A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons

In this paper, we present a comprehensive review of the data sources and estimation methods of 30 currently available global precipitation data sets, including gauge-based, satellite-related, and reanalysis data sets. We analyzed the discrepancies between the data sets from daily to annual timescales and found large differences in both the magnitude and the variability of precipitation estimates. The magnitude of annual precipitation estimates over global land deviated by as much as 300 mm/yr among the products. Reanalysis data sets had a larger degree of variability than the other types of data sets. The degree of variability in precipitation estimates also varied by region. Large differences in annual and seasonal estimates were found in tropical oceans, complex mountain areas, northern Africa, and some high-latitude regions. Overall, the variability associated with extreme precipitation estimates was slightly greater at lower latitudes than at higher latitudes. The reliability of precipitation data sets is mainly limited by the number and spatial coverage of surface stations, the satellite algorithms, and the data assimilation models. The inconsistencies described limit the capability of the products for climate monitoring, attribution, and model validation

Quantisation of 2D-gravity with Weyl and area-preserving diffeomorphism invariances

The constraint structure of 2D-gravity with the Weyl and area-preserving diffeomorphism invariances is analysed in the ADM formulation. It is found that when the area-preserving diffeomorphism constraints are kept, the usual conformal gauge does not exist, whereas there is the possibility to choose the so-called ``quasi-light-cone'' gauge, in which besides the area-preserving diffeomorphism invariance, the reduced Lagrangian also possesses the SL(2,R) residual symmetry. The string-like approach is applied to quantise this model, but a fictitious non-zero central charge in the Virasoro algebra appears. When a set of gauge-independent SL(2,R) current-like fields is introduced instead of the string-like variables, a consistent quantum theory is obtained.Comment: 14 pages, Latex fil

Insight on Shallow Trap States-Introduced Photocathodic Performance in n-Type Polymer Photocatalysts

Graphitic carbon nitride (g-C3N4) is a robust organic semiconductor photocatalyst with proven H2 evolution ability. However, its application in a photoelectrochemical system as a photocathode for H2 production is extremely challenging with the majority of reports representing it as a photoanode. Despite research into constructing g-C3N4 photocathodes in recent years, factors affecting an n-type semiconductor’s properties as a photocathode are still not well-understood. The current work demonstrates an effective strategy to transform an n-type g-C3N4 photoanode material into an efficient photocathode through introducing electron trap states associated with both N-defects and C–OH terminal groups. As compared to the g-C3N4 photoelectrode, this strategy develops 2 orders of magnitude higher conductivity and 3 orders of magnitude longer-lived shallow-trapped charges. Furthermore, the average OCVD lifetime observed for def-g-C3N4 is 5 times longer than that observed for g-C3N4. Thus, clear photocathode behavior has been observed with negative photocurrent densities of around −10 μA/cm2 at 0 V vs RHE. Open circuit photovoltage decay (OCVD), Mott–Schottky (MS) plot, and transient absorption spectroscopy (TAS) provide consistent evidence that long-lived shallow-trapped electrons that exist at about the microsecond time scale after photoexcitation are key to the photocathode behavior observed for defect-rich g-C3N4, thus further demonstrating g-C3N4 can be both a photoanode and a photocathode candidate

Application of riblets on turbine blade endwall secondary flow control

© 2015 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. Within the past 10 years, significant improvements have been achieved in the laser manufacturing process. It is feasible now to design various small-scale surface features (such as dimples, riblets, grooves, etc.) in gas turbine applications with the current manufacturing readiness level of laser surface texturing techniques. In this paper, the potential of adding riblets on a turbine endwall has been investigated through combined computational fluid dynamics and experimental studies in a low-speed linear cascade environment. Detailed comparisons of the flow structures have been made for cases with and without riblets on the endwall. The numerical results show that endwall riblets can effectively reduce the strength of the pressure side leg of the horseshoe vortex, lower the cross-passage pressure gradient, and alleviate the lift up of the passage vortex. Oil filmflowvisualization and exit aerodynamic loss survey in experiments support the computational fluid dynamics observations: The passage vortex loss core moves closer to the endwall with the addition of riblets. The present study consistently demonstrates that the addition of riblets can be an effective approach to reduce the endwall secondary flow. Further research questions are raised for the applicability of the riblets concept in actual engine conditions and options for design optimization

The cumulative effects of known susceptibility variants to predict primary biliary cirrhosis risk.

Multiple genetic variants influence the risk for development of primary biliary cirrhosis (PBC). To explore the cumulative effects of known susceptibility loci on risk, we utilized a weighted genetic risk score (wGRS) to evaluate whether genetic information can predict susceptibility. The wGRS was created using 26 known susceptibility loci and investigated in 1840 UK PBC and 5164 controls. Our data indicate that the wGRS was significantly different between PBC and controls (P=1.61E-142). Moreover, we assessed predictive performance of wGRS on disease status by calculating the area under the receiver operator characteristic curve. The area under curve for the purely genetic model was 0.72 and for gender plus genetic model was 0.82, with confidence limits substantially above random predictions. The risk of PBC using logistic regression was estimated after dividing individuals into quartiles. Individuals in the highest disclosed risk group demonstrated a substantially increased risk for PBC compared with the lowest risk group (odds ratio: 9.3, P=1.91E-084). Finally, we validated our findings in an analysis of an Italian PBC cohort. Our data suggested that the wGRS, utilizing genetic variants, was significantly associated with increased risk for PBC with consistent discriminant ability. Our study is a first step toward risk prediction for PBC