Sergey Frolov

Facilitating Strongly Coupled Ocean–Atmosphere Data Assimilation with an Interface Solver

AbstractIn a strongly coupled data assimilation (DA), a cross-fluid covariance is specified 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 points in all fluids. Solution of such a large algebraic problem is computationally expensive, often calls for a substantial rewrite of existing fluid-specific DA systems, and, as shown in this paper, can be avoided.The proposed interface solver assumes that covariances between coupled measurements and target fluid are often close to null (e.g., between stratospheric observations and the deep ocean within a 6-h forecast cycle). In the interface solver, two separate DA solvers are run in parallel: one that produces an analysis solution in the atmosphere, and one in the ocean. Each system uses a coupled observation vector where in addition to resident mea...

Localized Ensemble-Based Tangent Linear Models and Their Use in Propagating Hybrid Error Covariance Models

AbstractHybrid 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 unperturbed simulations of the weather forecast are a key component of such 4DVAR schemes. However, many forecasting centers have found that TLMs and their adjoints do not scale well computationally and are difficult to create and maintain—particularly for coupled ocean–wave–ice–atmosphere models. In this paper, the authors create ensemble-based TLMs (ETLMs) and test their ability to propagate both climatological and flow-dependent parts of hybrid error covariance models. These tests demonstrate that rank deficiency limits the utility of unlocalized ETLMs. High-rank, time-evolving, flow-adaptive localization functions are constructed and tested using rec...

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

AbstractThe 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 mai...

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

AbstractAn 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 corrections using only ensemble statistics. An offline ensemble Kalman filter (EnKF) is used to generate and maintain the ensemble. The LETLM uses data within a local influence volume, similar to the local ensemble transform Kalman filter, to linearly propagate the state variables at the central grid point. After tuning the LETLM with offline 6-h forecasts of analysis corrections, cycling experiments were performed that assimilated randomly located SWM height observations, based on a truth run with forced bottom topography. The performance using the LETLM is similar to that of the conventional TLM, suggesting that a well-constructed LETLM could free 4D vari...

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

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 covariances are used in the Kalman gain update providing updates of coupled bio-optical properties in accord with the model dynamics and available observations. With the assimilation of satellite-derived bio-optical properties (chlorophyll-a and absorption due to phytoplankton), the model was able to reproduce intensity and tendencies in subsurface chlorophyll distributions observed at water samples locations in the Monterey Bay, CA. Data assimilation also improved agreement between the observed and model-predicted ratios between diatoms and small phytoplankton populations.

300W CW Diode Pumped Nd:YAG Laser With Improved Divergence of Output Beam

We describe our investigations of a CW diode pumped solid state laser based on two Nd:YAG active elements provided with original unstable resonator. Two diffraction limited output beam divergence has been achieved. The laser radiation power of the resonator proposed has been obtained of 40% below but with the 30 times greater on-axis intensity as compared to the ordinary used resonator in a commercial laser of a similar type.