1. Using LAPS in the Forecast OfficeBy
Steve Albers
May 2002

2. LAPS A system designed to: Exploit all available data sources
Create analyzed and forecast grids
Build products for specific forecast applications
Use advanced display technology
…All within the local weather office

3. Why do analysis in the local office?

4. “THE CONCEPT OF THE LOCAL DATA BASE IS CENTRAL TO FUTURE OPERATIONS…THE MOST COMPLETE DATA SETS WILL ONLY BE AVAILABLE TO THE LOCAL WFO. THE NEW OBSERVING SYSTEMS ARE DESIGNED TO PROVIDE INTEGRATED 3-D DEPICTIONS OF THE RAPIDLY CHANGING STATE OF THE ENVIRONMENT.”
-Strategic plan for the modernization and associated restructuring of the National Weather Service

5. LAPS Flow Diagram

6. LAPS Grid LAPS Grid (in AWIPS) Hourly Time Cycle
Horizontal Resolution = 10 km
Vertical Resolution = 50 mb
Size: 61 x 61 x 21

7. Data Acquisition and Quality Control

9. LAPS Data Sources
The blue colored data are currently used in AWIPS LAPS. The other data are used in the "full-blown" LAPS and can potentially be added to AWIPS/LAPS if the data becomes available.

10. Local Surface Data
Local Data may be defined as that data not entering into the National Database
Sources
Highway Departments
Many States with full or partial networks
Agricultural Networks
State run, sometimes private
Universities and Other Schools
Experimental observations
Private Industry
Environmental monitoring
State and Federal Agencies
RAWS

12. Problems with Local Data
Poor Maintenance
Poor Communications
Poor Calibration
Result > Inaccurate,
Irregular,
Observations

13. Multi-layered Quality Control
Gross Error Checks
Rough Climatological Estimates
Station Blacklist
Dynamical Models
Use of meso-beta models
Standard Deviation Check
Statistical Models (Kalman Filter)
Buddy Checking

14. Standard Deviation Check
Compute Standard Deviation of observations-background
Remove outliers
Now adjustable via namelist

15. Kalman QC Scheme FUTURE Upgrade to AWIPS/LAPS QC
Adaptable to small workstations
Accommodates models of varying complexity
Model error is a dynamic quantity within the filter, thus the scheme adjusts as model skill varies

16. Kalman Flow Chart

17. AWIPS 5.1.2 LAPS Improvements:
Wind Profiler Ingest restored
QC threshold tightened
Surface Stations
More local (LDAD) station data
Improved QC of MSLP

18. AWIPS 5.2.1 LAPS Improvements:
Surface Analysis
Improved Successive Correction considers
instrument and background errors
Works with uneven station spacing and terrain
Reduction of bulls-eye effects (that had occurred even with valid stations)
Improved Surface Pressure Consistency
MSLP
Reduced
Unreduced (terrain following)

19. AWIPS 5.2.2 LAPS Improvements:
Additional Backgrounds such as AVN
Supports LAPS in Alaska, Pacific
Domain Relocatability
Surface Analysis
Improved fit between obs and analysis
Corrected “theta check” for temperature analysis at high elevation sites
Stability Indices added
Wet Bulb Zero, K, TT, Showalter, LCL

20. Candidate Future Improvements:
GUI
Domain Resizability
Graphical Product Monitor
Surface Obs QC
Turning on Kalman Filter QC (sfc_qc.exe)
Tighten T, Td QC checks
Allow namelist adjustment of QC checks
Handling of surface stations with known bias

21. Candidate Future Improvements (cont):
Surface Analysis
Land/Sea weighting to help with coastline effects
Adjustment of reduced pressure height
Other Background Models
Hi-res Eta?
Improved use of radar data
Multiple radars?
Wideband Level-II data?
Sub-cloud evaporation
Doppler radial velocities

22. Candidate Future Improvements (cont.)
Use of visible & 3.9u satellite in cloud analysis
LI/CAPE/CIN with different parcels in boundary layer
New (Bunkers) method for computing storm motions feeding to helicity determination
Wind profiler
Include obs from just outside the domain
Implies restructuring wind analysis
ACARS
Forecast Model (Hot-Start MM5)

23. Sources of LAPS Information
The LAPS homepage
provides access to many links including:
What is in AWIPS LAPS?

24. Analysis Information LAPS analysis discussions are near the bottom of:
Especially noteworthy are the links for
Satellite Meteorology
Analyses: Temperature, Wind, and Clouds/Precip.
Modeling and Visualization
A Collection of Case Studies

25. 3-D Temperature Interpolate from model (RUC)
Insert RAOB, RASS, and ACARS if available
3-Dimensional weighting used
Insert surface temperature and blend upward
depending on stability and elevation
Surface temperature analysis depends on
METARS, Buoys, and LDAD
Gradients adjusted by IR temperature

26. 3-D Clouds
Preliminary analysis from vertical “soundings” derived from METARS and PIREPS
IR used to determine cloud top (using temperature field)
Radar data inserted (3-D if available)
Visible satellite can be used

27. 3-D Cloud Analysis

29. LAPS Snow Cover and Precip. Type

30. LAPS 3-D Water Vapor (Specific Humidity) Analysis
Interpolates background field from synoptic-scale model forecast
QCs against LAPS temperature field (eliminates possible supersaturation)
Assimilates RAOB data
Assimilates boundary layer moisture from LAPS Sfc Td analysis
Scales moisture profile (entire profile excluding boundary layer) to agree with derived GOES TPW (processed at NESDIS)
Scales moisture profile at two levels to agree with GOES sounder radiances (channels 10, 11, 12). The levels are hPa, and above 500
Saturates where there are analyzed clouds
Performs final QC against supersaturation

