GMB Apr24, Wind Profile from Space based DWL Evaluation using OSSEs Michiko Masutani

GMB Apr24, DWL from ESA in 2009

GMB Apr24, 20083

4

5

6

7 GWOS Mission Concept from NASA

GMB Apr24, Michiko Masutani, John S. Woollen, Stephen J. Lord, Yucheng Song, Zoltan Toth,Russ Treadon NCEP/EMC Haibing Sun, Thomas J. Kleespies NOAA/NESDIS G. David Emmitt, Sidney A. Wood, Steven Greco Simpson Weather Associates Joseph Terry NASA/GSFC Co-Authors and Contributors to NCEP OSSEs Acknowledgements: John C. Derber, Weiyu Yang, Bert Katz, Genia Brin, Steve Bloom, Bob Atlas, V. Kapoor, Po Li, Walter Wolf, Jim Yoe, Bob Kistler, Wayman Baker, Tony Hollingsworth, Roger Saunder, and many moor Evaluation of DWL in NCEP OSSEs

GMB Apr24, Nature Run: Serves as a true atmosphere for OSSEs Observational data will be simulated from the Nature Run Nature Run

GMB Apr24, DATA PRESENTATION OSSE Quality Control (Simulated conventional data) OSSE DATA PRESENTATION Quality Control (Real conventional data) OSSE DA Real TOVS AIRS etc. DA Simulated TOVS AIRS etc. NWP forecast Existing data + Proposed data DWL, CrIS, ATMS, UAS, etc Nature Run Current observing system NWP forecast GFS OSSE

GMB Apr24, NCEP OSSE To be upgrade to Joint OSSEs at NCEP Wintertime Nature run (1 month, Feb5-Mar.7,1993) NR by ECMWF model T213 (~0.5 deg) 1993 data distribution for calibration NCEP DA (SSI) withT62 ~ 2.5 deg, 300km and T170 ~1 deg, 110km Simulate and assimilate level1B radiance –Different method than using interpolated temperature as retrieval Use line-of- sight (LOS) wind for DWL –not u and v components Calibration performed Effects of observational error tested NR clouds are evaluated and adjusted

GMB Apr24, Results from OSSEs for Doppler Wind Lidar (DWL) All levels (Best-DWL): Ultimate DWL that provides full tropospheric LOS soundings, clouds permitting. DWL-Upper : An instrument that provides mid- and upper- tropospheric winds down only to the levels of significant cloud coverage. DWL-PBL: An instrument that provides wind observations only from clouds and the PBL. Non-Scan DWL : A non-scanning instrument that provides full tropospheric LOS soundings, clouds permitting, along a single line that parallels the ground track. (ADM-Aeolus like DWL) Zonally and time averaged number of DWL measurements in a 2.5 degree grid box with 50km thickness for 6 hours. Numbers are divided by Note that 2.5 degree boxes are smaller in size at higher latitudes. Estimate impact of real DWL from combination.

GMB Apr24, Forecast hour Doppler Wind Lidar (DWL) Impact Dashed green line is for scan DWL with 20 times less data to make observation counts similar to non-scan DWL. The results show definite advantage of scanning. This experiment is done with T62 model and SSI. No Lidar (Conventional + NOAA11 and NOAA12 TOVS) Scan DWL_Lower Scan DWL Uniformly thinned to 5% Scan DWL_upper Non-scan_DWL Scan_DWL Synoptic Scale Total scale 200 mb V 850 mb V

GMB Apr24, DWL-Upper: Operates only 10% (possibly up to 20%) of the time. Switched on for 10 min at a time. Need DWL-lower to keep instrument warm. DWL-Lower:. Possible to operates 100% of the time and keeps the instruments warm as well as measuring low level wind DWL-NonScan: DWL covers all levels without scanning (ADM mission type DWL) Targeted DWL experiments Combination of lidars Technologically possible scenarios

GMB Apr24, mb 100% Upper Level 10% Upper Level Adaptive sampling (based on the difference between first guess and NR, three minutes of segments are chosen – the other 81 min are discarded) Doubled contour (Feb13 - Mar 6 average ) Non-Scan DWL

GMB Apr24, CTL Anomaly correlation difference from control 200V No Lidar (Conventional + NOAA11 and NOAA12 TOVS) 100% Lower 100% Lower + 100% Upper 100% Lower + 10% Targeted Upper 100% Lower + Non-Scan Non-Scan only Zonal wave 1-20 Zonal wave 10-20

