The Fusion of Radar Data and Satellite Imagery With Other Information in the LAPS Analyses

1
The Fusion of Radar Data and Satellite Imagery
With Other Information in the LAPS Analyses

• Steve Albers
• August 10, 2010

2
LAPS Radar Ingest
Level-II Broadcast Data (IRADS Network)
NOWRAD netCDF (Low-level Reflectivity)
Level-III AWIPS
LAPS script (LapsRadar.pl) calls WFO program
(tfrNarrowband2netCDF)
GSD Central Facility Processing
vrc_driver.x
Polar netCDF File (GSD NIMBUS Format)
Remap_polar_netcdf.exe
2-D LAPS Grid Reflectivity (VRC)
3-D LAPS Grid Ref Vel (VXX)
Mosaic_radar.x (multiple radar input)
2-D LAPS Grid Reflectivity (VRC)
3-D LAPS Grid Reflectivity (VRZ)
3
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

4
Doppler Other Wind Obs
5
Single / Multi-radar Wind Obs
6
Wind Analysis Flow Chart
7
LAPS 700Hpa Winds
8
Remapping Strategy (reflectivity)

• Horizontal Analysis/Filter (Reflectivity)
• Needed for medium/high resolutions (lt5km) 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

9
Horizontal Filter/Analysis
Before
After
10
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

11
Reflectivity (800 hPa)
12
Radar X-sect (wide/narrow band)
13
LAPS cloud analysis
METAR
METAR
METAR
14
3D Cloud Image
15
CloudSchematic
16
Cloud Analysis Flow Chart
17
Derived products flow chart
18
Cloud/precip cross section
19
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

20
Storm-Total Precipitation
21
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

22
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)

23
Cloud/Satellite Analysis Topics

• 11 micron IR
• 3.9 micron data
• Improving visible with terrain albedo database
• CO2-Slicing method (Cloud-top pressure)

24
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)

25
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

26
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

27
Visible Satellite Impact

28
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

29
Selected references

• Albers, S., 1995 The LAPS wind analysis. Wea.
  and Forecasting, 10, 342-352.
• 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,
  273-287.
• Birkenheuer, D., B.L. Shaw, S. Albers, E. Szoke,
  2001 Evaluation of local-scale forecasts for
  severe weather of July 20, 2000. 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.

30
Precip type and snow cover
31
The End
32
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?

33
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

34
Cloud type diagnosis
Cloud type is derived as a function of
temperature and stability
35
LAPS data ingest strategy
36
Cloud/precip cross section
37
The End
38
LAPS radar ingest