Precipitation and latent heating distributions from satellite passive microwave radiometry. Part I: improved method and uncertainties

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h−1 to 20% at 14 mm h−1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%–80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day−1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%–35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%–15% at 5 mm day−1, with proportionate reductions in latent heating sampling errors

New directions in island biogeography

Aim: Much of our current understanding of ecological and evolutionary processes comes from island research. With the increasing availability of data on distributions and phylogenetic relationships and new analytical approaches to understanding the processes that shape species distributions and interactions, a re-evaluation of this ever-interesting topic is timely. Location: Islands globally. Methods: We start by arguing that the reasons why island research has achieved so much in the past also apply to the future. We then critically assess the current state of island biogeography, focusing on recent changes in emphasis, including research featured in this special issue of Global Ecology and Biogeography. Finally, we suggest promising themes for the future. We cover both ecological and evolutionary topics, although the greater emphasis on island ecology reflects our own backgrounds and interests. Results: Much ecological theory has been directly or indirectly influenced by research on island biotas. Currently, island biogeography is renascent, with research focusing on, among other things, patterns and processes underlying species interaction networks, species coexistence and the assembly of island communities through ecological and evolutionary time. Continuing island research should provide additional insight into biological invasions and other impacts of human activities, functional diversity and ecosystem functioning, extinction and diversification, species pools and more. Deeper understanding of the similarities and differences between island and mainland systems will aid transferability of island theory to continental regions. Main conclusions: As research in biogeography and related fields expands in new directions, islands continue to provide opportunities for developing insights, both as natural laboratories for ecology and evolution and because of the exceptions islands often present to the usual ‘rules’ of ecology. New data collection initiatives are needed on islands world-wide and should be directed towards filling gaps in our knowledge of within-island distributions of species, as well as the functional traits and phylogenetic relationships of island species

Modeling DNA Structure, Elasticity and Deformations at the Base-pair Level

We present a generic model for DNA at the base-pair level. We use a variant of the Gay-Berne potential to represent the stacking energy between neighboring base-pairs. The sugar-phosphate backbones are taken into account by semi-rigid harmonic springs with a non-zero spring length. The competition of these two interactions and the introduction of a simple geometrical constraint leads to a stacked right-handed B-DNA-like conformation. The mapping of the presented model to the Marko-Siggia and the Stack-of-Plates model enables us to optimize the free model parameters so as to reproduce the experimentally known observables such as persistence lengths, mean and mean squared base-pair step parameters. For the optimized model parameters we measured the critical force where the transition from B- to S-DNA occurs to be approximately $140{pN}$. We observe an overstretched S-DNA conformation with highly inclined bases that partially preserves the stacking of successive base-pairs.Comment: 15 pages, 25 figures. submitted to PR

Molecular and Historical Aspects of Corn Belt Dent Diversity

Tens-of-thousands of open-pollinated cultivars of corn (Zea mays L.) are being maintained in germplasm banks. Knowledge of the amount and distribution of genetic variation within and among accessions can aid end users in choosing among them. We estimated molecular genetic variation and looked for influences of pedigree, adaptation, and migration in the genetic makeup of conserved Corn-Belt Dent-related germplasm. Plants sampled from 57 accessions representing Corn-Belt Dents, Northern Flints, Southern Dents, plus 12 public inbreds, were genotyped at 20 simple sequence repeat (SSR) loci. For 47 of the accessions, between 5 and 23 plants per accession were genotyped (mean = 9.3). Mean number of alleles per locus was 6.5 overall, 3.17 within accessions, and 3.20 within pooled inbreds. Mean gene diversity was 0.53 within accessions and 0.61 within pooled inbreds. Open-pollinated accessions showed a tendency toward inbreeding (FIS = 0.09), and 85% of genetic variation was shared among them. A Fitch-Margoliash tree strongly supported the distinctiveness of flint from dent germplasm but did not otherwise reveal evidence of genetic structure. Mantel tests revealed significant correlations between genetic distance and geographical (r = 0.54, P= 0.04) or maturity zone (r = 0.33, P = 0.03) distance only if flint germplasm was included in the analyses. A significant correlation (r = 0.76, P \u3c 0.01) was found between days to pollen shed and maturity zone of accession origin. Pedigree, rather than migration or selection, has most influenced the genetic structure of the extant representatives of the open-pollinated cultivars at these SSR loci

Alignment of the CMS silicon tracker during commissioning with cosmic rays

This is the Pre-print version of the Article. The official published version of the Paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS silicon tracker, consisting of 1440 silicon pixel and 15 148 silicon strip detector modules, has been aligned using more than three million cosmic ray charged particles, with additional information from optical surveys. The positions of the modules were determined with respect to cosmic ray trajectories to an average precision of 3–4 microns RMS in the barrel and 3–14 microns RMS in the endcap in the most sensitive coordinate. The results have been validated by several studies, including laser beam cross-checks, track fit self-consistency, track residuals in overlapping module regions, and track parameter resolution, and are compared with predictions obtained from simulation. Correlated systematic effects have been investigated. The track parameter resolutions obtained with this alignment are close to the design performance.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)