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Keppenne, C. L.

Publications and source records attributed to Keppenne, C. L..

5 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Reconstruction of the 1997/1998 El Nino from TOPEX/POSEIDON and TOGA/TAO Data Using a Massively Parallel Pacific-Ocean Model and Ensemble Kalman Filter

Two massively parallel data assimilation systems in which the model forecast-error covariances are estimated from the distribution of an ensemble of model integrations are applied to the assimilation of 97-98 TOPEX/POSEIDON altimetry and TOGA/TAO temperature data into a Pacific basin version the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. in the first system, ensemble of model runs forced by an ensemble of atmospheric model simulations is used to calculate asymptotic error statistics. The data assimilation then occurs in the reduced phase space spanned by the corresponding leading empirical orthogonal functions. The second system is an ensemble Kalman filter in which new error statistics are computed during each assimilation cycle from the time-dependent ensemble distribution. The data assimilation experiments are conducted on NSIPP's 512-processor CRAY T3E. The two data assimilation systems are validated by withholding part of the data and quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The pros and cons of each system are discussed.

Keppenne, C. L.↗
NASA NTRS1993

High-Frequency Orographically Forced Variability in a Single-Layer Model of the Martian Atmosphere

A shallow water model with realistic topography and idealized zonal wind forcing is used toinvestigate orographically forced modes in the Martian atmosphere. Locally, the model reproduceswell the climatology at the sites of Viking Lander I and II (VL1 and VL2) as inferred from theViking Lander fall and spring observations. Its variability at those sites is dominated by a 3-sol(Martian solar day) oscillation in the region of VL1 and by a 6-sol oscillation in that of VL2. Theseoscillations are forced by the zonal asymmetries of the Martian mountain field. It is suggested thatthey contribute to the observed variability by reinforcing the baroclinic oscillations with nearbyperiods identified in observational studies. The spatial variability associated with the orographicallyforced oscillations is studied by means of extended empirical orthogonal function analysis. The 3-solVL1 oscillation corresponds to a tropical, eastward-traveling, zonal-wavenumber one pattern...

Keppenne, C. L.↗
NASA NTRS1993

Optimal gains for a single polar orbiting satellite

Gains are the spatial weighting of an observation in its neighborhood versus the local values of a model prediction. They are the key to data assimilation, as they are the direct measure of how the data are used to guide the model. As derived in the broad context of data assimilation by Kalman and in the context of meteorology, for example, by Rutherford, the optimal gains are functions of the prediction error covariances between the observation and analysis points. Kalman introduced a very powerful technique that allows one to calculate these optimal gains at the time of each observation. Unfortunately, this technique is both computationally expensive and often numerically unstable for dynamical systems of the magnitude of meteorological models, and thus is unsuited for use in PMIRR data assimilation. However, the optimal gains as calculated by a Kalman filter do reach a steady state for regular observing patterns like that of a satellite. In this steady state, the gains are constants in time, and thus could conceivably be computed off-line. These steady-state Kalman gains (i.e., Wiener gains) would yield optimal performance without the computational burden of true Kalman filtering. We proposed to use this type of constant-in-time Wiener gain for the assimilation of data from PMIRR and Mars Observer.

Banfield, Don↗