Zhaoxia Pu University of Utah, Salt Lake City, UT Bruce Gentry NASA/GSFC, Greenbelt, MD

1. Assessing the minimum requirements of Doppler wind lidar measurements for seasonal climate studies and high impact weather forecasting: Recent progress and future plan Zhaoxia Pu University of Utah, Salt Lake City, UT Bruce Gentry NASA/GSFC, Greenbelt, MD Belay Demoz Howard University, Washington, DC Acknowledgements:Dr. Ramesh Kakar, NASA/HQ Dr. Michiko Masutani, EMC/NCEP Meeting of the Working Group on Space-Based Lidar Winds Wintergreen, VA, July 8 – 11, 2008

2. Outline • Background • Objective • Research components • Recent progress and preliminary results • Future work

3. Background • NASA has classified tropospheric wind profiling as high-priority science and invested in wind profiling instrument development efforts. • It is anticipated the future Doppler wind lidar (DWL) measurements could be helpful for both seasonal climate studies and high-impact weather forecasting • Objective • Under a NASA supported research project, our main research goal is to assess the minimum requirements of DWL measurements to fulfill the needs for 1) seasonal climate studies, and 2) analysis and forecasting of mesoscale high-impact weather Systems, such as hurricanes and winter storms etc.

4. Research components • I. Determine the minimum requirements (areas that must be targeted; resolution, accuracy etc.) of DWL measurements in representing the seasonal variability of global wind profiles. • Investigate the climatology of global wind profiles and • uncertainties of current global wind analysis • Analyze the error characteristics of the future DWL measurements • from recent available data (e.g., GLOW, coherent wind lidar data etc.) • Compare the climatology of global wind profiles with the • statistics of expected Doppler lidar wind profiles • II. Determine the minimum configuration (resolution, components, error tolerance) of DWL measurements in improving high impact weather forecasting • Mesoscale Observing System Simulation Experiments (OSSEs)

5. The uncertainties of global wind analysis NCEP/NCAR Reanalysis vs. ERA-40, 1980-1999 Mean wind speed and vector differences between two reanalyses at 850mb Mean wind speed and vector from NCEP reanalysis at 850mb Mean wind speed and vector differences between two reanalyses at 500mb Mean wind speed and vector from NCEP reanalysis at 500mb The analyses tends to be different when observations are lack in some areas. This implies the wind observations must be sampled in these areas where the analysis is mostly uncertain.

6. Uncertainties in global wind analysis NCEP/NCAR Reanalysis vs. ERA-40, (1980-1999 ) Seasonal variability of meridianally averaged v, DJF(winter) vs. JJA(summer) • There is difference in terms of • the seasonal wind variability • represented by two reanalysis • products (at least in the • magnitude of the variability) • It is important that the future DWL • data could be helpful to accurately • present the seasonal wind variability.

7. Variation of monthly mean wind speed with height over the East Coast areas of US (65W-85W, 25N-50N) from ECMWF reanalysis (1980-1999) Future Doppler Lidar Wind should be good enough to detect monthly and seasonal variations of the wind profiles in details

8. IHOP_2002: Domain and Instrumentation • Lidars (7) • SRL, GLOW, HARLIE, DLR, LASE, LEANDRE-II, HRDL • Aircraft (6) • NASA DC-8, NRL-P3, DLR-FALCON, LEAR Jet, UW King Air, Proteus • Mobile Radars(5) • W-band (UMASS, OU), SMART-R, (2) DOWs (Penn State), XPOW (U Conn) • Mobile Mesonet • Oklahoma Mesonet • ARM SGP facilities • GOES satellite • GPS, AERONET, etc Homestead Spol • GSFC/LIDAR Highlights: • First simultaneous deployment for SRL, GLOW, HARLIE • First attempt at extended lidar operation

9. Error characteristics of the data from Goddard Lidar Observatory for Winds (GLOW) Mean and Standard Derivation from data collected during IHOP (for May 2002)

10. Altitude distribution

11. Wind speed distribution

12. Wind direction distribution

13. 40 No. Pts: 6051 35 Res: 50m 30 25 Sonde Speed (m/s) 20 15 10 5 0 0 5 10 15 20 25 30 35 40 Lidar Speed (m/s) Sonde speed vs Lidar speed50 m, 3 minute

14. Speed difference distribution(Lidar-sonde)

15. June 21, 2002, low level jet at Homestead, OK Sonde GLOW Wind features agree well below the 4km GLOW data show more detailed structures

16. Work in progress • Continue on investigating the climatology of global wind profiles • and uncertainties in current global wind analysis • Analyze the error characteristics of the wind lidar data from • GLOW • Expected near future progress • Obtain the expected Doppler Lidar wind profiles from • the GLOW wind data, coherent wind lidar data, as well as profiler • and sondes data from the Howard Beltsville site when they are • available • Compare the climatology of global wind profiles with the • statistics of expected Doppler lidar wind profiles

17. Mesoscale OSSEs • General Concept of OSSE (courtesy of R. Atlas 2008) • For mesoscale OSSEs • * “Nature” -- ECMWF nature run (T799NR) • * “ Data assimilation system -- Weather Research and Forecasting (WRF) • model and its four-dimensional variational data assimilation (4DVAR) system • * Simulated observations: Doppler Lidar Winds

18. Current activity -- work in progress • Involve in a joint OSSEs (Masutani 2008) • Evaluate hurricane cases in the ECMWF natural runs at both T799 and • T511 resolutions • Evaluate winter storm cases from ECMWF natural run (T511 NR) • Future work • Identify the hurricane and winter storm cases from ECMWF natural runs • Conduct OSSEs to • 1) evaluate the impact of the DWL measurements on the forecasts of hurricanes and winter storms • 2) determine the minimum requirements of DWL measurements in improving the hurricane intensity forecast.