1 Rolf Langland NRL-Monterey Plans for Evaluation of Lidar Wind Observations at NRL-Monterey Working Group on Space-Based Lidar Winds 05 Feb 2008.

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Presentation transcript:

1 Rolf Langland NRL-Monterey Plans for Evaluation of Lidar Wind Observations at NRL-Monterey Working Group on Space-Based Lidar Winds 05 Feb 2008

2 1.T-PARC plans - Falcon and P-3 2.Data Assimilation Issues 3.Potential Benefit of Space-Based Lidar Wind Observations Outline of Talk

3 airport base: Atsugi, Japan (tbc with US Navy) alternative airports: Okinawa, Misawa, Iwo Jima (?), Korea (?) flight time: 90 h plus 30 h for transfer planned schedule (depending on funding) total: 7-8 weeks incl. transfer/integration takeoff in Germany: 21 Aug 2008 arrival in Japan: 24/25 August 2008 last day in Japan: 4 October (~6 weeks in Japan) arrival in Germany: 7/8 October real-time data: dropsondes near real-time: aircraft in-situ, lidar quicklooks non-realtime: lidar data lidar aircraft manager: max. range: NM max altitude: 12.8 km (42 kft) Falcon plans: T-PARC 2008

4 wind lidar data: horiz resolution: ~10 km vert. resolution: 100 m number of wind profiles in Japan: 5400 number of profiles on transfer though Siberia: 1800 (the permission for observations in Russia is not certain yet) expected lidar coverage based on the experience from A-TReC 35% for 10-km horizontal resolution 55% for 40-km horizontal resolution Research interests: observation targeting extratropical transition of tropical cyclones and downstream impact value of new observing systems (lidars) tropical moisture export Falcon plans: T-PARC 2008

5 Targeting Guidance for TC forecasts – NOGAPS singular vectors Adjoint-based observation impact evaluation (after reanalysis with T-PARC lidar observations) Conventional observation addition and denial forecast experiments (after reanalysis) NRL plans: T-PARC 2008

6 NOGAPS Singular Vector Targeting Guidance Observation Target TimeForecast Verification Time Target area for additional observations

7 Example of NOGAPS-NAVDAS Adjoint-based Observation Impact Reduction Increase Effect of observations on 24-hr fcst error norm

8 Data Assimilation Issues for Lidar Observations Procedures for super-obbing or thinning of raw data Quality control – innovation checks Specification of observation and representativeness error

9 Potential Benefits of Space-Based Lidar Observations Will observations fill gaps in current observing network (esp mb layer?) Will observations be in forecast error source regions? More accurate than other wind observations? How much data will be provided, and how frequently ?

10 Current GEOSAT Wind Coverage 300 – 500 mb 500 – 700 mb 700 – 800 mb800 – 900 mb Impact of JMA – MTSAT wind observations

11 Error Source Regions – Sensitivity to Initial Conditions January 2007 – 0000 and 1200UTC Analyses NOGAPS - NAVDAS

12 60N 20N 130W 140E Observations in the North Pacific Region North Pacific Ocean

13 04 Feb 2007 (00,06,12,18UTC) Total = 97,183 obs = 6.7% of global data North Pacific region observation data count - NAVDAS Ob Data Count

14 Ob Data Count North Pacific Region Observation Variable Count - NAVDAS 04 Feb 2007 (00,06,12,18UTC)

15 North Pacific observation impact sum - NAVDAS 1-31 Jan 2007 (00UTC analyses) Change in 24h moist total energy error norm (J kg -1 ) Error Reduction

16 Error Reduction (x 1.0e 5 ) Change in 24h moist total energy error norm (J kg -1 ) 1-31 Jan 2007 (00UTC analyses) North Pacific forecast error reduction per-observation Ship Obs Targeted dropsondes = high-impact per- ob, low total impact

17 End of Presentation !

18 Excluding Aircraft & Satwind Observations Global observation density - NAVDAS 04 Feb 2007 (00,06,12,18UTC) Excluding Aircraft Observations Number of data in 5deg x 5deg lat-lon areas All Observations More satellite data over ocean Than over land