•Rainfall series in the UAE are analyzed for detection of trends and change points.•The modified M–K test is applied for the assessment of the significance of trends.•The original results lead ...towards a general decreasing trend in precipitations.•Bayesian analysis reveals an increasing trend with a downward shift in 1999.•Results indicate a seasonality change with rain occurring earlier in the winter.
Arid and semiarid climates occupy more than 1/4 of the land surface of our planet, and are characterized by a strongly intermittent hydrologic regime, posing a major threat to the development of these regions. Despite this fact, a limited number of studies have focused on the climatic dynamics of precipitation in desert environments, assuming the rainfall input – and their temporal trends – as marginal compared with the evaporative component. Rainfall series at four meteorological stations in the United Arab Emirates (UAE) were analyzed for assessment of trends and detection of change points. The considered variables were total annual, seasonal and monthly rainfall; annual, seasonal and monthly maximum rainfall; and the number of rainy days per year, season and month. For the assessment of the significance of trends, the modified Mann–Kendall test and Theil-Sen’s test were applied. Results show that most annual series present decreasing trends, although not statistically significant at the 5% level. The analysis of monthly time series reveals strong decreasing trends mainly occurring in February and March. Many trends for these months are statistically significant at the 10% level and some trends are significant at the 5% level. These two months account for most of the total annual rainfall in the UAE. To investigate the presence of sudden changes in rainfall time-series, the cumulative sum method and a Bayesian multiple change point detection procedure were applied to annual rainfall series. Results indicate that a change point happened around 1999 at all stations. Analyses were performed to evaluate the evolution of characteristics before and after 1999. Student’s t-test and Levene’s test were applied to determine if a change in the mean and/or in the variance occurred at the change point. Results show that a decreasing shift in the mean has occurred in the total annual rainfall and the number of rainy days at all four stations, and that the variance has decreased for the total annual rainfall at two stations. Frequency analysis was also performed on data before and after the change point. Results show that rainfall quantile values are significantly lower after 1999. The change point around the year 1999 is linked to various global climate indices. It is observed that the change of phase of the Southern Oscillation Index (SOI) has strong impact over the UAE precipitation. A brief discussion is presented on dynamical basis, the teleconnections connecting the SOI and the change in precipitation regime in the UAE around the year 1999.
•We assessed the goodness-of-fit of different distributions to wind speed data in the UAE.•Performances of parametric, mixture and non-parametric distributions are compared.•Mixture of two-component ...Weibull distribution gives the overall best fit.•The Kappa and Generalized Gamma are the parametric distributions giving the best fit.
For the evaluation of wind energy potential, probability density functions (pdfs) are usually used to describe wind speed distributions. The selection of the appropriate pdf reduces the wind power estimation error. The most widely used pdf for wind energy applications is the 2-parameter Weibull probability density function. In this study, a selection of pdfs are used to model hourly wind speed data recorded at 9 stations in the United Arab Emirates (UAE). Models used include parametric models, mixture models and one non-parametric model using the kernel density concept. A detailed comparison between these three approaches is carried out in the present work. The suitability of a distribution to fit the wind speed data is evaluated based on the log-likelihood, the coefficient of determination R2, the Chi-square statistic and the Kolmogorov–Smirnov statistic. Results indicate that, among the one-component parametric distributions, the Kappa and Generalized Gamma distributions provide generally the best fit to the wind speed data at all heights and for all stations. The Weibull was identified as the best 2-parameter distribution and performs better than some 3-parameter distributions such as the Generalized Extreme Value and 3-parameter Lognormal. For stations presenting a bimodal wind speed regime, mixture models or non-parametric models were found to be necessary to model adequately wind speeds. The two-component mixture distributions give a very good fit and are generally superior to non-parametric distributions.
ABSTRACT
This study discusses the evolution of temperature, precipitation and soil moisture patterns over the United Arab Emirates (UAE) region, which is characterized by hot climate and scarce ...precipitation. A stochastic model that reproduces non‐stationary oscillation (NSO) processes by utilizing ensemble empirical mode decomposition (EEMD) and non‐parametric techniques is used to predict the evolution of temperature, precipitation and soil moisture. The long‐term gridded temperature, precipitation and soil moisture data from the Global Historic Climatic Network, Global Precipitation Climatology Center and Climate Prediction Center are used in this study. The data consists of 65 years of average monthly temperature and soil moisture measurements and 110 years of average monthly precipitation over the UAE. The last 20 years of observations of temperature, precipitation and soil moisture are reserved for the validation of the methodology and the rest of the data is used for prediction. The results show that future long‐term patterns are well captured by the model and hence confirm the potential of the EEMD technique and the NSO resampling (NSOR) modelling process. The model is also used for forecasting the evolution of temperature, precipitation and soil moisture patterns for the next 30 years. This procedure is finally used to produce the spatial patterns of temperature, precipitation and soil moisture. Significant increase in temperature and decrease in precipitation and soil moisture are observed particularly over Abu Dhabi. The spatial map shows strong increase (decrease) in temperature (precipitation and soil moisture) over most of the UAE. The results are quite different for the south eastern part of the UAE. Western parts of the UAE are projected to see larger temperature increases than other parts. The results are coherent with the previous findings over this region.
