Sergey Frolov

Sergey Frolov
University of Colorado Boulder | CUB · Cooperative Institute for Research in Environmental Sciences (CIRES)

Ph.D.

About

47
Publications
8,160
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747
Citations
Introduction
Current research is focused on developing data assimilation algorithms for initialization of coupled forecast models. Coupled processes of interest include ocean-atmosphere, ocean-atmosphere-wave, and ocean optics-ocean biology. Past research included estuarine and coastal oceanography, statistical learning from large environmental simulations, optimal design of ocean observatories, and ocean ecosystem process studies.
Additional affiliations

Publications

Publications (47)
Article
Full-text available
Mesoscale eddies dominate energetics of the ocean, modify mass, heat and freshwater transport and primary production in the upper ocean. However, the forecast skill horizon for ocean mesoscales in current operational models is shorter than 10 days: eddy-resolving ocean models, with horizontal resolution finer than 10 km in mid-latitudes, represent...
Article
Full-text available
This paper describes the new global Navy Earth System Prediction Capability (Navy‐ESPC) coupled atmosphere‐ocean‐sea ice prediction system developed at the Naval Research Laboratory (NRL) for operational forecasting for timescales of days to the subseasonal. Two configurations of the system are validated: (1) a low‐resolution 16‐member ensemble sys...
Article
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Patterns of correlations between the ocean and the atmosphere are examined using a high-resolution (1/12° ocean and ice, and 1/3° atmosphere) ensemble of data assimilative, coupled, global, ocean-atmosphere forecasts. This provides a unique perspective into atmosphere-ocean interactions constrained by assimilated observations, allowing for the cont...
Article
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This paper illustrates that analysis corrections, when applied as a model tendency term, can be used to improve non-linear model forecasts and is consistent with the hypothesis that they represent an additive 6-hour accumulation of model error. Comparison of mean analysis corrections with observational estimates of bias further illustrates the fide...
Article
Full-text available
An ensemble-based linearized forecast model has been developed for data assimilation applications for numerical weather prediction. Previous studies applied this local ensemble tangent linear model (LETLM) to various models, from simple one-dimensional models to a low-resolution (~2.5°) version of the Navy Global Environmental Model (NAVGEM) atmosp...
Technical Report
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This report is intended as part of the important dialogue between the ocean colour and the biogeochemical/ecosystem/climate modelling communities. Numerical modellers are frequent users of ocean colour products, but many modellers remain unsure of the best way to use these products, and are often unaware of the uncertainties associated with them. O...
Article
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Coupled data assimilation (DA) provides a consistent framework for assimilating satellite observations that are sensitive to several components of the Earth system. In this paper, we focus on low-peaking infrared satellite channels that are sensitive to the lower atmosphere and Earth Surface Temperature (EST) over both ocean and land. Our atmospher...
Article
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Current parallelization trends in computer technology facilitates development of the algorithms that retrieve linear approximations of the model operators and their adjoints from ensembles of model simulations. In this study we address the problem of obtaining exact linearizations in the presence of semi‐implicit numerics of the parent model under...
Article
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Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners of DA are encouraged...
Article
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Ocean data assimilation is increasingly recognized as crucial for the accuracy of real-time ocean prediction systems and historical re-analyses. The current status of ocean data assimilation in support of the operational demands of analysis, forecasting and reanalysis is reviewed, focusing on methods currently adopted in operational and real-time p...
Article
The European Centre for Medium‐Range Weather Forecasts has recently developed an implicit coupling approach in the CERA system, where atmospheric 4D‐Var and ocean 3D‐Var are synchronized using multiple outer iterations in the incremental variational formulation. Since this original work on the outer loop coupling, it has been unclear just how close...
Article
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The local ensemble tangent linear model (LETLM) provides an alternative method for creating the tangent linear model (TLM) and adjoint of a nonlinear model that promises to be easier to maintain and more computationally scalable than earlier methods. In this paper, we compare the ability of the LETLM to predict the difference between two nonlinear...
Article
An ensemble based approach to specify observational error covariance in the data assimilation of satellite bio-optical properties is proposed. The observational error covariance is derived from statistical properties of the generated ensemble of satellite MODIS-Aqua chlorophyll (Chl) images. The proposed observational error covariance is used in th...
Poster
Full-text available
An extended range ensemble forecast system is being developed in the US Navy Earth System Prediction Capability (ESPC). A global ensemble generation capability to support the coupled ESPC ensemble forecast has being developed, and initial assessments are underway. The air/ocean/ice ensemble is generated with parallel perturbed-observation analyses....
Article
