2017 ◽  
Vol 21 (3) ◽  
pp. 1573-1591 ◽  
Author(s):  
Louise Crochemore ◽  
Maria-Helena Ramos ◽  
Florian Pappenberger ◽  
Charles Perrin

Abstract. Many fields, such as drought-risk assessment or reservoir management, can benefit from long-range streamflow forecasts. Climatology has long been used in long-range streamflow forecasting. Conditioning methods have been proposed to select or weight relevant historical time series from climatology. They are often based on general circulation model (GCM) outputs that are specific to the forecast date due to the initialisation of GCMs on current conditions. This study investigates the impact of conditioning methods on the performance of seasonal streamflow forecasts. Four conditioning statistics based on seasonal forecasts of cumulative precipitation and the standardised precipitation index were used to select relevant traces within historical streamflows and precipitation respectively. This resulted in eight conditioned streamflow forecast scenarios. These scenarios were compared to the climatology of historical streamflows, the ensemble streamflow prediction approach and the streamflow forecasts obtained from ECMWF System 4 precipitation forecasts. The impact of conditioning was assessed in terms of forecast sharpness (spread), reliability, overall performance and low-flow event detection. Results showed that conditioning past observations on seasonal precipitation indices generally improves forecast sharpness, but may reduce reliability, with respect to climatology. Conversely, conditioned ensembles were more reliable but less sharp than streamflow forecasts derived from System 4 precipitation. Forecast attributes from conditioned and unconditioned ensembles are illustrated for a case of drought-risk forecasting: the 2003 drought in France. In the case of low-flow forecasting, conditioning results in ensembles that can better assess weekly deficit volumes and durations over a wider range of lead times.


2017 ◽  
Vol 46 (25) ◽  
pp. 8259-8268 ◽  
Author(s):  
Wan-Ying Zhang ◽  
Yong-Mei Tian ◽  
Hong-Feng Li ◽  
Peng Chen ◽  
Yi-Quan Zhang ◽  
...  

A series of linear trinuclear complexes Ln2M(OQ)8 [Ln(iii) = Dy and Er, M(ii) = Ca and Mg] were structurally and magnetically investigated.


2018 ◽  
Author(s):  
Xinyi Dong ◽  
Joshua S. Fu ◽  
Qingzhao Zhu ◽  
Jian Sun ◽  
Jiani Tan ◽  
...  

Abstract. Haze has been severely affecting the densely populated areas in China during recent years. While many of the pilot studies have been devoted to investigate the contributions from local anthropogenic emission, limited attention has been paid to the influence from long-range transport. In this study, we use simulations from 6 participating models supplied through the Task Force on Hemispheric Transport of Air Pollution Phase 2 (HTAP2) exercise to investigate the long-range transport impact of Europe and Russia/Belarussia/Ukraine on the surface air quality in East Asia, with special focus on their contributions during the haze episodes over China. The impact of 20 % anthropogenic emission perturbation from the source region is extrapolated by a factor of 5 to estimate the full impact. We find that the full impacts from EUR and RBU are 0.99 µg/m3 (3.1 %) and 1.32 µg/m3 (4.1 %) respectively during haze episodes, while the annual averaged full impacts are only 0.35 µg m3 (1.7 %) and 0.53 µg/m3 (2.6 %) respectively. By estimating the aerosol response within and above the planetary boundary layer (PBL), we find that long-range transport within the PBL contributes to 22–38 % of the total column density of aerosol response. Comparison with the HTAP Phase 1 (HTAP1) assessment reveals that from 2000 to 2010, the long-range transport from Europe to East Asia has decreased significantly by a factor of 2–10 for surface aerosol mass concentration due to the simultaneous emission reduction in source region and emission increase in the receptor region. By investigating the visibility response, we find that the long-range transport from the Europe and RBU region increases the number of haze events in China by 0.15 % and 0.11 % respectively, and the North China Plain and southeast China receives 1–3 extra haze days. This study is the first investigation into the contribution of long-range transport to haze in China with multiple model experiments.


Stroke ◽  
2019 ◽  
Vol 50 (Suppl_1) ◽  
Author(s):  
Barbara K Marebwa ◽  
Janina Wilmskotter ◽  
Brielle Stark ◽  
Lisa Johnson ◽  
Julius Fridriksson ◽  
...  

