Optimal interpolation of satellite and ground data for irradiance nowcasting at city scales

We use a Bayesian method, optimal interpolation, to improve satellite derived irradiance estimates at city-scales using ground sensor data. Optimal interpolation requires error covariances in the satellite estimates and ground data, which define how information from the sensor locations is distributed across a large area. We describe three methods to choose such covariances, including a covariance parameterization that depends on the relative cloudiness between locations. Results are computed with ground data from 22 sensors over a 75×80 km area centered on Tucson, AZ, using two satellite derived irradiance models. The improvements in standard error metrics for both satellite models indicate that our approach is applicable to additional satellite derived irradiance models. We also show that optimal interpolation can nearly eliminate mean bias error and improve the root mean squared error by 50%

Changes in tropical Atlantic interannual variability from a substantial weakening of the meridional overturning circulation

In response to a substantial weakening of the Atlantic Meridional Overturning Circulation (AMOC)— from a coupled ocean–atmosphere general circulation model experiment—significant changes in the interannual variability are found over the tropical Atlantic, characterized by an increase of variance (by ~150 %) in boreal late spring-early summer and a decrease of variance (by ~60 %) in boreal autumn. This study focuses on understanding physical mechanisms responsible for these changes in interannual variability in the tropical Atlantic. It demonstrates that the increase of variability in spring is a consequence of an increase in the variance of the El Niño-Southern Oscillation, which has a large impact on the tropical Atlantic via anomalous surface heat fluxes. Winter El Niño (La Niña) affects the eastern equatorial Atlantic by decreasing (increasing) cloud cover and surface wind speed which is associated with anomalous downward (upward) short wave radiation and reduced (enhanced) upward latent heat fluxes, creating anomalous positive (negative) sea surface temperature (SST) anomalies over the region from winter to spring. On the other hand, the decrease of SST variance in autumn is due to a deeper mean thermocline which weakens the impact of the thermocline movement on SST variation. The comparison between the model results and observations is not straightforward owing to the influence of model biases and the lack of a major MOC weakening event in the instrumental record. However, it is argued that the basic physical mechanisms found in the model simulations are likely to be robust and therefore have relevance to understanding tropical Atlantic variability in the real world, perhaps with modified seasonality

Dynamics for a 2-vertex Quantum Gravity Model

We use the recently introduced U(N) framework for loop quantum gravity to study the dynamics of spin network states on the simplest class of graphs: two vertices linked with an arbitrary number N of edges. Such graphs represent two regions, in and out, separated by a boundary surface. We study the algebraic structure of the Hilbert space of spin networks from the U(N) perspective. In particular, we describe the algebra of operators acting on that space and discuss their relation to the standard holonomy operator of loop quantum gravity. Furthermore, we show that it is possible to make the restriction to the isotropic/homogeneous sector of the model by imposing the invariance under a global U(N) symmetry. We then propose a U(N) invariant Hamiltonian operator and study the induced dynamics. Finally, we explore the analogies between this model and loop quantum cosmology and sketch some possible generalizations of it.Comment: 28 pages, v2: typos correcte

A large sample analysis of European rivers on seasonal river flow correlation and its physical drivers

The geophysical and hydrological processes governing river flow formation exhibit persistence at several timescales, which may manifest itself with the presence of positive seasonal correlation of streamflow at several different time lags. We investigate here how persistence propagates along subsequent seasons and affects low and high flows. We define the high-flow season (HFS) and the low-flow season (LFS) as the 3-month and the 1-month periods which usually exhibit the higher and lower river flows, respectively. A dataset of 224 rivers from six European countries spanning more than 50 years of daily flow data is exploited. We compute the lagged seasonal correlation between selected river flow signatures, in HFS and LFS, and the average river flow in the antecedent months. Signatures are peak and average river flow for HFS and LFS, respectively. We investigate the links between seasonal streamflow correlation and various physiographic catchment characteristics and hydro-climatic properties. We find persistence to be more intense for LFS signatures than HFS. To exploit the seasonal correlation in the frequency estimation of high and low flows, we fit a bi-variate meta-Gaussian probability distribution to the selected flow signatures and average flow in the antecedent months in order to condition the distribution of high and low flows in the HFS and LFS, respectively, upon river flow observations in the previous months. The benefit of the suggested methodology is demonstrated by updating the frequency distribution of high and low flows one season in advance in a real-world case. Our findings suggest that there is a traceable physical basis for river memory which, in turn, can be statistically assimilated into high- and low-flow frequency estimation to reduce uncertainty and improve predictions for technical purposes

