The Westerly Index as complementary indicator of the North Atlantic oscillation in explaining drought variability across Europe   总被引：1，自引：0，他引：1  

Sergio M. Vicente-Serrano  Ricardo García-Herrera  David Barriopedro  Cesar Azorin-Molina  Juan I. López-Moreno  Natalia Martín-Hernández  Miquel Tomás-Burguera  Luis Gimeno  Raquel Nieto 《Climate Dynamics》2016,47(3-4):845-863

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Changes in surface solar radiation in Northeastern Spain over the past six centuries recorded by tree-ring δ13C     

I. Dorado-Liñán  A. Sanchez-Lorenzo  E. Gutiérrez Merino  O. Planells  I. Heinrich  G. Helle  E. Zorita 《Climate Dynamics》2016,47(3-4):937-950

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Searching for Added Value in Simulating Climate Extremes with a High-Resolution Regional Climate Model over Western Canada     

Charles L. Curry  Bárbara Tencer  Kirien Whan  Andrew J. Weaver  Michel Giguère  Edward Wiebe 《大气与海洋》2016,54(4):364-384

We evaluate the capacity of a regional climate model to represent observed extreme temperature and precipitation events and also examine the impact of increased resolution, in an effort to identify added value in this respect. Two climate simulations of western Canada (WCan) were conducted with the Canadian Regional Climate Model (version 4) at 15 (CRCM15) and 45?km (CRCM45) horizontal resolution driven at the lateral boundaries by data from the European Centre for Medium-range Weather Forecasts (ECMWF) 40-year Reanalysis (ERA-40) for the period 1973–1995. The simulations were evaluated using the spline-interpolated dataset ANUSPLIN, a daily observational gridded surface temperature and precipitation product with a nominal resolution of approximately 10?km. We examine a range of climate extremes, comprising the 10th and 90th percentiles of daily maximum (TX) and minimum (TN) temperatures, the 90th percentile of daily precipitation (PR90), and the 27 core Climate Daily Extremes (CLIMDEX) indices.

Both simulations exhibit cold biases compared with observations over WCan, with the bias exacerbated at higher resolution, suggesting little added value for temperature overall. There are instances, however, of regional improvement in the spatial pattern of temperature extremes at the higher resolution of CRCM15 (e.g., the CLIMDEX index for the annual number of days when TX?>?25°C). The high-resolution simulations also reveal similarly localized features in precipitation (e.g., rain shadows) that are not resolved at the 45?km resolution. With regard to precipitation extremes, although both simulations generally display wet biases, CRCM15 features a reduced bias in PR90 in all seasons except winter. This improvement occurs despite the fact that spatial and interannual variability of PR90 in CRCM15 is significantly overestimated relative to both CRCM45 and ANUSPLIN. We posit that these characteristics are the result of demonstrable differences between corresponding topographical datasets used in the gridded observations and CRCM, the resulting errors propagated to physical variables tied to elevation and the beneficial effect of subsequent spatial averaging. Because topographical input is often discordant between simulations and gridded observations, it is argued that a limited form of spatial averaging may contribute added value beyond that which has already been noted in previous studies with respect to small-scale climate variability.  相似文献   

Using a regional numerical weather prediction model for GNSS positioning over Brazil     

Daniele Barroca Marra Alves  Luiz Fernando Sapucci  Haroldo Antonio Marques  Eniuce Menezes de Souza  Tayná Aparecida Ferreira Gouveia  Jackes Akira Magário 《GPS Solutions》2016,20(4):677-685

The global navigation satellite system (GNSS) can provide centimeter positioning accuracy at low costs. However, in order to obtain the desired high accuracy, it is necessary to use high-quality atmospheric models. We focus on the troposphere, which is an important topic of research in Brazil where the tropospheric characteristics are unique, both spatially and temporally. There are dry regions, which lie mainly in the central part of the country. However, the most interesting area for the investigation of tropospheric models is the wet region which is located in the Amazon forest. This region substantially affects the variability of humidity over other regions of Brazil. It provides a large quantity of water vapor through the humidity convergence zone, especially for the southeast region. The interconnection and large fluxes of water vapor can generate serious deficiencies in tropospheric modeling. The CPTEC/INPE (Center for Weather Forecasting and Climate Studies/Brazilian Institute for Space Research) has been providing since July 2012 a numerical weather prediction (NWP) model for South America, known as Eta. It has yield excellent results in weather prediction but has not been used in GNSS positioning. This NWP model was evaluated in precise point positioning (PPP) and network-based positioning. Concerning PPP, the best positioning results were obtained for the station SAGA, located in Amazon region. Using the NWP model, the 3D RMS are less than 10 cm for all 24 h of data, whereas the values reach approximately 60 cm for the Hopfield model. For network-based positioning, the best results were obtained mainly when the tropospheric characteristics are critical, in which case an improvement of up to 7.2 % was obtained in 3D RMS using NWP models.  相似文献   

User Contribution Patterns and Completeness Evaluation of Mapillary,a Crowdsourced Street Level Photo Service          下载免费PDF全文

Levente Juhász  Hartwig H. Hochmair 《Transactions in GIS》2016,20(6):925-947

Mapillary is a Web 2.0 application which allows users to contribute crowdsourced street level photographs from all over the world. In the first part of the analysis this article reviews Mapillary data growth for continents and countries as well as the contribution behavior of individual mappers, such as the number of days of active mapping. In the second part of the analysis the study assesses Mapillary data completeness relative to a reference road network dataset at the country level. In addition, a more detailed completeness analysis is conducted for selected urban and rural areas in the US and part of northern Europe for which the completeness of Mapillary data will also be compared with that of Google Street View. Results show that Street View provides generally a better coverage on almost all road categories with some exceptions for pedestrian and cycle paths in selected cities. However, Mapillary data can be conveniently collected from any mobile device that is equipped with a photo camera. This gives Mapillary the potential to reach better coverage along off‐road segments than Google Street View.  相似文献   

Proposal of a New Parameter for the Weathering Characterization of Carbonate Flysch-Like Rock Masses: The Potential Degradation Index (PDI)     

M. Cano  R. Tomás 《Rock Mechanics and Rock Engineering》2016,49(7):2623-2640

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Multi-stage evolution of xenotime–(Y) from Písek pegmatites,Czech Republic: an electron probe micro-analysis and Raman spectroscopy study     

E. Švecová  R. Čopjaková  Z. Losos  R. Škoda  L. Nasdala  J. Cícha 《Mineralogy and Petrology》2016,110(6):747-765

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Urban seismic risk index for Medellín,Colombia, based on probabilistic loss and casualties estimations     

Mario A. Salgado-Gálvez  Daniela Zuloaga Romero  César A. Velásquez  Martha L. Carreño  Omar-Darío Cardona  Alex H. Barbat 《Natural Hazards》2016,80(3):1995-2021

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A Markov regime-switching framework to forecast El Niño Southern Oscillation patterns     

Iván Cárdenas-Gallo  Raha Akhavan-Tabatabaei  Mauricio Sánchez-Silva  Emilio Bastidas-Arteaga 《Natural Hazards》2016,81(2):829-843

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Forecast model of allergenic hazard using trends of Poaceae airborne pollen over an urban area in SW Iberian Peninsula (Europe)     

Santiago Fernández-Rodríguez  Pablo Durán-Barroso  Inmaculada Silva-Palacios  Rafael Tormo-Molina  José María Maya-Manzano  Ángela Gonzalo-Garijo 《Natural Hazards》2016,84(1):121-137

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