The North Pacific Experiment (NORPEX-98): Targeted observations for improved North American weather forecasts

The objectives and preliminary results of an interagency field program, the North Pacific Experiment (NORPEX), which took place between 14 January and 27 February 1998, are described. NORPEX represents an effort to directly a ddress the issue of observational sparsity over the North Pacific basin, wh ich is a major contributing factor in short-range (less than 4 days) foreca st failures for land-falling Pacific winter-season storms that affect the U nited States, Canada, and Mexico. The special observations collected in NOR PEX include approximately 700 targeted tropospheric soundings of temperatur e, wind, and moisture from Global Positioning System (GPS) dropsondes obtai ned in 38 storm reconnaissance missions using aircraft based primarily in H awaii and Alaska. In addition, wind data were provided every 6 h over the e ntire North Pacific during NORPEX, using advanced and experimental techniqu es to extract information from multispectral geostationary satellite imager y. Preliminary results of NORPEX data impact studies using the U.S. Navy an d National Weather Service forecast models include reductions of approximat ely 10% in mean 2-day forecast error over western North America (30 degrees -60 degrees N, 100 degrees-130 degrees W) from assimilation of targeted dro psonde and satellite wind data (when measured against control forecasts tha t contain no special NORPEX observations). There are local reductions of up to 50% in 2-day forecast error for individual cases, although some forecas ts are degraded by the addition of the special dropsonde or satellite wind data. In most cases, the positive impact of the targeted dropsonde data on short-range forecast skill is reduced when the full set of advanced satelli te wind data is already included in the model analyses. The NORPEX dataset is being used in research to improve objective methods for targeting observ ations, to study the "mix" of in situ and space-based observations, and to understand the structure and dynamics of fast-growing errors that Limit our ability to provide more accurate forecasts of Pacific winter storms.