GMB Apr24, CTL Anomaly correlation difference from control 200V No Lidar (Conventional + NOAA11 and NOAA12 TOVS) 100% Lower 100% Lower + 100% Upper 100% Lower + 10% Targeted Upper 100% Lower + Non-Scan Non-Scan only Zonal wave 1-20 Zonal wave DWL-Lower with scan is better than DWL-Non-Scan only even in upper atmosphere With 100% DWl-Lower, targeted 10% DWL-Upper performs somewhat better than DWL-Non-Scan in the analysis DWL non-Scan become better in hour forecast

GMB Apr24, D2+D3: Red: Scan upper+scan Lower D1: Light Blue closed circle: Best DWL (D1) with scan Rep Error 1m/s R45: Cyen dotted line triangle: D1 with rep error 4.5m/s (4.5x4.5≈20) U20: Orange: D1 uniformly thinned for factor 20 (Note this is technologically difficult) N4: Violet:D1 Thinned for factor 20 but in for direction 45,135,225,315 (mimicking GWOS) S10: Green dashed: Scan DWL 10min on 90 min off. No other DWL D4 : Dark Blue dashed: non scan DWL One or Four non-scan-DWL NH V500 Zonal wave number 10-20

GMB Apr24, Difference in AC from CTL (Conventional+TOVS) U and V at 500hPa, top NH Bot SH, left 1-3, right NH SH U500 V500 Zonal wave 1-3 Zonal wave D2+D3: Red: Scan upper+scan Lower D1: Light Blue closed circle:scal-DWL repE1m/s R45: Cyen dotted line triangle: repE 4.5m/s U20: Orange: uniformly thinned to 5% N4: Violet:Four direction S10: Green dashed:Scan DWL 10min on 90 min off. D4 : Dark Blue dashed: non scan DWL

GMB Apr24, Difference in AC from CTL (Conventional+TOVS) T and W at 500hPa, top NH Bot SH, left 1-3, right NH SH T500 W500 Zonal wave 1-3 Zonal wave D2+D3: Red: Scan upper+scan Lower D1: Light Blue closed circle:scal-DWL repE1m/s R45: Cyen dotted line triangle: repE 4.5m/s U20: Orange: uniformly thinned to 5% N4: Violet:Four direction S10: Green dashed:Scan DWL 10min on 90 min off. D4 : Dark Blue dashed: non scan DWL

GMB Apr24, GWOS is better than ADM-Aeolus in the SH, Zonal wave 1-3 T W GWOS ADM U V D2+D3: Red: Scan upper+scan Lower D1: Light Blue closed circle:scal-DWL repE1m/s R45: Cyen dotted line triangle: repE 4.5m/s U20: Orange: uniformly thinned to 5% N4: Violet:Four direction S10: Green dashed:Scan DWL 10min on 90 min off. D4 : Dark Blue dashed: non scan DWL

GMB Apr24, Scan-DWL has much more impact compared to non- scan-DWL with same amount of data. If the data is thinned uniformly 20 times thinned data (U20) produce 50%-90% of impact. 20 times less weighted 100% data (R45) is generally slightly better than U20 (5% of data) In fact U20 and R45 perform better than D1 time to time. This is more clear in 200hPa. Simple GWOS type experiment (N4) showed significant improvement to D4 only in large scale over SH but not much better over NH and synoptic scale. Without additional scan-DWL,10min on 90 off (S10)sampling is much worse than U20(5% uniform thinning) with twice as much as data.

GMB Apr24, Using T62 model forecast skill drop after 48 hr but this will improved with T170 particularly in wave number The results are expected to change with GSI particularly with flow dependent back ground error covariance. OSSE with one month long T213 nature run is limited. Need better nature run. Any comments and advice appreciated

GMB Apr24, Need one good new Nature Run which will be used by many OSSEs, including regional data assimilation. Share the simulated data to compare the OSSE results from various DA systems to gain confidence in results. OSSEs require many experts and require a wide range of resources. Extensive international collaboration within the Meteorological community is essential for timely and reliable OSSEs to influence decisions. Joint OSSEs

