus. Groove lanes in Nicholson Regio are significantly different from the other sites because they are isolated within dark terrain. Fourier analysis of these dark terrain groove lanes shows dominant wavelengths (•-2.1, 3.2, and 8.0 km) that are similar to those in lanes of more typical grooved terrain. This suggests that the tectonic style and lithospheric characteristics in this portion of Ganymede's dark terrain were similar to those in bright grooved terrain at the time of deformation. Our results support the hypothesis that longer topographic wavelengths in Ganymede's groove lanes formed by means of extensional necking of the lithosphere, while multiple shorter wavelengths formed by normal faulting of the brittle lithosphere, in both bright and dark terrains. The similar wavelengths of deformation seen in several groove lanes in both bright and dark terrain suggest similarity in lithospheric thickness, composition, and mechanical structure at these disparate sites. A global process (such as differentiation) could be responsible for creating a similar planet-wide strain and thermal regime during the time of grooved terrain formation. •Now at Siemens Medical Systems, Ultrasound Group, Issaquah, They found no apparent correlation with longitude and latitude. Galileo images allow grooved terrain units to be studied at a much finer scale than was possible with Voyager images, al- padding has also been applied, providing the number of data points necessary for the FFT algorithm. Each resulting spectrum was manually searched for significant peaks (defined as peaks above half of the maximum value in the spectrum), as these are representative of the dominant wavelength(s) for that particular profile. (For example, the power spectrum of Figure 2a (bottom) shows just on...

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