A leading Data Assimilation (DA) technique in meteorology is 4DVAR which relies on the Tangent Linear Model (TLM) of the non-linear model and its adjoint. The difficulty of building and maintaining traditional TLMs and adjoints of coupled ocean-wave-atmosphere-etc models is daunting. On the other hand, coupled model ensemble forecasts are readily a...
Article
Full-text available
An ensemble-based tangent linear model (TLM) is described and tested in data assimilation experiments using a global shallow-water model (SWM). A hybrid variational data assimilation system was developed with a 4D variational (4DVAR) solver that could be run either with a conventional TLM or a local ensemble TLM (LETLM) that propagates analysis cor...
Article
Since January 2009, two long-range high-frequency (HF) radar systems have been collecting hourly high-spatial-resolution surface current data in the southeastern corner of the Bay of Biscay. The temporal resolution of the HF radar surface currents permits simulating drifter trajectories with the same time step as that of real drifters deployed in t...
Article
Full-text available
Hybrid error covariance models that blend climatological estimates of forecast error covariances with ensemble-based, flow-dependent forecast error covariances have led to significant reductions in forecast error when employed in 4DVAR data assimilation schemes. Tangent linear models (TLMs) designed to predict the differences between perturbed and...
Article
Full-text available
In a strongly coupled data assimilation (DA), one specifies a cross-fluid covariance that allows measurements from a coupled fluid (e.g. atmosphere) to directly impact analysis increments in a target fluid (e.g. ocean). The exhaustive solution to this coupled DA problem calls for a covariance where all available measurements can influence all grid...
Article
Full-text available
Regular grid (“lawnmower”) survey is a classical strategy for synoptic sampling of the ocean. Is it possible to achieve a more effective use of available resources if one takes into account a-priori knowledge about variability in magnitudes of uncertainty and decorrelation scales? In this article, we develop and compare the performance of several p...
Article
Full-text available
A key challenge for ecosystem science in the 21st century is to characterize emerging trends in ecosystem productivity due to climate change and to better predict cycles in ecosystem variability. A first step toward this goal is to be able to characterize phytoplankton variability across a wide range of spatial and temporal scales. In this paper, 1...
Conference Paper
Data assimilation experiments with the coupled physical, bio-optical model of Monterey Bay are presented. The approach is based on the representation of the error covariances in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from the model run. Estimated coupled bio-optical, physical error c...
Conference Paper
Two Seasonde type high frequency (HF) radars have measured the surface currents in the southeastern part of the Bay of Biscay off the coast of Spain from 2009 to present. The radars are located at Cape Matxitxako and Cape Higer and operate at 4.86 mHz with a 40 kHz bandwidth, and provide hourly current measurements with a 5 km spatial resolution. T...
Article
Data assimilation experiments with the coupled physical, bio-optical model of Monterey Bay are presented. The objective of this study is to investigate whether the assimilation of satellite-derived bio-optical properties can improve the model predictions (phytoplankton population, chlorophyll) in a coastal ocean on time scales of 1–5 days. The Mont...
Conference Paper
Full-text available
An apparent link between upwelling‐related physical signatures, macronutrients, and harmful algal blooms (HABs) in the various “hotspots” throughout California has motivated attempts to forecast HABs as a function of select environmental variables. Empirical statistical models have been developed and there have been attempts to link these empirical...
Article
Full-text available
Accurate short-term prediction of surface currents can improve the efficiency of search-and-rescue operations, oil-spill response, and marine operations. We developed a linear statistical model for predicting surface currents (up to 48 hours in the future) based on a short time-history of past HF-radar observations (past 48 hours) and an optional f...
Article
Full-text available
1] Predicting water column integrated phytoplankton biomass from near-surface measurements has been an important effort in marine ecological research, particularly since the advent of satellite remote sensing of ocean color. Quantitative relationships between chlorophyll-a concentrations (Chl-a) at the surface and its depth-integrated magnitude hav...
Article
Spatial and temporal decorrelation scales in phytoplankton bloom magnitudes are reviewed with the goal of informing the design of efficient and informative observing networks for monitoring of potentially harmful algal blooms (HABs) along the U.S. West Coast. Our analysis of historic MODIS Fluorescent Line Height data shows that, unlike several pre...
Conference Paper
Full-text available
Wave glider (WG) is a novel autonomous surface vehicle that uses energy from surface waves for propulsion and an array of solar panels to power the sensor and hotel payloads. In this paper, we test the applicability of the WG platform for persistent monitoring of algal biomass distribution in Monterey Bay, CA. In October of 2010, the WG successfull...
Article
The ability to characterize the response of small marine organisms to each other, and to their environment, is a demanding observational challenge. Small organisms live in a water reference frame, while existing cable or mooring-based observatories operate in an Earth reference frame. Thus repeated observations from a fixed system observe different...
Conference Paper
Full-text available
This paper presents an oceanographic toolchain that can be used to generate multi-vehicle robotic surveys for large-scale dynamic features in the coastal ocean. Our science application targets Harmful Algal Blooms (HABs) which have significant societal impact to coastal communities yet are poorly understood ecologically. Bloom patches can be large...
