Search research articles
Contact Us
Filters
Showing results (1-10 of 11) with videos related to
Page
of 2
Sort By:
Optics Letters
|
September 15, 2015
A simple approach for estimating the refractive index structure parameter (Cn²) profile in the atmosphere
Sukanta Basu
Boundary-Layer Meteorology
|
March 16, 2019
Hybrid Profile-Gradient Approaches for the Estimation of Surface Fluxes
Sukanta Basu
Applied Optics
|
March 17, 2026
Leveraging deep learning-based foundation models for optical turbulence (<i>C</i><i>n</i>2) estimation under data scarcity
Sukanta Basu
Optics Letters
|
May 14, 2016
Using an artificial neural network approach to estimate surface-layer optical turbulence at Mauna Loa, Hawaii
Yao Wang, Sukanta Basu
Optics Letters
|
September 9, 2016
Utilizing the Kantorovich metric for the validation of optical turbulence predictions
Yao Wang, Sukanta Basu
Optics Express
|
May 4, 2016
Extending a surface-layer Cn2 model for strongly stratified conditions utilizing a numerically generated turbulence dataset
Ping He, Sukanta Basu
Physical Review. E
|
June 17, 2017
Estimating higher-order structure functions from geophysical turbulence time series: Confronting the curse of the limited sample size
Adam W DeMarco, Sukanta Basu
Optics Letters
|
September 1, 2023
Π-ML: a dimensional analysis-based machine learning parameterization of optical turbulence in the atmospheric surface layer
Maximilian Pierzyna, Rudolf Saathof, Sukanta Basu
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
September 28, 2004
Synthetic turbulence, fractal interpolation, and large-eddy simulation
Sukanta Basu, Efi Foufoula-Georgiou, Fernando Porté-Agel
Applied Optics
|
June 10, 2024
Intercomparison of flux-, gradient-, and variance-based optical turbulence (<i>C</i> <i>n</i>2) parameterizations
Maximilian Pierzyna, Oscar Hartogensis, Sukanta Basu, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 11) with videos related to
Sort By:
Page
of 2
Optics Letters
|
September 15, 2015
A simple approach for estimating the refractive index structure parameter (Cn²) profile in the atmosphere
Sukanta Basu
Boundary-Layer Meteorology
|
March 16, 2019
Hybrid Profile-Gradient Approaches for the Estimation of Surface Fluxes
Sukanta Basu
Applied Optics
|
March 17, 2026
Leveraging deep learning-based foundation models for optical turbulence (<i>C</i><i>n</i>2) estimation under data scarcity
Sukanta Basu
Optics Letters
|
May 14, 2016
Using an artificial neural network approach to estimate surface-layer optical turbulence at Mauna Loa, Hawaii
Yao Wang, Sukanta Basu
Optics Letters
|
September 9, 2016
Utilizing the Kantorovich metric for the validation of optical turbulence predictions
Yao Wang, Sukanta Basu
Optics Express
|
May 4, 2016
Extending a surface-layer Cn2 model for strongly stratified conditions utilizing a numerically generated turbulence dataset
Ping He, Sukanta Basu
Physical Review. E
|
June 17, 2017
Estimating higher-order structure functions from geophysical turbulence time series: Confronting the curse of the limited sample size
Adam W DeMarco, Sukanta Basu
Optics Letters
|
September 1, 2023
Π-ML: a dimensional analysis-based machine learning parameterization of optical turbulence in the atmospheric surface layer
Maximilian Pierzyna, Rudolf Saathof, Sukanta Basu
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
September 28, 2004
Synthetic turbulence, fractal interpolation, and large-eddy simulation
Sukanta Basu, Efi Foufoula-Georgiou, Fernando Porté-Agel
Applied Optics
|
June 10, 2024
Intercomparison of flux-, gradient-, and variance-based optical turbulence (<i>C</i> <i>n</i>2) parameterizations
Maximilian Pierzyna, Oscar Hartogensis, Sukanta Basu, et al.
Page
of 2