A Predictability Study Using Geostationary Satellite Wind Observations during NORPEX

Abstract

High-density geostationary satellite wind observations have become an important new contributor to the observing network over oceanic regions. During the 1998 North Pacific Experiment (NORPEX), assimilation of these data in the Navy Operational Global Atmospheric Prediction System (NOGAPS) provided substantial improvements in 48-h forecast skill over the northeast Pacific and western North America. The current study shows that the large positive impact of the geostationary satellite winds results mainly from the reduction of analysis errors that project onto the leading singular vectors derived from the linearized forecast model. These errors account for only a small fraction of the total analysis error and, during NORPEX, were confined mostly to the middle and lower troposphere with maxima over the central Pacific. These errors do not necessarily coincide with the locations of the largest analysis errors. Experiments in which the satellite information is retained only at prescribed vertical levels in the analysis confirm that the increments in the middle and lower troposphere account for most of the forecast impact. Implications for the design of future observing systems, including strategies for targeted observing, are discussed. It is argued that the results support the key underlying principles of targeted observing, namely, that the early stages of error growth in most numerical weather forecasts are dominated by a relatively small number of unstable structures, and that preferentially reducing analysis errors that project onto these structures can produce significant improvements in forecast skill.