Author(s):  
Nuru I. Sarkar ◽  
Kashif Nisar ◽  
Layangi Babbage

The Advanced Network Technologies is research that investigates technology(s) behind today’s modern networks and network infrastructures. One part of this technology being Asynchronous Transfer Mode (ATM). A technology commonly in place in networks all around the world today. This paper focuses on ATM. Dubbed “Modelling and Performance Studies of ATM Networks”; this research seeks to look at and into the “impact of application segment length on the performance of an ATM network” and the “impact of traffic type data on the performance of an ATM network”. To be able to examine an ATM network, the authors need to be able to simulate a network. Thus, for this research, they have used the OPNET Modeler 14.0 Simulation software to create a network model that represents a ATM network. By actually simulating an ATM network at AUT University New Zealand, the authors can therefore change certain variables, and observe the effects the changes have on performance. As stated, one of the impacts that will be explored is the effect that application segment length has on an ATM network. Thus, one variable that will be changed in the authors’ simulation is the segment length. This is the length of each packet segment that is sent through the network for a particular traffic type. The second impact to be inspected is the impact of different traffic types on an ATM network. This network model is based on a campus network. An Application Configuration is setup with default parameters which specify 8 common applications used. Among them the ones that the authors will focus on are VOIP, Video and FTP. A Profile Configuration is setup that will define the 3 applications stated above. A fixed node model of 100BaseT will specify the profile configuration for each scenario and the number of work stations of each scenario.


2012 ◽  
Vol 3 (3) ◽  
pp. 47-56
Author(s):  
Kashif Nisar ◽  
Nurul I. Sarkar

The Advanced Network Technologies is a research that investigates the technology(s) behind today’s modern networks and network infrastructures one of these technologies being Asynchronous Transfer Mode (ATM). Therefore, also focuses its attention on ATM. Dubbed “Modelling and Performance Studies of ATM Networks”; this research seeks to look at, and into, the impact of application segment length on the performance of an ATM network and the impact of traffic type data on the performance of an ATM network. To be able to examine an ATM network, we need to be able to simulate it somehow. This research, the authors have used the OPNET Modeler 14.0 simulation tool to create a network model that represents a real-life ATM network. And by actually simulating an ATM network at AUT University New Zealand, they can therefore change certain variables, and observe the effects the changes have on performance. As stated above, one of the impacts that will be explored is the effect that application segment length has on an ATM network. Thus, one variable that will be changed in our simulation is the segment length. This is the length of each packet segment that is sent through the network for a particular traffic type. The second impact to be inspected is the impact of different traffic types on an ATM network. For example, voice & video traffic should theoretically affect an ATM network


Atmosphere ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 48 ◽  
Author(s):  
Changhan Bae ◽  
Byeong-Uk Kim ◽  
Hyun Cheol Kim ◽  
Chul Yoo ◽  
Soontae Kim

This study identified the key chemical components based on an analysis of the seasonal variations of ground level PM2.5 concentrations and its major chemical constituents (sulfate, nitrate, ammonium, organic carbon, and elemental carbon) in the Seoul Metropolitan Area (SMA), over a period of five years, ranging from 2012 to 2016. It was found that the mean PM2.5 concentration in the SMA was 33.7 μg/m3, while inorganic ions accounted for 53% of the total mass concentration. The component ratio of inorganic ions increased by up to 61%–63% as the daily mean PM2.5 concentration increased. In spring, nitrate was the dominant component of PM2.5, accounting for 17%–32% of the monthly mean PM2.5 concentrations. In order to quantify the impact of long-range transport on the SMA PM2.5, a set of sensitivity simulations with the community multiscale air-quality model was performed. Results show that the annual averaged impact of Chinese emissions on SMA PM2.5 concentrations ranged from 41% to 44% during the five years. Chinese emissions’ impact on SMA nitrate ranged from 50% (winter) to 67% (spring). This result exhibits that reductions in SO2 and NOX emissions are crucial to alleviate the PM2.5 concentration. It is expected that NOX emission reduction efforts in China will help decrease PM2.5 concentrations in the SMA.


Materials ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 875
Author(s):  
Aleksander Promiński ◽  
Ewelina Tomczyk ◽  
Mateusz Pawlak ◽  
Agnieszka Jędrych ◽  
Józef Mieczkowski ◽  
...  

Achieving remotely controlled, reversibly reconfigurable assemblies of plasmonic nanoparticles is a prerequisite for the development of future photonic technologies. Here, we obtained a series of gold-nanoparticle-based materials which exhibit long-range order, and which are controlled with light or thermal stimuli. The influence of the metallic core size and organic shell composition on the switchability is considered, with emphasis on achieving light-responsive behavior at room temperature and high yield production of nanoparticles. The latter translates to a wide size distribution of metallic cores but does not prevent their assembly into various, switchable 3D and 2D long-range ordered structures. These results provide clear guidelines as to the impact of size, size distribution, and organic shell composition on self-assembly, thus enhancing the smart design process of multi-responsive nanomaterials in a condensed state, hardly attainable by other self-assembly methods which usually require solvents.


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