One of the challenges of the modernized weather forecast office is to integrate external data from outside sources. The Advanced Weather Information Processing System (AWIPS) is a tool by which this can be done. The Local Data Acquisition and Display (LDAD) unit of the AWIPS system enables forecasters to acquire these external data and display it on system consoles. LDAD simplifies decoding and plotting of this data through user defined preprocessors which re-format the data into comma separated format. Alternatively the data can be sent to LDAD already in a comma delimitered format without the need for preprocessors. A set of configuration files is also needed for each data set so the observations can be plotted on screen. When this processed data is stored into a specified incoming directory, the LDAD system decodes and produces netCDF files that are used for plotting.

This paper will illustrate how both strategies are used at WFO Binghamton to ingest and plot external data, namely surface observations, from a variety of sources. Typically these external data are obtained either via ftp, or by utilizing PC's running ProComm Plus software scripts that periodically dial and download the raw data. The data are then copied over to an HP Unix based computer via a mounted directory using SAMBA software (which enables file sharing between PC's and Unix/Linux). From there a Perl script is run on LDAD via a cron job that FTP's the data into LDAD, decodes it, and drops it into the incoming directory as a comma separated file. The data is then processed into netCDF format which can be plotted and displayed. Examples of data sources currently ingested at WFO Binghamton will be shown, including Automated Weather Observing Stations (AWOS) surface observations, Automated Weather Source (AWS) schoolnet surface observations, and New York State Department of Transportation (DOT) automated observations. Beginning in summer 2001 the New York State DOT will be expanding the automated surface observation stations to 600 sites across New York. In future AWIPS software builds, these data will be automatically ingested by the Local Analysis and Prediction System (LAPS), which produces hourly 10 km analyses of numerous observed and derived fields across the forecast area. The importance of ingesting these external data sources into a high resolution analysis system in a region of variable terrain will be illustrated