S. Frolov

发表

Author's Personal Copy Dynamics of Atmospheres and Oceans Fast Data Assimilation Using a Nonlinear Kalman Filter and a Model Surrogate: an Application to the Columbia River Estuary

António M. Baptista, Rudolph van der Merwe, Todd K. Leen, 2022 .

First Application of the Local Ensemble Tangent Linear Model (LETLM) to a Realistic Model of the Global Atmosphere

C. Bishop, K. Hoppel, R. Langland, 2018, Monthly Weather Review.

Hybrid 4DVAR with a Local Ensemble Tangent Linear Model: Application to the Shallow-Water Model

C. Bishop, K. Hoppel, G. Nedoluha, 2017 .

Sequential Data Assimilation with Sigma-point Kalman Filter on Low-dimensional Manifold June 23 , 2007 DRAFT-DO NOT CIRCULATE

Zhengdong Lu, Rudolph van der Merwe, Todd K. Leen, 2007 .

Optimizing fixed observational assets in a coastal observatory

António M. Baptista, Sergey Frolov, Michael Wilkin, 2008 .

Postmigration image optimization: A Gulf of Mexico case study

N. Chemingui, S. Frolov, Samuel Brown, 2016 .

Enabling technologies for fast, nonlinear data assimilation in a coastal margin observatory

S. Frolov, 2007 .

Assimilation of Low-Peaking Satellite Observations Using the Coupled Interface Framework

C. Bishop, M. Flatau, J. McLay, 2020 .

The ART-XC telescope on board the SRG observatory

Rfnc-Vniief, Universities Space Research Association, H Germany, 2021, Astronomy & Astrophysics.

Erratum to "Fast neural network surrogates for very high dimensional physics-based models in computational oceanography" [Neural Netw. 20(4) (2007) 462-478]

Zhengdong Lu, António M. Baptista, Rudolph van der Merwe, 2007, Neural Networks.

Bio‐Optical Data Assimilation With Observational Error Covariance Derived From an Ensemble of Satellite Images

I. Shulman, B. Penta, R. Gould, 2018 .

Correcting Systematic and State‐Dependent Errors in the NOAA FV3‐GFS Using Neural Networks

J. Whitaker, R. Pincus, S. Penny, 2022, Journal of Advances in Modeling Earth Systems.

Synthesis of Ocean Observations Using Data Assimilation for Operational, Real-Time and Reanalysis Systems: A More Complete Picture of the State of the Ocean

Peter R. Oke, Paolo Oddo, Anna Teruzzi, 2019, Front. Mar. Sci..

Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction

Stephen G. Penny, Yosuke Fujii, Ibrahim Hoteit, 2019, Front. Mar. Sci..

Fast neural network surrogates for very high dimensional physics-based models in computational oceanography

Zhengdong Lu, António M. Baptista, Rudolph van der Merwe, 2007, Neural Networks.

Leveraging deep learning for seismic image denoising

N. Chemingui, S. Frolov, E. Klochikhina, 2020 .

Complementary use of Wave Glider and satellite measurements: Description of spatial decorrelation scales in Chl-a fluorescence across the Pacific basin

Sergey Frolov, Christopher A. Edwards, Nicole L. Goebel, 2014 .

Assimilation of bio-optical properties into coupled physical, bio-optical coastal model

Peter Sakalaukus, Sherwin Ladner, Sergey Frolov, 2013, Defense, Security, and Sensing.

Impact of bio-optical data assimilation on short-term coupled physical, bio-optical model predictions

Richard W. Gould, Peter Sakalaukus, Sherwin Ladner, 2013 .

Implicit and explicit cross‐correlations in coupled data assimilation

M. Bonavita, P. Laloyaux, B. Ménétrier, 2018, Quarterly Journal of the Royal Meteorological Society.

The Navy's Earth System Prediction Capability: A New Global Coupled Atmosphere‐Ocean‐Sea Ice Prediction System Designed for Daily to Subseasonal Forecasting

C. Bishop, N. Barton, A. Wallcraft, 2020, Earth and Space Science.

Challenges of Increased Resolution for the Local Ensemble Tangent Linear Model

C. Bishop, K. Hoppel, R. Langland, 2020, Monthly Weather Review.

The Local Ensemble Tangent Linear Model: an enabler for coupled model 4D‐Var

Craig H. Bishop, Sergey Frolov, Douglas R. Allen, 2017 .

The Local Ensemble Tangent Linear Model: an enabler for coupled model 4DVAR: Local Ensemble Tangent Linear Model

C. Bishop, D. Allen, S. Frolov, 2017 .

Ensemble forecasting greatly expands the prediction horizon for ocean mesoscale variability

N. Barton, A. Wallcraft, O. Smedstad, 2021, Communications Earth & Environment.

Including parameterized error covariance in local ensemble solvers: Experiments in a 1D model with balance constraints

J. Whitaker, C. Draper, S. Frolov, 2022, Quarterly Journal of the Royal Meteorological Society.

Using Analysis Corrections to Address Model Error in Atmospheric Forecasts

Craig H. Bishop, Neil P Barton, Carolyn A. Reynolds, 2020 .

Estimation of ecologically significant circulation features of the Columbia River estuary and plume using a reduced-dimension Kalman filter.

Yinglong J. Zhang, A. Baptista, C. Seaton, 2009 .

Near Optimal Sensor Selection in the COlumbia RIvEr (CORIE) Observation Network for Data Assimilation Using Genetic Algorithms

Wu-chi Feng, António M. Baptista, Nirupama Bulusu, 2007, DCOSS.

2007 Special Issue: Fast neural network surrogates for very high dimensional physics-based models in computational oceanography

Rudolph van der Merwe, T. Leen, Zhengdong Lu, 2007 .

Seismic Reflection Tomography with 3D RTM Angle Gathers

N. Chemingui, D. Whitmore, S. Frolov, 2013 .