GMB Apr24, OSSEs: Observing Systems Simulation Experiments JCSDA: Joint Center for Satellite Data Assimilation SWA: Simpson Weather Associates ESRL: Earth System Research Laboratory (formerly FSL, CDC, ETL) Joint OSSEs April 2008 NCEP: Michiko Masutani, John S. Woollen, Yucheng Song, Stephen J. Lord, Zoltan Toth ECMWF: Erik AnderssonKNMI: Ad Stoffelen, Gert-Jan Marseille JCSDA: Lars Peter Riishojgaard (NASA/GFSC),NESDIS: Fuzhong Weng, Tong Zhu Haibing Sun, SWA: G. David Emmitt, Sidney A. Wood, Steven Greco NASA/GFSC: Ron Errico, Oreste Reale, Runhua Yang, Emily Liu, Joanna Joiner, Harpar Pryor, Alindo Da Silva, Matt McGill, NOAA/ESRL:Tom Schlatter, Yuanfu Xie, Nikki Prive, Dezso Devenyi, Steve Weygandt MSU/GRI: Valentine Anantharaj, Chris Hill, Pat Fitzpatrick, JMA Takemasa Miyoshi, Munehiko. Yamaguchi JAMSTEC Takeshi Enomoto So far most of the work is done by volunteers. People who helped or advised Joint OSSEs. Joe Terry (NASA), K. Fielding (ECMWF), S. Worley (NCAR), C.-F., Shih (NCAR), Y. Sato (NCEP,JMA), Lee Cohen(ESRL), David Groff(NCEP), Daryl Kleist(NCEP), J Purser(NCEP), Bob Atlas(NOAA/AOML), C. Sun (BOM), M. Hart(NCEP), G. Gayno(NCEP), W. Ebisuzaki (NCEP), A. Thompkins (ECMWF), S. Boukabara(NESDIS), John Derber(NCEP), X. Su (NCEP), R. Treadon(NCEP), P. VanDelst (NCEP), M Liu(NESDIS), Y Han(NESDIS), H.Liu(NCEP),M. Hu (ESRL), Chris Velden (SSEC), William Lahoz (Reading), George Ohring(JCSDA), Many more people from NCEP,NESDIS, NASA, ESRL More people are working on proposal, getting involved or considering participation. Z. Pu(Univ. Utah), Lidia Cucil (EMC, JCSDA), G. Compo(ESRL), Prashant D Sardeshmukh(ESRL), M.-J. Kim(NESDIS), Jean Pailleux(Meteo France), Roger Saunders(Met Office), C. O’Handley(SWA), E Kalnay(U.MD), A.Huang (U. Wisc), Craig Bishop(NRL), Hans Huang(NCAR),

GMB Apr24, New Nature Run by ECMWF Based on Recommendations by JCSDA, NCEP, GMAO, GLA, SIVO, SWA, NESDIS, ESRL Low Resolution Nature Run Spectral resolution : T511 Vertical levels: L91 3 hourly dump Initial conditions: 12Z May 1 st, 2005 Ends at: 0Z Jun 1,2006 Daily SST and ICE: provided by NCEP Model: Version cy31r1 Two High Resolution Nature Runs 35 days long Hurricane season: Starting at 12z September 27,2005, Convective precipitation over US: starting at 12Z April 10, 2006 T799 resolution, 91 levels, one hourly dump Get initial conditions from T511 NR

GMB Apr24, To be archived in the MARS system on the THORPEX server at ECMWF Accessed by external users. Currently available internally as expver=etwu Copies for US are available to designated users for research purpose& users known to ECMWF Saved at NCEP, ESRL, and NASA/GSFC Complete data available from portal at NASA/GSFC Conctact:Michiko Masutani Archive and Distribution Supplemental low resolution regular lat lon data 1degx1deg for T511 NR, 0.5degx0.5deg for T799 NR Pressure level data: 31 levels, Potential temperature level data: 315,330,350,370,530K Selected surface data for T511 NR : Convective precip, Large scale precip, MSLP,T2m,TD2m, U10,V10, HCC, LCC, MCC, TCC, Sfc Skin Temp Complete surface data for T799 NR Posted from NCAR CISL Research Data Archive. Data set ID ds621.0 Currently NCAR account is required for access. (Also available from NCEP hpss, NASA/GSFC Portal, ESRL, NCAR/MMM, NRL/MRY, Univ. of Utah, JMA) Note: This data must not be used for commercial purposes and re- distribution rights are not given. User lists are maintained by Michiko Masutani and ECMWF