Characteristics of the Asian–Pacific Oscillation in Boreal Summer Simulated by BCC_CSM with Different Horizontal Resolutions

The summer Asian–Pacific Oscillation(APO) is a major teleconnection pattern that reflects the zonal thermal contrast between East Asia and the North Pacific in the upper troposphere. The performance of Beijing Climate Center Climate System Models(BCC CSMs) with different horizontal resolutions, i.e., BCC CSM1.1 and BCC CSM1.1(m), in reproducing APO interannual variability, APO-related precipitation anomalies, and associated atmospheric circulation anomalies, is evaluated.The results show that BCC CSM1.1(m) can successfully capture the interannual variability of the summer APO index. It is also more capable in reproducing the APO's spatial pattern, compared to BCC CSM1.1, due to its higher horizontal resolution. Associated with a positive APO index, the northward-shifted and intensified South Asian high, strengthened extratropical westerly jet, and tropical easterly jet in the upper troposphere, as well as the southwesterly monsoonal flow over North Africa and the Indian Ocean in the lower troposphere, are realistically represented by BCC CSM1.1(m), leading to an improvement in reproducing the increased precipitation over tropical North Africa, South Asia, and East Asia, as well as the decreased precipitation over subtropical North Africa, Japan, and North America. In contrast, these features are less consistent with observations when simulated by BCC CSM1.1. Regression analysis further indicates that surface temperature anomalies over the North Pacific and the southern and western flanks of the Tibetan Plateau are reasonably reproduced by BCC CSM1.1(m), which contributes to the substantial improvement in the simulation of the characteristics of summer APO compared to that of BCC CSM1.1.     

An algorithm to retrieve precipitation with synthetic aperture radar

This paper presents a new type of rainfall retrieval algorithm, called the model-oriented statistical and Volterra integration. It is a combination of the model-oriented statistical (MOS) and Volterra integral equation (VIE) approaches. The steps involved in this new algorithm can be briefly illustrated as follows. Firstly, information such as the start point and width of the rain is obtained through pre-analysis of the data received by synthetic aperture radar (SAR). Secondly, the VIE retrieval algorithm is employed over a short distance to obtain information on the shape of the rain. Finally, the rain rate can be calculated by using the MOS retrieval algorithm. Simulation results show that the proposed algorithm is effective and simple, and can lead to time savings of nearly 50% compared with MOS. An example of application of SAR data is also discussed, involving the retrieval of precipitation information over the South China Sea.     

Estimation of Above Ground Biomass for Central Indian Deciduous Forests Using ALOS PALSAR L-Band Data

Reliable and accurate estimates of tropical forest above ground biomass (AGB) are important to reduce uncertainties in carbon budgeting. In the present study we estimated AGB of central Indian deciduous forests of Madhya Pradesh (M.P.) state, India, using Advanced Land Observing Satellite – Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR) L-band data of year 2010 in conjunction with field based AGB estimates using empirical models. Digital numbers of gridded 1?×?1° dual polarization (HH & HV) PALSAR mosaics for the study area were converted to normalized radar cross section (sigma naught - σ⁰). A total of 415 sampling plots (0.1 ha) data collected over the study area during 2009–10 was used in the present study. Plot-level AGB estimates using volume equations representative to the study area were computed using field inventory data. The plot-level AGB estimates were empirically modeled with the PALSAR backscatter information in HH, HV and their ratios from different forest types of the study area. The HV backscatter information showed better relation with field based AGB estimates with a coefficient of determination (R²) of 0.509 which was used to estimate spatial AGB of the study area. Results suggested a total AGB of 367.4 Mt for forests of M.P. state. Further, validation of the model was carried out using observed vs. predicted AGB estimates, which suggested a root mean square error (RMSE) of ±19.32 t/ha. The model reported robust and defensible relation for observed vs. predicted AGB values of the study area.     

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

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.     

Is the long-term variation of the estimated GPS differential code biases associated with ionospheric variability?

The global positioning system (GPS) differential code biases (DCB) provided by the International GNSS Service (IGS) show solar-cycle-like variation during 2002–2013. This study is to examine whether this variation of the GPS DCBs is associated with ionospheric variability. The GPS observations from low earth orbit (LEO) satellites including CHAMP, GRACE and Jason-1 are used to address this issue. The GPS DCBs estimated from the LEO-based observations at different orbit altitudes show a similar tendency as the IGS DCBs. However, this solar-cycle-like dependency is eliminated when the DCBs of 13 continuously operating GPS satellites are constrained to zero-mean. Our results thus revealed that ionospheric variation is not responsible for the long-term variation of the GPS DCBs. Instead, it is attributed to the GPS satellite replacement with different satellite types and the zero-mean condition imposed on all satellite DCBs.     

