We propose a nonlinear ocean forecasting technique based on a combination of genetic algorithms and empirical orthogonal function (EOF) analysis. The method is used to forecast the space-time variability of the sea surface temperature (SST) in the Alboran Sea. The genetic algorithm finds the equations that best describe the behaviour of the different temporal amplitude functions in the EOF deco...

seismic attribute is a quantitative measure of an interested seismic characteristic. there are several seismic attributes. in recent years, time-frequency (tf) attributes have been developed which to reach them, tf analyzing of seismic data is required. a high resolution tf representation (tfr) can yield more accurate tf attributes. there are several tfr methods including short-time fourier tra...

the grace mission has substantiated the low–low satellite-to-satellite tracking (ll-sst) concept. the ll-sst configuration can be combined with the previously realized high–low sst concept in the champ mission to provide a much higher accuracy. the line of sight (los) acceleration difference between the grace satellite pair is the most frequently used observable for mapping the global gravity f...

reduced differental transform method (rdtm), which isone of the useful and effective numerical method, is applied to solve nonlinear time-dependent foam drainage equation (fde) with different initial conditions. we compare our method with the famous adomian decomposition and laplace decomposition methods. the obtained resultsdemonstrated that rdtm is a powerful tool for solving nonlinear par...

[1] The tropical Pacific sea surface temperature (SST) anomalies such as La Nina have been an important predictor for wildfires in the southeastern and southwestern U.S. This study seeks seasonal predictors for wildfires in the northwestern U.S., a region with the most intense wildfires among various continental U.S. regions. Singular value decomposition and regression techniques are applied to...

Sensitivity analysis on Sea Surface Temperature: SST estimation with Thermal Infrared Radiometer: TIR data through simulations is conducted. Also Conjugate Gradient Method: CGM based SST estimation method is proposed. SST estimation error of the proposed CGM based method is compared to the conventional Split Window Method: SWM with a variety of conditions including atmospheric models. The resul...

We examine the extent to which the large-scale features of the sea surface temperature (SST) anomaly eld are resolved by a sparse observational network of coral oxygen isotope ( 18O) time series. Regression of annually-averaged 18O data against gridded estimates of local SST anomaly within the period 1856{1990 con rm the literature regression of 18Oanomaly on SST anomaly for Indo-Paci c corals....

A radial basis function network (RBFN) method is proposed to reconstruct daily Sea surface temperatures (SSTs) with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°E–135°E) are selected when the tropical storm Hagibis arrived in June 2014, and these SST samples are obtained from the OISST products accordi...

predicting the quality of water and air is a particular challenge for forecasting systems that support them. in order to represent the small-scale phenomena, a high-resolution model needs accurate capture of air and sea circulations, significant for forecasting environmental pollution. data assimilation is one of the state of the art methods to be used for this purpose. due to the importance of...

in this paper, we conduct a comparative study between the homotopy perturbation method (hpm) and adomian’s decomposition method (adm) for analytic treatment of nonlinear volterra integral equations, and we show that the hpm with a specific convex homotopy is equivalent to the adm for these type of equations.