The 15 papers in this special issue examine the use of remote sensing in urban locations. This research reflects the current status of the rapid urban growth and application of remote sensing to ...address these challenges. Urban growth models predict rapid increases in extent and populations all over the world. It is anticipated that over two-thirds of the population will live in cities by 2050. The fastest growing cities in the world are in the developing countries where the infrastructure growth has not been matching the urban growth thereby creating a range of socio-economic issues. In developed countries, urban monitoring mainly consists in tracking more subtle changes and densification within cities. In both cases, poorly planned urbanization can lead to greater risks to the quality of life and thereby significant economic risks.
This work presents a detailed study of the dynamical processes triggering the occurrence of the two heavy dust storms which occurred between 18 and 22 March 2012 over the Middle East. The dynamics of ...this event are related to the coupling of subtropical jet and polar jet over the Saudi Arabia region, resulting in massive dust storm generation and dust transport through Rub’ al Khali and the Persian Gulf to the UAE region. AOD and PM10 values showed a fourfold increase during the event reaching a maximum of 1.8 and 1653μg/m3 respectively. The spatial extent of the dust storm is evident from high values of MODIS AOD (~1.5) and OMI aerosol index (4.5) covering the entire Middle East. The total attenuated backscatter at 550nm from CALLIPSO showed the vertical extent of dust up to 8km. In addition, surface temperature showed a decrease of almost 15°C during the event signifying the intensity of the dust storm. Aerosol radiative forcing estimates during the dust storm showed a cooling at the surface and warming in the atmosphere, with a maximum forcing value reaching up to ~−210Wm−2 (185 Wm−2). Hence, it is evident from the present study that the dust layer caused an additional warming of ~150Wm−2 in the atmosphere over this region. The present event showcases the importance of dust storm induced aerosol optical and physical processes, and associated atmospheric dynamics over UAE as well as other affected regions.
Extended Attribute Profiles (EAPs), which are obtained by applying morphological attribute filters to an image in a multilevel architecture, can be used for the characterization of the spatial ...characteristics of objects in a scene. EAPs have proved to be discriminant features when considered for thematic classification in remote sensing applications especially when dealing with very high resolution images. Altimeter data (such as LiDAR) can provide important information, which being complementary to the spectral one can be valuable for a better characterization of the surveyed scene. In this paper, we propose a technique performing a classification of the features extracted with EAPs computed on both optical and LiDAR images, leading to a fusion of the spectral, spatial and elevation data. The experiments were carried out on LiDAR data along either with a hyperspectral and a multispectral image acquired on a rural and urban area of the city of Trento (Italy), respectively. The classification accuracies obtained pointed out the effectiveness of the features extracted by EAPs on both optical and LiDAR data for classification.
The analysis of multi-temporal remote-sensing images is one of the main applications in Earth’s observation and monitoring. In this paper, we present a Matlab toolbox for change detection analysis of ...optical multi-temporal remote-sensing data in which unsupervised approaches, iterative principal component analysis (ITPCA), and iteratively reweighted multivariate alteration detection (IR-MAD) are implemented and optimized. The optimization is represented by the implementation of novel pre- and post-processing strategies that aim to mitigate the side effects introduced by different acquisition conditions affecting change detection analysis. Special modules have been designed in order to decrease the required memory when large data sets are processed.
Herein, we report strain- and damage-sensing performance of biocompatible smart CNT/UHMWPE nanocomposites for the first time. CNT/UHMWPE nanocomposites are fabricated by solution mixing followed by ...compression molding. The surface morphology, microstructural properties, thermal decomposition and stability, glass transition temperature and thermal conductivity of the nanocomposites are characterized. The degree of crystallinity of CNT/UHMWPE nanocomposites is found to have a maximum value of 52% at 0.1 wt% CNT loading. The degree of crystallinity influences the mechanical properties of the CNT/UHMWPE nanocomposites. The electrical percolation threshold is achieved at 0.05 wt% of CNT and it follows a two dimensional conductive network according to percolation theory. The piezoresistive response of CNT/UHMWPE nanocomposites is demonstrated with a gauge factor of ~2.0 in linear elastic regime and that in the range of 3.8–96.0 in inelastic regimes for 0.05 wt% of CNT loading. A simple theoretical model is also developed to predict the resistivity evolution in both elastic and inelastic regimes. High sensitivity of CNT/UHMWPE nanocomposites coupled with linear piezoresistive response up to 100% strain demonstrates their potential for application in artificial implants as a self-sensing material.
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•Self-sensing performance of CNT/UHMWPE nanocomposites is reported for the first time.•The electrical percolation threshold is achieved at 0.05 wt% of CNT loading.•CNT/UHMWPE nanocomposites exhibits a gauge factor of ~2.0 in linear elastic regime.•A simple theoretical model is developed to predict the resistivity evolution with stretch.•Strong piezoresistivity up to 100% strain demonstrates their candidacy for knee implants.
Object-based classification is a promising technique for image classification. Unlike pixel-based methods, which only use the measured radiometric values, the object-based techniques can also use ...shape and context information of scene textures. These extra degrees of freedom provided by the objects allow the automatic identification of geological structures. In this article, we present an evaluation of object-based classification in the context of extraction of geological faults. Digital elevation models and radar data of an area near Lake Magadi (Kenya) have been processed. We then determine the statistics of the fault populations. The fractal dimensions of fault dimensions are similar to fractal dimensions directly measured on remote sensing images of the study area using power spectra (PSD) and variograms. These methods allow unbiased statistics of faults and help us to understand the evolution of the fault systems in extensional domains. Furthermore, the direct analysis of image texture is a good indicator of the fault statistics and allows us to classify the intensity and type of deformation. We propose that extensional fault networks can be modeled by iterative function system (IFS).
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