CMIP5 model simulations of warm Arctic-cold Eurasia pattern in winter surface air temperature anomalies

Climate Dynamics - The second empirical orthogonal function mode (EOF2) of winter surface air temperature (SAT) over 0°–180° E, 40°–90° N during 1979–2005 is...     

Verification and mitigation of the power-induced measurement errors for airport pseudolites in LAAS

Certain GPS receivers exhibit a power-induced measurement error when the input signal power exceeds a certain threshold that is a function of the receiver architecture. The characterization of this error is important in the case of airport pseudolites (APLs) due to receiver saturation at ranges close to the transmission antenna. This paper details an effort using laboratory test to characterize the power-induced measurement error in NovAtel Millennium and Beeline receivers that are widely used for APL development. The results from the laboratory tests show that this effect can lead to errors as large as 3 m on pseudorange measurement for the dynamic range typical for APLs. The carrier-phase error however is seen to be limited to 5 cm. On the verification and characterization of the error, a cost-effective mitigation technique for LAAS is proposed. A solution for the ground subsystem is sought by employing power-control measures to limit the amount of APL power that LGF GPS/APL receivers are exposed to. In order to keep the integration cost low, the solution for the airborne subsystem does not involve hardware modifications or additions, but rather relies on the transition to a differential carrier-phase positioning algorithm prior to the onset of the power-induced error along the approach path. The proposed architecture was flight-tested to verify successful mitigation of the power-induced error on both the ground and air, and the results from these tests are presented in the paper.     

Sheeted dykes in Kandra ophiolite complex,Nellore schist belt,Andhra Pradesh — Vestiges of Precambrian oceanic crust

Extensive field and petrological studies carried out in Kandra ophiolite complex (KOC) in the southern part of Nellore schist belt (NSB) revealed the existence of sheeted dykes in Kandra- Kondakuru-Gollapalli section. The sheeted dykes occur in the northern part of the complex and compositionally vary from medium-grained dolerites showing typical sub-ophitic texture to diabase dykes that are extremely fine grained aphanitic to fine-grained cryptocrystalline parallel basic dykes (varying in width from 4 cm to 1.25 m). These dykes show chilled margins on either side with the host dykes into which these are intruded. Veins of oceanic plagiogranite (0.5 × 5 m) are noticed in a major sheeted dyke. Occurrence of oceanic plagiogranite as ovoid / semicircular patches of 6 cm diameter resembling “immiscible droplets” within basic dykes is also noticed. The southern part of the complex is made of a major NW-SE trending cumulus gabbro that grades into olivine gabbronorite in its eastern part. The southern gabbros represent the plutonic component and form the deeper part of the complex. In this paper an attempt has been made to present the field, petrographic and mineral chemistry account of various lithounits that constitute the Kandra ophiolite complex in a succinct manner.     

Swarm intelligence-based solver for parameter estimation of laboratory through-diffusion transport of contaminants

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated by fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. These parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.     

Development of a diatom-based specific conductivity model for the glacio-isostatic lakes of Truelove Lowland: implications for paleoconductivity and paleoenvironmental reconstructions in Devon Island lakes, N.W.T., Canada

Diatoms are identified and enumerated from the surface sediments of 100 lakes of Truelove Lowland, Devon Island, N.W.T., Canada. These lakes range from large oligotrophic lakes, to small tundra ponds, to coastal marine lagoons which are diverse in terms of ionic concentration and composition. The relationship between diatoms and 15 limnological variables is examined using Canonical Correspondence Analysis (CCA). Specific conductivity is identified as the most important variable influencing the distribution of diatoms in the Truelove lakes. A Weighted Averaging (WA) calibration model is developed to predict diatom-inferred specific conductivity. The reliability of the model is tested by evaluating the correlation between observed and diatom-inferred values and determining the error of prediction by bootstrapping. The applicability of the predictive conductivity equation is demonstrated by reconstructing the paleoconductivity history of Fish Lake.     

经验方法研究下垫面变化对洪水的影响

1980s以来,人类活动对下垫面的影响加剧,研究下垫面变化对流域产汇流规律的影响具有重要意义.通过对海河流域中紫荆关、阜平两个流域分别用经验方法进行洪水模拟演算,并把洪水资料按照年代不同分时段,建立P+Pa～Rs相关关系图,分析流域下垫面变化对降雨径流相关关系的影响.建立产流量R与洪峰Qm之间的相关关系,通过统计比较不同年代的趋势线发现,在产流量相同情况下,1980s后的洪峰流量较1980s前有所减少,说明海河流域的调蓄作用有增强的趋势.同时建立流域下垫面条件改变后产流量与洪峰变化幅度的相关关系,发现流域产流量变化与洪峰变化呈正相关关系.     

Detection of ionospheric scintillation effects using LMD–DFA

The performance and measurement accuracy of global navigation satellite system (GNSS) receivers is greatly affected by ionospheric scintillations. Rapid amplitude and phase variations in the received GPS signal, known as ionospheric scintillation, affects the tracking of signals by GNSS receivers. Hence, there is a need to investigate the monitoring of various activities of the ionosphere and to develop a novel approach for mitigation of ionospheric scintillation effects. A method based on Local Mean Decomposition (LMD)–Detrended Fluctuation Analysis (DFA) has been proposed. The GNSS data recorded at Koneru Lakshmaiah (K L) University, Guntur, India were considered for analysis. The carrier to noise ratio (C/N₀) of GNSS satellite vehicles were decomposed into several product functions (PF) using LMD to extract the intrinsic features in the signal. Scintillation noise was removed by the DFA algorithm by selecting a suitable threshold. It was observed that the performance of the proposed LMD–DFA was better than that of empirical mode decomposition (EMD)–DFA.     

Multi-objective optimal design for flood risk management with resilience objectives

In flood risk management, the divergent concept of resilience of a flood defense system cannot be fully defined quantitatively by one indicator and multiple indicators need to be considered simultaneously. In this paper, a multi-objective optimization (MOO) design framework is developed to determine the optimal protection level of a levee system based on different resilience indicators that depend on the probabilistic features of the flood damage cost arising under the uncertain nature of rainfalls. An evolutionary-based MOO algorithm is used to find a set of non-dominated solutions, known as Pareto optimal solutions for the optimal protection level. The objective functions, specifically resilience indicators of severity, variability and graduality, that account for the uncertainty of rainfall can be evaluated by stochastic sampling of rainfall amount together with the model simulations of incurred flood damage estimation for the levee system. However, these model simulations which usually require detailed flood inundation simulation are computationally demanding. This hinders the wide application of MOO in flood risk management and is circumvented here via a surrogate flood damage modeling technique that is integrated into the MOO algorithm. The proposed optimal design framework is applied to a levee system in a central basin of flood-prone Jakarta, Indonesia. The results suggest that the proposed framework enables the application of MOO with resilience objectives for flood defense system design under uncertainty and solves the decision making problems efficiently by drastically reducing the required computational time.