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Zeng, Lixin

Publications and source records attributed to Zeng, Lixin.

Space and time aliasing structure is monthly mean polar-orbiting satellite data

Monthly mean wind fields from the European Remote Sensing Satellite (ERS1) scatterometer are presented. A banded structure which resembles the satellite subtrack is clearly and consistently apparent in the isotachs as well as the u and v components of the routinely produced fields. The structure also appears in the means of data from other polar-orbiting satellites and instruments. An experiment is designed to trace the cause of the banded structure. The European Centre for Medium-Range Weather Forecast (ECMWF) gridded surface wind analyses are used as a control set. These analyses are also sampled with the ERS1 temporal-spatial samplig pattern to form a simulated scatterometer wind set. Both sets are used to create monthly averages. The banded structures appear in the monthly mean simulated data but do not appear in the control set. It is concluded that the source of the banded structure lies in the spatial and temporal sampling of the polar-orbiting satellite which results in undersampling. The problem involves multiple timescales and space scales, oversampling and under-sampling in space, aliasing in the time and space domains, and preferentially sampled variability. It is shown that commonly used spatial smoothers (or filters), while producing visually pleasing results, also significantly bias the true mean. A three-dimensional spatial-temporal interpolator is designed and used to determine the mean field. It is found to produce satisfactory monthly means from both simulated and real ERS1 data. The implications to climate studies involving polar-orbiting satellite data are discussed.

Zeng, Lixin↗

Estimating central pressures of oceanic midlatitude cyclones

A method of determining surface pressures in oceanic storm systems using Earth Remote-Sensing Satellite (ERS-1) scatterometer data is employed to determine the lowest pressure in 25 storms. This method uses the surface winds as a lower boundary condition on a planetary boundary layer model to determine gradient winds and, thereby, pressure gradients. An optimization scheme referenced to a pressure outside the storm provides a pressure field and an estimate of the low pressure. The values are compared to European Center for Medium-Range Weather Forecasts (ECMWF) analyses in each case; there is good agreement, with some expected differences.

Brown, R. A.↗