Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

An overview of the current status of CMB observations

In this paper we briefly review the current status of the Cosmic Microwave Background (CMB) observations, summarising the latest results obtained from CMB experiments, both in intensity and polarization, and the constraints imposed on the cosmological parameters. We also present a summary of current and future CMB experiments, with a special focus on the quest for the CMB B-mode polarization.Comment: Latest CMB results have been included. References added. To appear in "Highlights of Spanish Astrophysics V", Proceedings of the VIII Scientific Meeting of the Spanish Astronomical Society (SEA) held in Santander, 7-11 July, 200

OPTICAL REDSHIFT AND RICHNESS ESTIMATES FOR GALAXY CLUSTERS SELECTED WITH THE SUNYAEV-ZEL'DOVICH EFFECT FROM 2008 SOUTH POLE TELESCOPE OBSERVATIONS

We present redshifts and optical richness properties of 21 galaxy clusters uniformly selected by their Sunyaev-Zel'dovich signature. These clusters, plus an additional, unconfirmed candidate, were detected in a 178 square-degree area surveyed by the South Pole Telescope in 2008. Using griz imaging from the Blanco Cosmology Survey and from pointed Magellan telescope observations, as well as spectroscopy using Magellan facilities, we confirm the existence of clustered red-sequence galaxies, report red-sequence photometric redshifts, present spectroscopic redshifts for a subsample, and derive R_200 radii and M_200 masses from optical richness. The clusters span redshifts from 0.15 to greater than 1, with a median redshift of 0.74; three clusters are estimated to be at z > 1. Redshifts inferred from mean red-sequence colors exhibit 2% RMS scatter in sigma_z/(1+z) with respect to the spectroscopic subsample for z < 1. We show that M_200 cluster masses derived from optical richness correlate with masses derived from South Pole Telescope data and agree with previously derived scaling relations to within the uncertainties. Optical and infrared imaging is an efficient means of cluster identification and redshift estimation in large Sunyaev-Zel'dovich surveys, and exploiting the same data for richness measurements, as we have done, will be useful for constraining cluster masses and radii for large samples in cosmological analysis