An extension of SPARQL for expressing qualitative preferences

In this paper we present SPREFQL, an extension of the SPARQL language that allows appending a PREFER clause that expresses "soft" preferences over the query results obtained by the main body of the query. The extension does not add expressivity and any SPREFQL query can be transformed to an equivalent standard SPARQL query. However, clearly separating preferences from the "hard" patterns and filters in the WHERE clause gives queries where the intention of the client is more cleanly expressed, an advantage for both human readability and machine optimization. In the paper we formally define the syntax and the semantics of the extension and we also provide empirical evidence that optimizations specific to SPREFQL improve run-time efficiency by comparison to the usually applied optimizations on the equivalent standard SPARQL query.Comment: Accepted to the 2017 International Semantic Web Conference, Vienna, October 201

NCAM 180 Acting via a Conserved C-Terminal Domain and MLCK Is Essential for Effective Transmission with Repetitive Stimulation

SummaryNCAM 180 isoform null neuromuscular junctions are unable to effectively mobilize and exocytose synaptic vesicles and thus exhibit periods of total transmission failure during high-frequency repetitive stimulation. We have identified a highly conserved C-terminal (KENESKA) domain on NCAM that is required to maintain effective transmission and demonstrate that it acts via a pathway involving MLCK and probably myosin light chain (MLC) and myosin II. By perfecting a method of introducing peptides into adult NMJs, we tested the hypothesized role of proteins in this pathway by competitive disruption of protein-protein interactions. The effects of KENESKA and other peptides on MLCK and MLC activation and on failures in both wild-type and NCAM 180 null junctions supported this pathway, and serine phosphorylation of KENESKA was critical. We propose that this pathway is required to replenish synaptic vesicles utilized during high levels of exocytosis by facilitating myosin-driven delivery of synaptic vesicles to active zones or their subsequent exocytosis

TFAP2C regulates transcription in human naive pluripotency by opening enhancers.

Naive and primed pluripotent human embryonic stem cells bear transcriptional similarity to pre- and post-implantation epiblast and thus constitute a developmental model for understanding the pluripotent stages in human embryo development. To identify new transcription factors that differentially regulate the unique pluripotent stages, we mapped open chromatin using ATAC-seq and found enrichment of the activator protein-2 (AP2) transcription factor binding motif at naive-specific open chromatin. We determined that the AP2 family member TFAP2C is upregulated during primed to naive reversion and becomes widespread at naive-specific enhancers. TFAP2C functions to maintain pluripotency and repress neuroectodermal differentiation during the transition from primed to naive by facilitating the opening of enhancers proximal to pluripotency factors. Additionally, we identify a previously undiscovered naive-specific POU5F1 (OCT4) enhancer enriched for TFAP2C binding. Taken together, TFAP2C establishes and maintains naive human pluripotency and regulates OCT4 expression by mechanisms that are distinct from mouse

Computing Black Hole entropy in Loop Quantum Gravity from a Conformal Field Theory perspective

Motivated by the analogy proposed by Witten between Chern-Simons and Conformal Field Theories, we explore an alternative way of computing the entropy of a black hole starting from the isolated horizon framework in Loop Quantum Gravity. The consistency of the result opens a window for the interplay between Conformal Field Theory and the description of black holes in Loop Quantum Gravity.Comment: 9 page