Station-keeping for a translunar communication station

A translunar communication station is to be kept close to a nominal unstable periodic ‘Halo’ orbit, visible at all times from Earth. The analytically computed nominal orbit is not perfect, requiring an average control acceleration of about 10^?6 g's for tight control. An adjustable quadratic combination of position deviation and control acceleration is minimized to provide an (adjustable) control law with period feedback gains and a periodic bias. The average control acceleration can be reduced to less than 10^?8 g's with an error settling time of less than 21/2 months. The resulting limiting motion provides, in turn, an improved nominal, permitting the same low control cost with much tighter control, corresponding to settling times of the order of one day.     

A Time Monte Carlo method for addressing uncertainty in land-use change models

One of the main objectives of land-use change models is to explore future land-use patterns. Therefore, the issue of addressing uncertainty in land-use forecasting has received an increasing attention in recent years. Many current models consider uncertainty by including a randomness component in their structure. In this paper, we present a novel approach for tuning uncertainty over time, which we refer to as the Time Monte Carlo (TMC) method. The TMC uses a specific range of randomness to allocate new land uses. This range is associated with the transition probabilities from one land use to another. The range of randomness is increased over time so that the degree of uncertainty increases over time. We compare the TMC to the randomness components used in previous models, through a coupled logistic regression-cellular automata model applied for Wallonia (Belgium) as a case study. Our analysis reveals that the TMC produces results comparable with existing methods over the short-term validation period (2000–2010). Furthermore, the TMC can tune uncertainty on longer-term time horizons, which is an essential feature of our method to account for greater uncertainty in the distant future.     

Identifying Groundwater Potential in Crystalline Basement Rocks Using Remote Sensing and Electromagnetic Sounding Techniques in Central Western Mozambique

Exploring for groundwater in crystalline rocks in semiarid areas is a challenge because of their complex hydrogeology and low potential yields. An integrated approach was applied in central western Mozambique, in an area covered by Precambrian crystalline basement rocks. The approach combined a digital elevation model (DEM), remote sensing, and a ground-based geophysical survey. The aim was to identify groundwater zones with high potential and to identify geological structures controlling that potential. Lineaments were extracted from the DEM that had been enhanced using an adaptive-tilt, multi-directional, shading technique and a non-filtering technique to characterize the regional fracture system. The shallowness and amount of stored groundwater in the fracture zones was assessed using vegetation indices derived from Landsat 8 OLI images. Then, 14 transient electromagnetic (TEM) survey profiles were taken in different geological settings across continuous lineaments that were considered to be aligned along inferred faults. In the central lineament zones, the TEM soundings gave resistivity values of less than 300 Ωm at a depth of 20–80 m. The values varied with location. Conversely, values greater than 400 Ωm were observed at the sites away from the central zones. This contrast is probably caused by the differences in permeability and degree of weathering along the fractured zones. These differences could be key factors in determining groundwater occurrence. By integrating five water-related factors (lineament density, slope, geology, vegetation index, and proximity to lineaments), high groundwater potential zones were located in the vicinity of the lineaments. In these zones, vegetation remains active regardless of the season.     

Study of Aerosol Direct and Indirect Effects and Auto-conversion Processes over the West African Monsoon Region Using a Regional Climate Model

This study assesses the direct and indirect effects of natural and anthropogenic aerosols(e.g., black carbon and sulfate)over West and Central Africa during the West African monsoon(WAM) period(June–July–August). We investigate the impacts of aerosols on the amount of cloudiness, the influences on the precipitation efficiency of clouds, and the associated radiative forcing(direct and indirect). Our study includes the implementation of three new formulations of auto-conversion parameterization [namely, the Beheng(BH), Tripoli and Cotton(TC) and Liu and Daum(R6) schemes] in Reg CM4.4.1,besides the default model's auto-conversion scheme(Kessler). Among the new schemes, BH reduces the precipitation wet bias by more than 50% over West Africa and achieves a bias reduction of around 25% over Central Africa. Results from detailed sensitivity experiments suggest a significant path forward in terms of addressing the long-standing issue of the characteristic wet bias in Reg CM. In terms of aerosol-induced radiative forcing, the impact of the various schemes is found to vary considerably(ranging from-5 to-25 W m~(-2)).     

GPS Water Vapor and Its Comparison with Radiosonde and ERA-Interim Data in Algeria

Remote sensing of atmospheric water vapor using global positioning system(GPS) data has become an effective tool in meteorology,weather forecasting and climate research. This paper presents the estimation of precipitable water(PW)from GPS observations and meteorological data in Algeria,over three stations located at Algiers,Bechar and Tamanrasset.The objective of this study is to analyze the sensitivity of the GPS PW estimates for the three sites to the weighted mean temperature(T_m),obtained separately from two types of T_m–T_s regression [one general,and one developed specifically for Algeria(T_s stands for surface temperature)],and calculated directly from ERA-Interim data. The results show that the differences in T_m are of the order of 18 K,producing differences of 2.01 mm in the final evaluation of PW. A good agreement is found between GPS-PW and PW calculated from radiosondes,with a small mean difference with Vaisala radiosondes.A comparison between GPS and ERA-Interim shows a large difference(4 mm) in the highlands region. This difference is possibly due to the topography. These first results are encouraging,in particular for meteorological applications in this region,with good hope to extend our dataset analysis to a more complete,nationwide coverage over Algeria.     

Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

Theoretical and Applied Climatology - Snow is a key element for many socioeconomic activities in mountainous regions. Due to the sensitivity of the snow cover to variations of temperature and...     

Regularized Bayesian estimation for GEV-B-splines model

Large observed datasets are not stationary and/or depend on covariates, especially, in the case of extreme hydrometeorological variables. This causes the difficulty in estimation, using classical hydrological frequency analysis. A number of non-stationary models have been developed using linear or quadratic polynomial functions or B-splines functions to estimate the relationship between parameters and covariates. In this article, we propose regularised generalized extreme value model with B-splines (GEV-B-splines models) in a Bayesian framework to estimate quantiles. Regularisation is based on penalty and aims to favour parsimonious model especially in the case of large dimension space. Penalties are introduced in a Bayesian framework and the corresponding priors are detailed. Five penalties are considered and the corresponding priors are developed for comparison purpose as: Least absolute shrinkage and selection (Lasso and Ridge) and smoothing clipped absolute deviations (SCAD) methods (SCAD1, SCAD2 and SCAD3). Markov chain Monte Carlo (MCMC) algorithms have been developed for each model to estimate quantiles and their posterior distributions. Those approaches are tested and illustrated using simulated data with different sample sizes. A first simulation was made on polynomial B-splines functions in order to choose the most efficient model in terms of relative mean biais (RMB) and the relative mean-error (RME) criteria. A second simulation was performed with the SCAD1 penalty for sinusoidal dependence to illustrate the flexibility of the proposed approach. Results show clearly that the regularized approaches leads to a significant reduction of the bias and the mean square error, especially for small sample sizes (n < 100). A case study has been considered to model annual peak flows at Fort-Kent catchment with the total annual precipitations as covariates. The conditional quantile curves were given for the regularized and the maximum likelihood methods.     

Update earthquake risk assessment in Cairo,Egypt

The Cairo earthquake (12 October 1992; m _b  = 5.8) is still and after 25 years one of the most painful events and is dug into the Egyptians memory. This is not due to the strength of the earthquake but due to the accompanied losses and damages (561 dead; 10,000 injured and 3000 families lost their homes). Nowadays, the most frequent and important question that should rise is “what if this earthquake is repeated today.” In this study, we simulate the same size earthquake (12 October 1992) ground motion shaking and the consequent social-economic impacts in terms of losses and damages. Seismic hazard, earthquake catalogs, soil types, demographics, and building inventories were integrated into HAZUS-MH to produce a sound earthquake risk assessment for Cairo including economic and social losses. Generally, the earthquake risk assessment clearly indicates that “the losses and damages may be increased twice or three times” in Cairo compared to the 1992 earthquake. The earthquake risk profile reveals that five districts (Al-Sahel, El Basateen, Dar El-Salam, Gharb, and Madinat Nasr sharq) lie in high seismic risks, and three districts (Manshiyat Naser, El-Waily, and Wassat (center)) are in low seismic risk level. Moreover, the building damage estimations reflect that Gharb is the highest vulnerable district. The analysis shows that the Cairo urban area faces high risk. Deteriorating buildings and infrastructure make the city particularly vulnerable to earthquake risks. For instance, more than 90 % of the estimated buildings damages are concentrated within the most densely populated (El Basateen, Dar El-Salam, Gharb, and Madinat Nasr Gharb) districts. Moreover, about 75 % of casualties are in the same districts. Actually, an earthquake risk assessment for Cairo represents a crucial application of the HAZUS earthquake loss estimation model for risk management. Finally, for mitigation, risk reduction, and to improve the seismic performance of structures and assure life safety and collapse prevention in future earthquakes, a five-step road map has been purposed.     

DHI evaluation by combining rock physics simulation and statistical techniques for fluid identification of Cambrian-to-Cretaceous clastic reservoirs in Pakistan

The use of seismic direct hydrocarbon indicators is very common in exploration and reservoir development to minimise exploration risk and to optimise the location of production wells. DHIs can be enhanced using AVO methods to calculate seismic attributes that approximate relative elastic properties. In this study, we analyse the sensitivity to pore fluid changes of a range of elastic properties by combining rock physics studies and statistical techniques and determine which provide the best basis for DHIs. Gassmann fluid substitution is applied to the well log data and various elastic properties are evaluated by measuring the degree of separation that they achieve between gas sands and wet sands. The method has been applied successfully to well log data from proven reservoirs in three different siliciclastic environments of Cambrian, Jurassic, and Cretaceous ages. We have quantified the sensitivity of various elastic properties such as acoustic and extended elastic (EEI) impedances, elastic moduli (K _sat and K _sat–μ), lambda–mu–rho method (λρ and μρ), P-to-S-wave velocity ratio (V _P/V _S), and Poisson’s ratio (σ) at fully gas/water saturation scenarios. The results are strongly dependent on the local geological settings and our modeling demonstrates that for Cambrian and Cretaceous reservoirs, K _sat–μ, EEI, V _P/V _S, and σ are more sensitive to pore fluids (gas/water). For the Jurassic reservoir, the sensitivity of all elastic and seismic properties to pore fluid reduces due to high overburden pressure and the resultant low porosity. Fluid indicators are evaluated using two metrics: a fluid indicator coefficient based on a Gaussian model and an overlap coefficient which makes no assumptions about a distribution model. This study will provide a potential way to identify gas sand zones in future exploration.