A 10-year record of Arctic summer sea ice freeboard from CryoSat-2

Satellite observations of pan-Arctic sea ice thickness have so far been constrained to winter months. For radar altimeters, conventional methods cannot differentiate leads from meltwater ponds that accumulate at the ice surface in summer months, which is a critical step in the ice thickness calculation. Here, we use over 350 optical and synthetic aperture radar (SAR) images from the summer months to train a 1D convolution neural network for separating CryoSat-2 radar altimeter returns from sea ice floes and leads with an accuracy >80%. This enables us to generate the first pan-Arctic measurements of sea ice radar freeboard for May–September between 2011 and 2020. Results indicate that the freeboard distributions in May and September compare closely to those from a conventional ‘winter’ processor in April and October, respectively. The freeboards capture expected patterns of sea ice melt over the Arctic summer, matching well to ice draft observations from the Beaufort Gyre Exploration Program (BGEP) moorings. However, compared to airborne laser scanner freeboards from Operation IceBridge and airborne EM ice thickness surveys from the Alfred Wegener Institute (AWI) IceBird program, CryoSat-2 freeboards are underestimated by 0.02–0.2 m, and ice thickness is underestimated by 0.28–1.0 m, with the largest differences being over thicker multi-year sea ice. To create the first pan-Arctic summer sea ice thickness dataset we must address primary sources of uncertainty in the conversion from radar freeboard to ice thickness

An Inversion Method for Measuring Beta in Large Redshift Surveys

A precision method for determining the value of Beta= Omega_m^{0.6}/b, where b is the galaxy bias parameter, is presented. In contrast to other existing techniques that focus on estimating this quantity by measuring distortions in the redshift space galaxy-galaxy correlation function or power spectrum, this method removes the distortions by reconstructing the real space density field and determining the value of Beta that results in a symmetric signal. To remove the distortions, the method modifies the amplitudes of a Fourier plane-wave expansion of the survey data parameterized by Beta. This technique is not dependent on the small-angle/plane-parallel approximation and can make full use of large redshift survey data. It has been tested using simulations with four different cosmologies and returns the value of Beta to +/- 0.031, over a factor of two improvement over existing techniques.Comment: 16 pages including 6 figures Submitted to The Astrophysical Journa

Redshift-Space Enhancement of Line-of-Sight Baryon Acoustic Oscillations in the SDSS Main-Galaxy Sample

We show that redshift-space distortions of galaxy correlations have a strong effect on correlation functions with distinct, localized features, like the signature of the baryon acoustic oscillations (BAO). Near the line of sight, the features become sharper as a result of redshift-space distortions. We demonstrate this effect by measuring the correlation function in Gaussian simulations and the Millennium Simulation. We also analyze the SDSS DR7 main-galaxy sample (MGS), splitting the sample into slices 2.5 degrees on the sky in various rotations. Measuring 2D correlation functions in each slice, we do see a sharp bump along the line of sight. Using Mexican-hat wavelets, we localize it to (110 +/- 10) Mpc/h. Averaging only along the line of sight, we estimate its significance at a particular wavelet scale and location at 2.2 sigma. In a flat angular weighting in the (pi,r_p) coordinate system, the noise level is suppressed, pushing the bump's significance to 4 sigma. We estimate that there is about a 0.2% chance of getting such a signal anywhere in the vicinity of the BAO scale from a power spectrum lacking a BAO feature. However, these estimates of the significances make some use of idealized Gaussian simulations, and thus are likely a bit optimistic.Comment: 17 pages, 27 figures. Minor changes to match final version accepted to Ap

A 120-Mpc Periodicity in the Three-Dimensional Distribution of Galaxy Superclusters

Using a new compilation of available data on galaxy clusters and superclusters we present evidence for a quasiregular three-dimensional network of rich superclusters and voids, with the regions of high density separated by about 120 Mpc. We calculate the power spectrum for clusters of galaxies; it has a peak on the wavelength equal to the step of the network; the excess in the amplitude of the spectrum over that of the cold dark matter model is by a factor of 1.4. The probability that the spectrum can be formed within the framework of the standard cosmogony is very small. If the cluster distribution reflects the distribution of all matter (luminous and dark), then there must exists some hithero unknown process that produces regular structure on large scales.Comment: Tex, 6 pages, 2 PostScript figures embedded, accepted by Nature on November 19, 199