1. Lightning NextGen Workshop
Steve Albers
NOAA / ESRL / GSD / FAB
March 2010

2. Icing NextGen Workshop
Steve Albers
NOAA / ESRL / GSD / FAB
March 2010

3. Derived products flow chart

4. Radar X-sect (wide/narrow band)

5. Ceiling and Visibility NextGen Workshop
Steve Albers, Paul Schultz, Yuanfu Xie
NOAA/ESRL/GSD/FAB
March 2010

6. LAPS cloud analysis
METAR
METAR
METAR

7. Hot-start and Cloud analysis
LAPS hot-start scheme
Dramatically improves
Very short-range forecast,
Importance to terminal
Scale convective forecast
References: ???
The hot-start scheme will be adapted into
STMAS, a multigrid variational data
Assimilation system with satellite, radar,
And conventional obs and model dynamic
Constraint simultaneously.

8. 3D Cloud Image

9. Cloud Analysis Flow Chart

10. Cloud/precip cross section

11. Satellite use in Cloud Analysis
11 micron IR
3.9 micron data
Visible (with terrain albedo database)
CO2-Slicing method (Cloud-top pressure)

12. End

13. Surface Precipitation Accumulation
Algorithm similar to NEXRAD PPS, but runs
in Cartesian space
Rain / Liquid Equivalent
Z = 200 R ^ 1.6
Snow case: use rain/snow ratio dependent on column maximum temperature
Checks on Z and T could be added to reduce bright band effect

14. Storm-Total Precipitation

15. Future Cloud / Radar analysis efforts
Account for evaporation of radar echoes in dry air
Sub-cloud base for NOWRAD
Below the radar horizon for full volume reflectivity
Processing of multiple radars and radar types
Evaluate Ground Clutter / AP rejection

16. Future Cloud/Radar analysis efforts (cont)
Consider Terrain Obstructions
Improve Z-R Relationship
Convective vs. Stratiform
Precipitation Analysis
Improve Sfc Precip coupling to 3D hydrometeors
Combine radar with other data sources
Model First Guess
Rain Gauges
Satellite Precip Estimates (e.g. GOES/TRMM)

17. 11 micron imagery T(11u) best detects mid-high level clouds
Cloud Clearing Step
Cloud Building Step
Iterative Adjustment Step
Forward model converts cloud-sounding T(11u) estimate
Constrained 1DVAR iteration fits cloud layers to observed T(11u)

18. 3.9 micron imagery T(3.9u) – T(11u) detects stratus at night
Currently used with 11u cloud-tops for cloud building
Testing underway for cloud-clearing
Additional criteria include T(11u) and land fraction
T(3.9u) – T(11u) detects clouds in the daytime?
Visible may be similar in cloud masking properties
Visible may be easier for obtaining a cloud fraction
Cloud Phase?
Could work using T(3.9u) – T(11u) at night
Cloud-top phase needs blending throughout LWC/ICE column

19. Visible Satellite Improving visible with terrain albedo database
Cloud-clearing (done with current analysis)
Cloud-building (now being tested)
Accurate sfc albedo can work with VIS + 11 micron cloud-tops
Visible cloud fraction can be used to correct apparent brightness temperature to yield improved cloud-top temperature

20. Cloud Schematic

21. Visible Satellite Impact

22. CO2 Slicing Method (cloud-top P)
Subset of NESDIS Cloud-Top Pressure data
CO2 measurements add value
11u measurements (0 or 1 cloud fraction) redundant with imagery?
Imagery has better spatial and temporal resolution?
Treat as a “cloud sounding” similar to METARs and PIREPs

23. Selected references
Albers, S., 1995: The LAPS wind analysis. Wea. and Forecasting, 10,
Albers, S., J. McGinley, D. Birkenheuer, and J. Smart, 1996: The Local Analysis and prediction System (LAPS): Analyses of clouds, precipitation and temperature. Wea. and Forecasting, 11,
Birkenheuer, D., B.L. Shaw, S. Albers, E. Szoke, 2001: Evaluation of local-scale forecasts for severe weather of July 20, Preprints, 14th Conf on Numerical Wea. Prediction, Ft. Lauderdale, FL, Amer. Meteor. Soc.
Cram, J.M.,Albers, S., and D. Devenyi, 1996: Application of a Two-Dimensional Variational Scheme to a Meso-beta scale wind analysis. Preprints, 15th Conf on Wea. Analysis and Forecasting, Norfolk, VA, Amer. Meteor. Soc.
McGinley, J., S. Albers, D. Birkenheuer, B. Shaw, and P. Schultz, 2000: The LAPS water in all phases analysis: the approach and impacts on numerical prediction. Presented at the 5th International Symposium on Tropospheric Profiling, Adelaide, Australia.
Schultz, P. and S. Albers, 2001: The use of three-dimensional analyses of cloud attributes for diabatic initialization of mesoscale models. Preprints, 14th Conf on Numerical Wea. Prediction, Ft. Lauderdale, FL, Amer. Meteor. Soc.

24. Precip type and snow cover

25. The End

26. Remapping Strategy Polar to Cartesian
2D or 3D result (narrowband / wideband)
Average Z,V of all gates directly illuminating each grid box
QC checks applied
Typically produces sparse arrays at this stage

27. Doppler & Other Wind Obs

28. Single / Multi-radar Wind Obs

29. LAPS 700Hpa Winds

30. Remapping Strategy (reflectivity)
Horizontal Analysis/Filter (Reflectivity)
Needed for medium/high resolutions (<5km) at distant ranges
Replace unilluminated points with average of immediate grid neighbors (from neighboring radials)
Equivalent to Barnes weighting at medium resolutions (~5km)
Extensible to Barnes for high resolutions (~1km)
Vertical Gap Filling (Reflectivity)
Linear interpolation to fill gaps up to 2km
Fills in below radar horizon & visible echo

31. LAPS radar ingest

32. Horizontal Filter/Analysis
Before
After

33. Mosaicing Strategy (reflectivity)
Nearest radar with valid data used
+/- 10 minute time window
Final 3D reflectivity field produced within cloud analysis
Wideband is combined with Level-III (NOWRAD/NEXRAD)
Non-radar data contributes vertical info with narrowband
QC checks including satellite
Help reduce AP and ground clutter

34. Reflectivity (800 hPa)

35. Future LAPS analysis work
Surface obs QC
Operational use of Kalman filter (with time-space conversion)
Handling of surface stations with known bias
Improved use of radar data for AWIPS
Multiple radars
Wide-band full volume scans
Use of Doppler velocities
Obtain observation increments just outside of domain
Implies software restructuring
Add SST to surface analysis
Stability indices
Wet bulb zero, K index, total totals, Showalter, LCL (AWIPS)
LI/CAPE/CIN with different parcels in boundary layer
new (SPC) method for computing storm motions feeding to helicity determination
More-generalized vertical coordinate?

36. Recent analysis improvements
More generalized 2-D/3-D successive correction algorithm
Utilized on 3-D wind/temperature, most surface fields
Helps with clustered data having varying error characteristics
More efficient for numerous observations
Tested with SMS
Gridded analyses feed into variational balancing package
Cloud/Radar analysis
Mixture of 2D (NEXRAD/NOWRAD low-level) and 3D (wide-band volume radar)
Missing radar data vs “no echo” handling
Horizontal radar interpolation between radials
Improved use of model first guess RH &cloud liq/ice

37. Cloud type diagnosis
Cloud type is derived as a function of temperature and stability

38. LAPS data ingest strategy

39. Cloud/precip cross section

40. Wind Analysis Flow Chart