The PACific landfalling JETs (PACJET) field experiment took place in January- February 2001 and was designed to study and monitor the effects of strong subtropical and polar jets coming ashore in the western United States and Canada on weather forecasts. The jet features often contribute to the development of significant storms or heavy precipitation events over the US, but remain poorly observed having their origin over the eastern North Pacific Ocean. Satellite observations remain one of the only means of continuously monitoring these phenomena. In support of PACJET, the GOES rapid scan WINDs EXperiment (GWINDEX) was initiated at the Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin - Madison, providing hourly high-resolution satellite-derived winds over the PACJET domain. This information, along with GOES temperature and moisture profiles, has the potential to greatly improve the analyses and short term forecasts of these jet features if carefully assimilated into high-resolution initial conditions for NWP.

This poster will address the following: 1) using MM5, evaluate the impact on 1-6 day numerical predictions of US weather after assimilating GWINDEX winds along with GOES temperature and moisture profiles, as well as aircraft data collected during PACJET, 2) assess the impact these data have on short-term precipitation forecasts over western North America during the PACJET experiment, and 3) identify optimal methods for assimilating these data into NWP models. The satellite data used for this project will mainly come from the GOES-10 imager and sounder. MODerate resolution Imaging Spectroradiometer (MODIS) data will be used to more intensively measure subsynoptic jet streak features. All satellite data will be assimilated using the National Center for Atmospheric Research (NCAR Four-Dimensional Variational analysis system (4D-VAR).

The conference presentation will consist of an analysis of dual simulations of MM5 over the US for several IOPs during PACJET: one simulation set using satellite and aircraft assimilated data, and the other initialized without these data. A statistical assessment of forecast accuracy improvements, as well as measures of specific data-type impacts on the forecasts will be provided.