Conference Paper
Full-text available
Current feature tracking frameworks in sensor networks exploit advantages of either mobility, where mobile sensors can provide micro scale information of a small sensing area or numerical models that can provide macro scale information about the environment but not both. With the continual development of sensor networks, mobility becomes an importa...
Article
Full-text available
As integral capability within an end-to-end observatory for the Columbia River estuary-plume-shelf system, we routinely create simulation databases of 3-D baroclinic circulation with unstructured grid models SELFE (Semi-implicit Eulerian-Lagrangian Finite Element) and ELCIRC (Eulerian-Lagrangian Circulation). Here, 1999–2006 SELFE simulations are u...
Article
A fast and adjoint-free nonlinear data assimilation (DA) system was developed to simulate 3D baroclinic circulation in estuaries, leveraging two recently developed technologies: (1) a nonlinear model surrogate that executes forward simulation three orders of magnitude faster than a forward numerical circulation code and (2) a nonlinear extension to...
Article
A data assimilation method was used to estimate the variability of three ecologically significant features of the Columbia River estuary and plume: the size of the plume, the orientation of the plume, and the length of the salinity intrusion in the estuary. Our data assimilation method was based on a reduced dimension Kalman filter that enables fas...
Article
Proliferation of coastal observatories necessitates an objective approach to managing of observational assets. In this article, we used our experience in the coastal observatory for the Columbia River estuary and plume to identify and address common problems in managing of fixed observational assets, such as salinity, temperature, and water level s...
Conference Paper
Full-text available
The Columbia River (CoRie) Observation Network includes an extensive array of fixed stations monitoring the Columbia River estuary and nearby coastal ocean. At each station, variable combinations of in-situ sensors measure one or more physical properties of water or atmosphere. Using a multi-scale data assimilation model, the CORIE modeling system...
Article
Recent studies have shown that place cells in the hippocampal CA1 region fire in a sequence sensitive manner. In this study we tested if hippocampal CA3 and CA1 regions can give rise to the sequence sensitivity. We used a two-layer CA3-CA1 hippocampal ...
Conference Paper
Full-text available
CORIE is a pilot environmental observation and forecasting system (EOFS) for the Columbia River. The goal of CORIE is to characterize and predict complex circulation and mixing processes in a system encompassing the lower river, the estuary, and the near-ocean using a multi-scale data assimilation model. The challenge for scientists is to maintain...
Article
We present neural network surrogates that provide extremely fast and accurate emulation of a large-scale circulation model for the coupled Columbia River, its estuary and near ocean regions. The circulation model has O(10(7)) degrees of freedom, is highly nonlinear and is driven by ocean, atmospheric and river influences at its boundaries. The surr...
Conference Paper
Full-text available
This is a presentation from OSU workshop on data assimilation. This presentation was indexed automatically by the researchgate servers
Article
A very fast, model independent, fully non-linear extension to the reduced space Kalman filter has been recently proposed and demonstrated for the assimilation of the non-linear circulation in both a synthetic estuary and in the river-dominated Columbia River estuary. Here, we extend the application to another complex problem the simulation of a cou...
Article
Full-text available
LONG-TERM GOALS Improve synoptic observations and enhance ocean prediction through development of new capabilities for persistent underwater ocean surveillance. OBJECTIVES Multi-platform ocean observing systems are typically centrally controlled from shore limiting their ability to adapt to new observations which would inform more effective samplin...
Article
Full-text available
In order to address the highly nonlinear dynamics in estuary flow, we propose a novel data assimilation system based on components designed to accurately reflect nonlinear dy- namics. The core of the system is a sigma-point Kalman filter c oupled to a fast, neural network emulator for the flow dynamics. In order to be computa tionally feasible, the...
Article
Full-text available
Ph.D. Environmental Science and Engineering There is a building consensus among scientists, educators, managers, and politicians that integrated ocean observatories are a critical backbone to future scientific exploration, workforce training, and science-based management of coastal resources in the U.S. An integral part of the future infrastructure...

Questions

Questions (2)
Question
I am writing a paper where I would like to report some execution times for a multithreaded matlab code. Do you have any suggestions on how to measure cpu cycles in matlab? Tic and Toc measure wall-clock time. 
Question
GPU-like accelerators is a disruptive technology in parallel computing. Do you think that it is possible to use GPU accelerators to speed up your favorite ensemble algorithm? What actual speed-ups do you think will be realistic? For computer scientists, think of a matrix vector multiplication where the ensemble matrix is 10^9 by 100. We also often have algorithms where a large problem is split into small problems of size < 1000x1000.

Projects

Projects (2)
Project
An extended range air-sea-ice-wave coupled ensemble forecast system is being developed in the US Navy Earth System Prediction Capability (ESPC). A global ensemble generation capability to support the coupled ESPC ensemble forecast has being developed using parallel perturbed-observation analyses.