Investigation of Cycle Time Segments of Dragline Operation in Surface Coal Mine: A Statistical Approach

Dragline is highly capital intensive equipment to procure, operate and maintain in any surface mining operation. Given this, every second of operation of this capital intensive equipment is absolutely important. Improvement of even a single second in the total cycle time has a tremendous bearing on the overall performance of this equipment. In this light, the present paper is an endeavour to critically analyze the cycle time of dragline operations in a major surface coal mine in India. Rigorous statistical analysis has been performed on individual cycle time segments, of complete dragline cycle. The segmental cycle times have been found to be statistically significant and appear to be best represented by lognormal, normal and beta distributions. Furthermore, the mean time of the statistical distribution for segmental cycle time of dragline has revealed the dependence of cycle time on cut geometry and depth. Results have been illustrated in the form of figures, graphs and tables.     

Compromise not consensus: designing a participatory process for landslide risk mitigation

With the escalating costs of landslides, the challenge for local authorities is to develop institutional arrangements for landslide risk management that are viewed as efficient, feasible and fair by those affected. For this purpose, the participation of stakeholders in the decision-making process is mandated by the European Union as a way of improving its perceived legitimacy and transparency. This paper reports on an analytical-deliberative process for selecting landslide risk mitigation measures in the town of Nocera Inferiore in southern Italy. The process was structured as a series of meetings with a group of selected residents and several parallel activities open to the public. The preparatory work included a literature/media review, semi-structured interviews carried out with key local stakeholders and a survey eliciting residents’ views on landslide risk management. The main point of departure in the design of this process was the explicit elicitation and structuring of multiple worldviews (or perspectives) among the participants with respect to the nature of the problem and its solution. Rather than eliciting preferences using decision analytical methods (e.g. utility theory or multi-criteria evaluation), this process built on a body of research—based on the theory of plural rationality—that has teased out the limited number of contending and socially constructed definitions of problem-and-solution that are able to achieve viability. This framing proved effective in structuring participants’ views and arriving at a compromise recommendation (not, as is often aimed for, a consensus) on measures for reducing landslide risk. Experts played a unique role in this process by providing a range of policy options that corresponded to the different perspectives held by the participants.     

An Overview of Electrokinetic Consolidation of Soils

Electrokinetic stabilization is one of the techniques that improve the geotechnical properties of the soils. It was pioneered by Casagrande in late 1940s and has not seen much development since then, especially in large-scale field applications. Some bench scale studies have been carried out during the past two decades and there have been some small scale field studies and limited field applications, mostly on soft soils. Due to lack of understanding of the physiochemical and electrochemical changes in the soil during electrokinetic stabilization, uncertain energy costs, loss of efficiency with time and the corrosion of electrodes, this method is usually considered as a last resort for large-scale practical applications. The objective of this paper is to highlight the critical parameters affecting electrokinetic consolidation, and to discuss their effects on the efficiency of the process. A better understanding of these critical parameters and their effects will enable geotechnical engineers to design the electrokinetic consolidation operation more effectively and make it an economically viable process for many situations.     

Complexity measurement of regional groundwater resources system using improved Lempel-Ziv complexity algorithm

In this paper, the self-adaptive artificial fish swarm algorithm (SAAFSA) is used to optimize the coarse graining of segment numbers, which are used in the Lempel-Ziv complexity algorithm. This approach improves the Lempel-Ziv complexity (LZC) algorithm of equal probability coarse graining. As a case study, the complexities of monthly series of groundwater depth were analyzed at seven farms in the Hongxinglong Administration. GIS technology was used to create spatial distributions of monthly groundwater depths. A projection pursuit model based on the SAAFSA was established and used for complexity attribution analysis at selected farms with different degrees of complexity. The three selected farms, Hongqiling, 852, and Youyi, each represent a certain degree of complexity. Further analysis shows that precipitation, evaporation, temperature, and human activities are the primary factors that cause complexity variations in local groundwater depth. The results reveal the evolution of the complexity characteristics of local groundwater depth and provide scientific evidence for the need to effectively allocate regional water resources. Additionally, the proposed method can be applied in complexity analyses of other hydrologic features, as well as in research regarding nonlinear time series in economic, engineering, medical, and signal analyses.