The accurate forecast of wind speed is critical in the integration renewable energy within main electrical grid and an important factor for power stability, scheduling, planning. In this paper, we present deep learning algorithms, Long Short-Term Memory (LSTM), bidirectional LSTM algorithms (Bi-LSTM) using different configurations activation functions to evaluate experiments predict provisional trend speed. We used both models over Gabal Elzayt Wind Farm Egypt. data-set belongs NASA's...

Weather Research and Forecasting model coupled with chemistry (WRF-Chem) was used to simulate selected severe dust storm events over Egypt in terms of the aerosol optical depth (AOD). Two events, which occurred on 22 January 2004 31 March 2013, are examined. The analysis includes three emission schemes: Goddard Chemistry Aerosol Radiation Transport (GOCART), GOCART Air Force Agency (GOCART-AFWA), University Cologne (GOCART-UOC). Each scheme tested by adjusting coefficients related flux. AOD...

Aerosols are sources of the uncertainty in global atmosphere and climate. They have many critical health, economic social impacts. In this paper, we assess prediction temporal monthly Aerosol Optical Depth (AOD) over four dust within belt using three different algorithms. The models long-short term memory (LSTM), Convolutional neural networks-long-short (CNN-LSTM) (ConvLSTM). Classical Fast Fourier Transform (FFT) algorithm for time series predication is compared to networks models. Grid...

A decadal survey of atmospheric aerosols over Egypt and selected cities regions is presented using daily aerosol optical depth (AOD) data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) at 550 nm wavelength onboard the Aqua satellite. We explore AOD spatio-temporal variations during a 12-year record (2003 to 2014) MODIS high-resolution (10 km) Level 2 product. Five two geographic that feature different landscape human activities were for detailed analysis. For most examined...

Dust storms have severe environmental, economic, health, weather, and climate change impacts. A dust storm that hit Egypt on 22 January 2004 was selected as a case study to establish an accurate numerical model simulate over using the Weather Research Forecast with chemistry module (WRF-Chem). Two simulation setups WRF-Chem were conducted two geographic domains: first exclusively included sources within Egypt, while second external source, Bodélé Depression in southwestern Chad. The only...

Artificial Neural Networks (ANN) has been well studied for flood prediction. However, there is not enough empirical evidence to generalize ANN applicability small countries with microclimates prevailing in a geographical space. In this paper, we focus on the climatic conditions of Mauritius which seek investigate accuracy using predict flooding locally collected data from 11 meteorological stations spread across country. The model prediction presented work trained 20,000 climate records,...

In this work, sensitivity of ten microphysics schemes Weather Research and Forecasting model were compared to determine which is more accurate. A case study heavy rains over the Red Sea coast Egypt on 26th October 2016 that caused damaging floods subject study. Three coastal areas chosen, city Ras Ghareb, Wadi Elgemal National park, Elba park. The output precipitation from was satellite data obtained Tropical Rainfall Measuring Mission (TRMM). Our analysis showed has capability simulate...

The sulfur pollutants are the source of a sizeable portion air pollution. In this work, recent spatiotemporal distribution and trend mass concentration two critical pollutants, SO2 SO4, in addition to aerosol optical properties (AOD) were analyzed over region Middle East North Africa (MENA) from satellite Modern Era-Retrospective Analysis for Research Applications version 2 (MERRA-2) reanalysis data. SO4 data used these analyses obtained with resolution 0.5° × 0.625° throughout period 10...

The long-term temporal trends and spatial distribution of Ozone (O3) over Egypt is presented using monthly data from both the Atmospheric Infrared Sounder (AIRS) model Modern-Era Retrospective analysis for Research Applications (MERRA) datasets. twelve-year record (2005–2016) Total Column (TOC) has a resolution 1 × 1° AIRS 0.5 0.625° MERRA-2 dataset. average monthly, seasonal interannual time series are analyzed their trends, while distributions compared. It was found that underestimated...

Incomplete hydro-meteorological data and insufficient rainfall gauges have caused difficulties in establishing a reliable flood forecasting system. This study attempted to adopt the remotely sensed as an alternative incomplete observed poorly gauged Kuantan River Basin (KRB), main city at east coast of Peninsula Malaysia. Performance Weather Research Forecasting (WRF) schemes’ combinations, including eight microphysics (MP) six cumulus, were evaluated determine most suitable combination WRF...

Exact forecast of surface temperature over MARS is important and critical. Surface fundamental to the environmental parameter that has a direct impact on designing operating land rovers explore planet. In this paper, We used well known long Short-Term Memory (LSTM) algorithm build data-driven model predict planned landing site Jezero Crater for Mars 2020 Rover. The built using dataset based Climate Database (MCD) which derived from Global Model (GCM) simulations MARS. temporal availability...

Aerosol optical depth (AOD) is one of the most critical indicators for air quality. Estimation accurate AOD needs to include both dust and chemical reactions in calculations which are expensive from a computational point view. In this work, we present novel simple model estimate predict temporal trend based on well-known algorithm long-short term memory (LSTM). Five domains core study, Four popular cities Cairo, Alexandria, Aswan, Hurghada selected. addition sub-domain includes important...

Environmental systems including our atmosphere oceans, biological… etc. can be modeled by mathematical equations to estimate their states. These solved with numerical methods. Initial and boundary conditions are needed for such of these Predication simulations different case studies major sources the great importance models. Satellite data from wide ranges sensors provide observations that indicate system state. So both models satellite estimation states, between estimations it is required...

Radiation budget directly affect on the local and global current atmospheric state climate projections through thermal exchange between layers. In this work, we present capability of Generative Adversarial Networks (GANs) algorithm to model spatial distribution for upward radiative fluxes at Earth's surface over South America. Input GANs is total downward (long short wave) while output fluxes. We used ERAS monthly dataset period (2000-2020). The proof its reproduce pattern raditative within...

Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Recurrent Neural Network (RNN), Long short-term memory (LSTM) for Aerosol Optical Depth (AOD) using NASA’s MERRA-2 ReanalysisAuthorsMohammedMagoodaMohamedEltahaniDKarimMoharmiDSee all authors Mohammed MagoodaCairo Universityview email addressThe was not providedcopy addressMohamed EltahaniDJulichiDhttps://orcid.org/0000-0003-2322-8123view addressKarim MoharmiDCorresponding Author•...

Through electrification of transport, battery systems have recently received increasing attention both in the academic literature and practice. Specifically, Battery Management System (BMS), which traditionally has been mainly responsible for basic safety related functionality cell balancing, can today be equipped with sophisticated hardware features facilitating management vast amounts data near real time. This paves way potentially utilizing Big Data analytics a BMS. article describes...

Abstract Change of water storage over Middle East and North Africa (MENA) domain is presented during the period 2003-2017 using satellite data which provided by space mission, Gravity Recovery Climate Experiment (GRACE). Thirty-five basins MENA are selected. Fourteen showed positive trend (increase) in while remaining negative (decrease) storage. Our analysis revealed that most near equator had (increase storage) groundwater changes addition to showing periodic (increasing decreasing)...