The Local Analysis and Prediction System (LAPS) analyzes three-dimensional state variables each hour over a user-selected domain. This past spring, it was operated in conjunction with the International H2O Experiment (IHOP) centered near the ARM-CART site in central Kansas and Oklahoma. LAPS analyses routinely initialize local-scale high-resolution models such as NCAR's MM5 (mesoscale model, version 5). The LAPS system has been integrated into the AWIPS system as part of the National Weather Service modernization.

During the IHOP experiment, we focused on aspects of how GOES data impacted analyzed moisture and model QPF forecasting. For this exercise NESDIS prepared special single field of view datasets for total and layer moisture and cloud-top pressure with suitable latency for inclusion into the LAPS 30-min cycle. Both of these datasets are relevant to this study since layer precipitable water data are included in the LAPS variational assimilation scheme, and cloud extent is crucial for proper MM5 hot start. During the latter part of the exercise GOES-11 was activated and provided half-hourly products and imagery over the IHOP domain at greater resolution than GOES 8.

Specific cases and multi-run statistics were used to gauge the impact that the special satellite product data had on the LAPS moisture analysis and model forecasts.