Michiko Masutani Joint OSSE coordinator NOAA/NWS/NCEP/EMC Progress and Plans in Joint OSSEs

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Presentation transcript:

Michiko Masutani Joint OSSE coordinator NOAA/NWS/NCEP/EMC Progress and Plans in Joint OSSEs

More evaluations of Nature Run performed and planned Comparison between the ECMWF T511 Nature Run against climatology of observation , exp=eskb, cycle=31r1 Adrian Tompkins, ECMWF Initial assessment Erik Andersson(ECMWF) Cyclone track Thomas Jung (ECMWF) Comparison of zonal mean zonal wind jet maxima, NR and ECMWF analysis, NH Arctic winter in Nature Run Nikki Prive, ESRL Evaluation of Clouds Simpson Weather Associates SWA Case Events Identified from ECMWF T799 NR MSU Study of Low level jet Juan Carlos Jusem,NASA/SIVO Drift in Nature run Diurnal cycle Michiko Masutani, EMC

Simulation of Conventional Observations Jack Woollen (NCEP/EMC), Ron Errico (NASA/GMAO) Simulation of Radiance for Calibration GMAO, NESDIS, NCEP Tong Zhu, Haibing Sun, Fuzhong Weng(NOAA/NESDIS) Jack Woollen(NOAA/NCEP) Ron Errico, Runhua Yang, Emily Liu, Lars Peter Riishojgaard, Ravi Govindaraju (NASA/GSFC/GMAO) Simulation of Observations required for calibration Existing instrument experiments must be simulated for control and calibration and development of DAS and RTM Test GOESR, NPOESS, and other future satellite data Calibration experiments EMC,GMAO,ESRL Cloud Motion Vectors SWA - Advised by Chris Velden -

Uniform Raob for testing DAS EMC Scatterometer KNMI has capibility Simulation Radiance data to be evaluated by OSSEs GMAO,NESDIS,MSU,JCSDA, UW/SSEC and more Simulation of Observations Simulation of DWL KNMI, SWA, NASA/GSFC, Ball(?) Unmanned Air Craft System (UAS) NOAA/ESRL

OSSEs for THORPEX T-PARC EMC, FSU, ESRL Regional OSSEs to Evaluate ATMS and CrIS Observations GRI/Mississippi State Univ (MSU), JCSDA OSSE to evaluate UAS ESRL and NCEP OSSEs planned Funded or seeking funding but starting with volunteers OSSEs to investigate data impact of GOES and preparation for GOES-R NESDIS, EMC OSSE to evaluate DWL KNMI,SWA,EMC, GMAO, NOAA/ESRL, and more

Identical twin experiments It is worthwhile to try identical twin experiments to understand model error. Identical twin OSSEs can be only used for illustration only. ECMWF offered to perform identical twin OSSEs if there is specific goals. (Erik Andersson) Assimilation with LETKF possibly by 4D-var T. Miyoshi(JMA) and T. Enomoto(JAMSTEC) Sensor Web NASA/GSFC/SIVO, SWA Analysis with surface pressure Gil Compo, P. D. Sardeshmukh (ESRL) Various planned OSSE-related activities Visualization of the Nature run Jibo Sanyal (MSS), O. Reale (NASA/GSFC/GLA), H. Mitchell(NASA/GSFC/SIVO)

Regional OSSEs to evaluate DWL Zhaoxia Pu,Univ of Utah Targeted Observation using LETKF Eugenia Kalnay, UMCP Projects being considered or seeking funding and various possibilities Simulation of ASCAT QuickScat XOVMM Scatterometer Ad Stoffelen, KNMI OSSE to design configuration of GPS Lidia Cucurull,JCSDA,EMC Evaluation of Drift Buoy Jean Pailleux, Meteo France Evaluation of RAOB Drift Erik Andersson,EMCWF More possibilities: Evaluation of retrieval program Simulating Gestational DWL, Ball Evaluation data assimilation system Ron Errico, GMAO

♦ Produce perfect data and run calibration experiments ♦ Design representativeness error and observational error and redo calibration ♦ Development of standard verification package ♦ Clarify potential and limitations of OSSE and educate community ♦ Meso/Regional OSSEs Joint OSSE team agreed we have to concentrate on OSSEs with existing NRs to study superobbed data impact of high resolution data. However, there are strong demands for mesoscale OSSEs. Joint OSSE team is working on integrating mesoscale OSSE interest. ♦ Coordination of work - Uniform representation of observational data and results - Keep track who actually did the work and various contributions - Organizing publication OSSE Chapter in Data Assimilation book from Springer Introductory article in BAMS ♦ Joint OSSE web site Getting ready for OSSEs

Requirements for a future Nature Run - Some suggestions - ♦ The NWP model must have good forecast skill. Great visualization does not guarantee good forecast skill. ♦ At least a 3 month lower resolution run with the same model is required to provide a spin-up period for bias correction. ♦ Must have a good TC or a severe storm in the Nature Run period. ♦ Sufficient number of vertical levels: Minimum 91 levels ♦ Some degree of coupling with the ocean and land surface ♦ If it is regional, the effect of the lateral boundary must be evaluated. ♦ A list of verification methods must be produced by Joint OSSE. ♦ Need NR to be shared within Joint OSSE ♦ User friendly archive We need to avoid many poorly planned and assessed nature run