Construction of Marine Surface Pressure Fields from Scatterometer Winds Alone

Abstract

A series of 6-h, synoptic, gridded, global surface wind fields with a resolution of 100 km was generated using the dataset of dealiased Seasat satellite scatterometer (SASS) winds produced as described by Peteherych et al. This paper is an account of the construction of surface pressure fields from these SASS synoptic wind fields only, as carried out by different methods, and the comparison of these pressure fields with National Centers for Environmental Prediction (NCEP) analyses, with the pressure fields of the European Centre for Medium-Range Weather Forecasts (ECMWF), and with the special analyses of the Gulf of Alaska Experiment. One of the methods we use to derive the pressure fields utilizes a two-layer planetary boundary layer (PBL) model iterative scheme that relates the geostrophic wind vector to the surface wind vector, surface roughness, humidity, diabatic and baroclinic effects, and secondary flow. A second method involves the assumption of zero two-dimensional divergence, leading to a Poisson equation (the “balance equation”) in pressure, with the wind field serving as a forcing function. The pressure fields computed from the SASS winds using a two-layer PBL model closely approximate the NCEP and ECMWF fields. In some cases, the PBL-model-derived pressure fields can detect mesoscale features not resolved in either the NCEP or ECMWF analyses. Balanced pressure fields are much smoother and less well resolved than the PBL-model-derived or NCEP fields. Systematic differences between balanced pressure fields and the PBL-model-derived fields are attributed to the neglect of horizontal divergence in the balance equation. The effect of stratification is found to produce a larger impact than secondary flow or thermal wind effects on the derived pressure fields. Inclusion of secondary flow tends to weaken both low and high pressure centers, whereas inclusion of stratification intensifies low centers and weakens high centers.