24th International Laser Rader Conference23-27 June 2008: Boulder, Colorado - USA Progress in Joint OSSEs New nature runs and international collaboration M. Masutani 1# , E. Andersson 4 , G. D. Emmitt 6 , A. Stoffelen 7 , G.J. Marseille 7 , L. Riishojgaard 2,$,11 , R. Errico 2$ , J. S. Woollen 1+ , T. W. Schlatter 5 , F. Weng 3 , Z. Toth 1 , S. Lord 1 , S. A. Wood 6 , S. Greco 6 , Y. Xie 5 , T. Zhu 3@ , R. Yang 2& , H. Sun 3% , N. Prive 5 , O. Reale 2$ , A. da Silva 2 , M. J. McGill 2 , V. Anantharaj 8 , C. Hill 8 , P. J. Fitzpatrick 8 , D. Devenyi 5 , S. Weygandt 5 , Y. Song 1* , T. Miyoshi 9, T. Enomoto 10 , M. Yamaguchi 9 , E. Liu 2+ , D. Groff 1,11,+ , D. Kleist 1,11,+ 1 NOAA/NWS/NCEP/EMC, Camp Springs, MD 2 NASA/GSFC, Greenbelt, MD 3 NOAA/NESDIS/ORA, Camp Springs, MD 4 European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK 5 NOAA/Earth System Research Laboratory, Boulder, CO 6 Simpson Weather Associates (SWA), Charlottesville, VA 7 Royal Dutch Meteorological Institute (KNMI), DeBilt, Netherlands 9 Japanese meteorological Agency, Tokyo, Japan 10 The Japan Marine Science & Technology Center (JAMSTEC), Yokohama, Japan 8 Mississippi State University/GRI, MS 11 Joint Center for Satellite and Data Assimilation # RS Information Systems (RSIS), VA + Science Applications International Corporation (SAIC) $ Goddard Earth Science and Technology Center, University of Maryland, Baltimore, MD % QSS Group, Inc. *I. M. Systems Group, Inc. (IMSG) & Science Systems and Applications Inc (SSAI). MD @ Cooperative Institute for Research in the Atmosphere (CIRA)/CSU, CO 1. INTRODUCTION Building and maintaining observing systems (OS) with new instruments is extremely costly, particularly when satellites are involved. Objective methods that can evaluate the improvement in forecast skill due to the selection of instruments and configurations have long been sought. For future instruments, the forecast skill evaluation needs to be performed using simulation experiments, known as Observing System Simulation Experiments (OSSEs). The OSSE itself is a very expensive project; however, its cost is a small fraction of the total cost of an actual OS. By running OSSEs, current operational data assimilation systems (DAS) can be upgraded to handle new data types and their volume, thus accelerating the use of future instruments and OS’s. Additionally, OSSEs can hasten database development, and the development of data processing techniques (including formatting) and quality control software. Recent OSSEs show that some basic tuning strategies can be developed before the actual data become available. All of this will accelerate the operational use of new OS. Through the OSSEs future OS will be designed that can be effectively used by DAS and forecast systems to improve weather forecasts, thus giving the maximum societal and economic impact ([1].[2].[3]) Among the many future instruments the Doppler Wind Lidar (DWL) has often been evaluated by OSSEs ([1].[8]) because it is a very costly instrument and, therefore, justifies the cost of an OSSE. NCEP conducted OSSEs to evaluate the impact of DWL and demonstrated that OSSEs are able to provide critical information for assessing observational data impacts [4],[9]. 2. What we can learn from OSSEs It is a challenging task to evaluate the realism of impacts from OSSEs. Due to the uncertainties in an OSSE, the differences between the Nature Run (NR) and real atmosphere, the process of simulating data, and the estimation of observational errors all affect the results. Evaluation metrics also affect the conclusion. OSSE data impacts are often characterized as too optimistic but simulated data impacts can be pessimistic, depending on the model used. Consistency and theoretical backup of the results help in gaining confidence in the results from OSSEs. As more Corresponding author address:. Michiko Masutani, NOAA/NWS/NCEP/EMC, 5200 Auth Road Rm 207, Camp Springs, MD 20746 Michiko.masutani@noaa.gov