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Assessing the minimum requirements of Doppler wind lidar measurements for seasonal climate studies and high impact weather forecasting: Recent progress and

future plan

Zhaoxia PuUniversity of Utah, Salt Lake

City, UT

Bruce GentryNASA/GSFC, Greenbelt, MD

Belay DemozHoward University, Washington, DC

Meeting of the Working Group on Space-Based Lidar WindsWintergreen, VA, July 8 – 11, 2008

Acknowledgements: Dr. Ramesh Kakar, NASA/HQ Dr. Michiko Masutani, EMC/NCEP

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Outline

• Background

• Objective

• Research components

• Recent progress and preliminary results

• Future work

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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.

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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)

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The uncertainties of global wind analysis NCEP/NCAR Reanalysis vs. ERA-40, 1980-1999

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.

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

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Uncertainties in global wind analysis NCEP/NCAR Reanalysis vs. ERA-40, (1980-1999

)

• There is difference in terms of the seasonal wind variability represented by two reanalysisproducts (at least in the magnitude of the variability)

• It is important that the future DWLdata could be helpful to accuratelypresent the seasonal wind variability.

Seasonal variability of meridianally averaged v, DJF(winter) vs. JJA(summer)

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Variation of monthly mean wind speed with heightover 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

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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 MesonetOklahoma MesonetARM SGP facilitiesGOES satelliteGPS, AERONET, etc

IHOP_2002: Domain and Instrumentation

Homestead

Spol

GSFC/LIDAR Highlights: • First simultaneous deployment for SRL, GLOW, HARLIE• First attempt at extended lidar operation

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Error characteristics of the data from Goddard Lidar Observatory for Winds (GLOW)

Mean and Standard Derivation from data collected during IHOP (for May 2002)

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Altitude distribution

-2 0 2 4 6 8 10 120

50

100

150

200

250

Altitude (km)

Number of Occurrences

No. Pts: 6051Res: 50m

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Wind speed distribution

-10 0 10 20 30 40 500

50

100

150

200

250

300

Speed (m/s)

Number of occurrences

No. Pts: 6051Res: 50m

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Wind direction distribution

0 50 100 150 200 250 300 3500

100

200

300

400

500

600

700

800

Direction (deg)

No. Pts: 6051Res: 50m

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Sonde speed vs Lidar speed50 m, 3 minute

0 5 10 15 20 25 30 35 400

5

10

15

20

25

30

35

40

Lidar Speed (m/s)

Sonde Speed (m/s)

No. Pts: 6051Res: 50m

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Speed difference distribution(Lidar-sonde)

-50 0 500

50

100

150

200

250

300

350

400

Mean: 0.13407 StdDev: 4.0535 Median: -0.20294No. Pts: 6051 Res: 50m

Speed Difference (m/s)

Number of occurrences

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June 21, 2002, low level jet at Homestead, OK

GLOW

Sonde

Wind features agree well below the 4kmGLOW data show more detailed structures

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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 thestatistics of expected Doppler lidar wind profiles

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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

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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.