The aim of this study is to joint assimilate the ozone product from satellite Atmospheric Infrared Sounder (AIRS) and bogus data using four-dimensional ensemble-variational (4DEnVar) method, demonstrate potential benefits initialization technique in improving hurricane forecasting through a case study. Firstly, quality control scheme employed enhance AIRS; sea level pressure (SLP) at center con...

We combine a machine learning method and ensemble climate predictions to investigate windows of opportunity for seasonal predictability European summer associated with the North Atlantic jet stream. particularly focus on impact spring sea surface temperatures (SST) four dominant atmospheric teleconnections stream: Oscillation (NAO) in positive negative phases, Ridge (At. Ridge), Low Low). go be...

1 Throughout much of the latter half of the 20th century, the dominant mode of North2 ern Hemisphere (NH) extratropical wintertime circulation variability−the Arctic Oscillation 3 (AO)−exhibited a positive trend, with decreasing high-latitude sea-level pressure (SLP) and 4 increasing mid-latitude SLP. General circulation models (GCMs) show this trend is related 5 to several factors, including N...

Numerical model scenarios of future climate depict a global increase in temperatures and changing precipitation patterns, primarily driven by increasing greenhouse gas (GHG) concentrations. Aerosol particles also play an important role by altering the Earth’s radiation budget and consequently surface temperature. Here, we use the general circulation aerosol model ECHAM5-HAM, coupled to a mixed ...

dust storms are destructive climate phenomenon which damage farm, installations,roads,traffic and etc indemnifiable. this phenomena at dry and pertaining regions of the country as environmental perils, is effected by particular atmospheric condition.if the origin and extention of this phenomenon be recognized the damages can be decreased or counteracted.the studied about dust storm show thirtee...

This paper proposes a memory-efficient deep neural network (DNN) framework-based symbol level precoding (SLP). We focus on DNN with realistic finite precision weights and adopt an unsupervised learning (DL) based SLP model (SLP-DNet). apply stochastic quantization (SQ) technique to obtain its corresponding quantized version called SLP-SQDNet. The proposed scheme offers scalable performance vs m...

This paper introduces an approach to level-set topology optimization that can handle multiple constraints and simultaneously optimize non-level-set design variables. The key features of the new method are discretized boundary integrals to estimate function changes and the formulation of an optimization sub-problem to attain the velocity function. The sub-problem is solved using sequential linea...

This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (MSLP) over west Africa based on analysis Global Precipitation Climatology Project (GPCP) National Center for Environmental Prediction/National Atmospheric Research (NCEP/NCAR) Reanalysis respectively. An interconnection is found in this region, between anomaly (over Azores St. Helena High) monthly mean pre...