32. Products Derived from Wind Analysis

33. An example of the use of LAPS in convective event
Case Study Example
An example of the use of LAPS in convective event
14 May 1999
Location: DEN-BOU WFO

34. Quote from the Field
"...for the hourly LAPS soundings, you can go to interactive skew-T, and loop the editable soundings from one hour to the next, and get a more accurate idea of how various parameters are changing on an hourly basis...nice. We continue to find considerable use of the LAPS data (including soundings) for short-term convective forecasting."

35. Case Study Example
On 14 May, moisture is in place. A line of storms develops along the foothills around noon LT (1800 UTC) and moves east. LAPS used to diagnose potential for severe development. A Tornado Watch issued by ~1900 UTC for portions of eastern CO and nearby areas.
A brief tornado did form in far eastern CO west of GLD around 0000 UTC the 15th. Other tornadoes occurred later near GLD.

36. NOWRAD and METARS with LAPS surface CAPE
2100 UTC

37. NOWRAD and METARS with LAPS surface CIN
2100 UTC

38. Dewpoint max appears near CAPE max, but between METARS
2100 UTC

39. Examine soundings near CAPE max at points B, E and F
2100 UTC

40. Soundings near CAPE max at B, E and F
2100 UTC

41. RUC also has dewpoint max near point E
2100 UTC

42. LAPS & RUC sounding comparison at point E (CAPE Max)
2100 UTC

43. CAPE Maximum persists in same area
2200 UTC

44. CIN minimum in area of CAPE max
2200 UTC

45. Point E, CAPE has increased to 2674 J/kg
2200 UTC

46. Convergence and Equivalent Potential Temperature are co-located
2100 UTC

47. How does LAPS sfc divergence compare to that of the RUC?
Similar over the plains.
2100 UTC

48. LAPS winds every 10 km, RUC winds every 80 km
2100 UTC

49. Case Study Example (cont.)
The next images show a series of LAPS soundings from near LBF illustrating some dramatic changes in the moisture aloft. Why does this occur?

50. LAPS sounding near LBF
1600 UTC

51. LAPS sounding near LBF
1700 UTC

52. LAPS sounding near LBF
1800 UTC

53. LAPS sounding near LBF
2100 UTC

54. Case Study Example (cont.)
Now we will examine some LAPS cross-sections to investigate the changes in moisture, interspersed with a sequence of satellite images showing the location of the cross-section, C-C` (from WSW to ENE across DEN)

55. Visible image with LAPS 700 mb temp and wind and METARS
1500 UTC
Note the strong thermal gradient aloft from NW-S (snowing in southern WY) and the LL moisture gradient across eastern CO.

56. LAPS Analysis at 1500 UTC, Generated with Volume Browser

57. Visible image
1600 UTC

58. Visible image
1700 UTC

59. LAPS cross-section
1700 UTC

60. LAPS cross-section
1800 UTC

61. LAPS cross-section
1900 UTC

62. Case Study Example (cont.)
The cross-sections show some fairly substantial changes in mid-level RH. Some of this is related to LAPS diagnosis of clouds, but the other changes must be caused by the satellite moisture analysis between cloudy areas. It is not clear how believable some of these are in this case.

63. Case Study Example (cont.)
Another field that can be monitored with LAPS is helicity. A description of LAPS helicity is at
A storm motion is derived from the mean wind (sfc-300 mb) with an off mean wind motion determined by a vector addition of 0.15 x Shear vector, set to perpendicular to the mean storm motion
Next we’ll examine some helicity images for this case. Combining CAPE and minimum CIN with helicity agreed with the path of the supercell storm that produced the CO tornado.

64. NOWRAD with METARS and LAPS surface helicity
1900 UTC

65. NOWRAD with METARS and LAPS surface helicity
2000 UTC

66. NOWRAD with METARS and LAPS surface helicity
2100 UTC

67. NOWRAD with METARS and LAPS surface helicity
2200 UTC

68. NOWRAD with METARS and LAPS surface helicity
2300 UTC

69. Case Study Example (cont.)
Now we’ll show some other LAPS fields that might be useful (and some that might not…)

70. Divergence compares favorably with the RUC

71. The omega field has considerable detail (which is highly influenced by topography

72. LAPS Topography

73. Vorticity is a smooth field in LAPS

74. Comparison with the Eta does show some differences.
Are they real?

75. Stay Away from DivQ at 10 km

76. Why Run Models in the Weather Office?
Diagnose local weather features having mesoscale forcing
sea/mountain breezes
modulation of synoptic scale features
Take advantage of high resolution terrain data to downscale national model forecasts
orography is a data source!

77. Why Run Models in the Weather Office? (cont.)
Take advantage of unique local data
radar
surface mesonets
Have an NWP tool under local control for scheduled and special support
Take advantage of powerful/cheap computers

80. SFM forecast showing details of the orographic precipitation, as well as capturing the Longmont anticyclone flow on the plains

81. LAPS Summary You can see more about our local modeling efforts at
What else in the future? (hopefully a more complete input data stream to AWIPS LAPS analysis)

82. The End