1. LAPS blends a wide variety of national data sets and local data sets. For example, it can combine both national surface data and local mesoscale networks. It utilizes numerical weather prediction products from the national database as backgrounds for both analysis and prediction. LAPS analyses are used to initialize mesoscale forecast models. It creates forecasts at any horizontal or vertical resolution you may need, with output at the times and frequencies you require with many mesoscale models (MM5, RAMS, and the new WRF). It runs on inexpensive hardware: desk top to laptop, using the UNIX operating system. Local Analysis and Prediction System (LAPS) Technology Transfer LAPS is used for data assimilation, nowcasting, as well as model initialization and post-processing. As it evolves it continues to provide customized environmental applications to a wide variety of users in various agencies in government, the private sector, academia, and around the world. Introduction The Local Analysis and Prediction System (LAPS), under development at the NOAA Earth System Research Laboratory (ESRL), is finding its way to a broad user community. LAPS is a “go-anywhere” meteorological analysis and prediction system designed to utilize all local and national sources of data and create 3-dimensional grids of weather information. These fields are fed into a broad range of high-resolution weather models to develop short- range forecasts. This system can be set up to run in your operational environment and customized to produce the weather products you want, when you want them. Three LAPS implementations are illustrated in the panels to the right. Environmental Support for Space Launch Operations In collaboration with Lockheed-Martin Mission Systems and the US Air Force, ESRL is creating a complete analysis, forecasting and display system using LAPS coupled with the MM5 mesoscale forecast model (developed at Penn State University and National Center for Atmospheric Research) and the Advanced Weather Interactive Processing System (AWIPS). This system is designed to ingest unique, high resolution data sets supported on site, then create high-resolution analyses and forecasts to meet the challenge of supporting space launch operations. Fire Weather Analysis and Prediction National and regional wildfire managers and operations personnel require accurate and timely environmental information useful for prediction conditions conducive for wildfire formation and behavior. In collaboration with the USDA Forest Service Rocky Mountain Research Station, we are providing prototype real-time fire weather products as one of the five regional centers of the Fire Consortia for Advanced Modeling of Meteorology and Smoke (FCAMMS). Publications Albers, S, J. McGinley, D. Birkenheuer, and J. Smart 1996: The Local Analysis and Prediction System (LAPS), Analyses of clouds, precipitation, and temperature. Weather and Forecasting, 11, 273-287. Shaw, B.L., S.A. Albers, J.A. McGinley, L.S. Wharton, T.L. Wilfong, C.L. Crosiar, and D.E. Harms, 2002: A completely integrated, cost-effective local data assimilation and forecasting system to support space launch range operations. Interactive Symposium on the Advanced Weather Interactive Processing System (AWIPS), Orlando, FL, Amer. Meteor. Soc., 15-19. Szoke, E.J., and B.L. Shaw, 2001: An examination of the operational predictability of mesoscale terrain-induced features in eastern Colorado from several models. Ninth Conf. Of Mesoscale Processes, Fort Lauderdale, FL, Amer. Meteor. Soc., 380-383. Szoke, E.J., B. Shaw, M. Kay, J. Brown, P. Janish and R. Schneider, 2002: A preliminary examination of several mesoscale models for convective forecasting during IHOP. 19 th Conf. On Weather Analysis and Forecasting, San Antonio, TX, Amer. Meteor. Soc., J37-J40. Convective Available Potential Energy (CAPE) for 10km domain centered on Cape Canaveral. Steve Albers 1,2 Ed Szoke 1,2 LAPS Attributes: The local data sets being brought into LAPS include ASOS, wideband WSR-88D reflectivity and radial velocity, meteorological towers, RTAMPS balloons, SODAR, as well as wind and RASS profilers. These unique data sets, combined with national data sets such as GOES imagery, narrowband WSR-88D, METARs, and ACARS make this an extremely robust data assimilation system. Collaborators  NOAA / Earth System Research Laboratory  USDA Forest Service  Rocky Mountain Research Station  Fire and Environmental Research Applications Team  Northwest Regional Modeling Consortium BlueSky smoke dispersion model prediction using FSL-generated LAPS-initialized MM5 forecast for the SW US domain. Triple nested MM5 domains (10, 3.3, and 1.1 km) are able to resolve terrain-driven flow not represented in national-scale models (NCEP Eta streamlines in tan are shown for comparison). The initial system has been installed at both ranges (Cape Canaveral AFS, FL and Vandenberg AFB, CA). It is the first operational modeling system in the U.S. government running on an affordable Linux cluster and fully integrated with the AWIPS system...a possible prototype for the future Weather Forecast Office! Reliable, inexpensive, high-performance computing solutions for local forecast offices using Linux clusters AWIPS NOAA & CIRA personnel at ESRL have been involved in the operational implementation of LAPS analyses within the Advanced Weather Interactive Processing System (AWIPS). This is the primary weather information display system used in NWS Weather Forecast Offices around the nation. High-resolution (4km grid spacing) forecast of Ventilation Index and PBL winds. Real-Time WWW Products Available  Ventilation Index and PBL Winds  PBL Height  Haines Index (Low, Mid, High)‏  Fosberg Fire Weather Index  LAPS Fire Weather Index  Tabular Text User-Defined Point Forecasts  Standard Surface and Upper-Air Products  http://www.fs.fed.us/rmc During the 2003 fire season, researchers at the Northwest Regional Model Consortium collaborated to couple output from our numerical forecasts to the BlueSky smoke dispersion model. Forecasts were made available to the field via the web. Modular Local Data Assimilation and Forecast System Integrated within the JAX WFO A measure of success for technology transfer is whether or not the end product is useful. This Area Forecast Discussion issued by the JAX NWS office is an indicator! Surface winds in the JAX area of responsibility are influenced by small scale estuaries that require mesoscale models to be effectively resolved. Shown above is verification of wind speed RMSE (left) and bias (right) from FSL’s Real Time Verification System from the LAPS-initialized WRF (blue), Eta-initialized WRF (green), and the Eta model for all 0600Z runs from 1-20 July 2003. The mesoscale models demonstrate a clear advantage, which is greater when local data assimilation is included. The local modeling capability, combined with the LAPS diabatic initialization, shows promise for improving short range forecasts of precipitation by eliminating the model “spin up” problem with affordable computational solutions. Collaborators: NOAA/GSD/AB (Forecast Verification Section), NOAA/NWS/OST, NOAA/NWS/JAX WFO, Florida State University, NOAA/NOS LAPS Analyses on AWIPS/D3D for 10km domain centered in Colorado Brent Shaw 3 1 Cooperative Research for Research in the Atmosphere ( CIRA) 2 NOAA / Earth System Research Laboratory (ESRL) 3 Weather Decision Technologies