Using LAPS as a CWB Nowcasting Tool
By
Steve Albers
December 2002
Local Analysis and Prediction System (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
LAPS Flow Diagram
CWB LAPS Grid
• LAPS Analysis Grid – Hourly Time Cycle– Horizontal Resolution = 5 km– Vertical Resolution = 50 mb– Size: 199 x 247 x 21
Data Acquisition and Quality Control
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.
LAPS Data Sources
LAPS Surface Analysis
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
Standard Deviation Check
• Compute Standard Deviation of observations-background
• Remove outliers
• Now adjustable via namelist
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
Kalman QC Scheme
Sfc T
CAPE
3-D Temperature
• First guess from background model • 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 Mesonets (LDAD)
Successive correction analysis strategy
• 3-D weighting– Successive correction with Barnes weighting
– Distance weight e-(d/r)2 applied in 3-dimensions– Instrument error reflected in observation weight
• Wo = e-(d/r)2 / erro2
– Each analysis iteration becomes the background for the next iteration
– Decreasing radius of influence (r) with each iteration– Each iteration improves fit and adds finer scale structure– Works well with strongly clustered observations– Iterations stop when fine scale structure & fit to obs become
commensurate with observation spacing and instrument error
Successive correction analysis strategy (cont)
• Smooth blending with Background First Guess– Background subtracted to yield observation
increments (uo)– Background (with zero increment) has weight at each
grid point– Background weight proportional to inverse square of
estimated error• wb = 1 / errb
2
– For each iteration, analyzed increment (u) is as follows:
• ui,j,k = (uowo) / ( (w o )+ wb )
X-sectT / Wind
LAPS Wind Analysis
Products Derived from Wind Analysis
Doppler and Other Wind Obs
LAPS radar ingest
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
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
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
Horizontal Filter/Analysis Before After
Radar Mosaic
LAPS cloud analysis
METARMETAR
METAR
CloudSchematic
Cloud Isosurfaces
3-D Clouds
• Preliminary analysis from vertical “soundings” derived from METARS, PIREPS, and CO2 Slicing
• IR used to determine cloud top (using temperature field)
• Radar data inserted (3-D if available)
• Visible satellite can be used
Cloud Analysis Flow Chart
Cloud & Radar X-sect (Taiwan)
Cloud & Radar X-sect (wide/narrow band)
Derived cloud products flow chart
Cloud/Satellite Analysis Data
• 11 micron IR
• 3.9 micron data
• Visible (with terrain albedo)
• CO2-Slicing method (cloud-top pressure)
Visible Satellite Impact
Cloud Coverage without/with visible data
No vis data With vis data
Storm-Total Precipitation (wideband mosaic)
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
LAPS 3-D Water Vapor (Specific Humidity) Analysis [continued]
• 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 700-500 hPa, and above 500
• Saturates where there are analyzed clouds
• Performs final QC against supersaturation
Adjustments to cloud and moisture scheme
Originally cloud water and ice estimated from Smith-Feddes parcel Model – this tended to produce too much moisture and ice
Adjustments:1. Scale vertical motion by diagnosed cloud amount, extend below
cloud base2. Reduced cloud liquid consistent with 10% supersaturation of
diagnosed water vapor and autoconversion rates from Schultz
Cloud vertical motions
Balance scheme tuned
Proposed Tasks for IA#15
• Transfer existing LAPS/MM5 Hot-Start system to CWB– LAPS build on LINUX
• Expand satellite and radar data used for cloud diagnosis – Adapt to GOES 9 (visible + 3.9 micron)– Radar data compression needed?
• CWB/NFS as background• Continued tuning for tropics• Add thermodynamic constraint to balance package to
correct for bad background fields• Add a verification package to the LAPS/MM5 system –
State variables and QPF• Continue regular upgrades CWB software
Sources of LAPS Information
• The Taiwan LAPS homepage– http://laps.fsl.noaa.gov/taiwan/taiwan_home.html
LAPS analysis discussions are near the bottom of:http://laps.fsl.noaa.gov/presentations/presentations.html
Especially noteworthy are the links for
• Satellite Meteorology• Analyses: Temperature, Wind, and
Clouds/Precip.• Modeling and Visualization
– A Collection of Case Studies
Analysis Information
The End
Taiwan Short Term Forecast System
LAPS (Local Analysis and Prediction System)
Diabatic Initialization technique
Hot-Start MM5
Forecast domains & Computational requirement
D02D03
D01
1km (169*151)
D02
D01
1368 km ( 153 points)
1260
km
( 1
41 p
oint
s)
151
pts
151 pts
9km
3km
CPUs 42 compaq 833 MHz
Need 1.5hrs for 24hrs fcst
0.000.050.100.150.20
0.400.350.300.25
0.710.680.650.620.580.540.500.45
0.920.900.880.860.830.800.770.74
0.990.980.970.960.94
1.00
30 V
erti
cal l
ayer
s (σ
leve
ls)
CWB Hot-Start MM5 Model Configuration
Domain1 Domain2
Grid-points 153*141*30 151*151*30
Horizontal Resolution
9 km 3 km
Time-Step 27 secs 9 secs
Nesting Two-way feedback between nests
Lateral B.C.
Relaxation/inflow-outflow (from CWB/NFS)
Lower B.C. Daily SST and LAPS surface analysis
Upper B.C. Upper Radiative Condition
CWB Hot-Start MM5 Model Physics
Initial Field From LAPS and Diabatic Initialization
Microphysics Schultz scheme
PBL scheme MRF PBL
Surface scheme 5-layer Soil Model
Radiation RRTM scheme
Shallow Convection
YES
Cumulus Parameterization
NO
Kalman Flow Chart
Cloud Coverage without/with visible data
No vis data With vis data
Case Study Example
An example of the use of LAPS in convective event
14 May 1999
Location: DEN-BOU WFO
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.
NOWRAD and METARS with LAPS surface CAPE
2100 UTC
NOWRAD and METARS with LAPS surface CIN
2100 UTC
Dewpoint max appears near CAPE max, but between METARS
2100 UTC
Examine soundings near CAPE max at points B, E and F
2100 UTC
Soundings near CAPE max at B, E and F
2100 UTC
RUC also has dewpoint max near point E
2100 UTC
LAPS & RUC sounding comparison at point E (CAPE Max)
2100 UTC
CAPE Maximum persists in same area
2200 UTC
CIN minimum in area of CAPE max
2200 UTC
Point E, CAPE has increased to 2674 J/kg
2200 UTC
Convergence and Equivalent Potential Temperature are co-located
2100 UTC
How does LAPS sfc divergence compare to that of the RUC?
Similar over the plains.
2100 UTC
LAPS winds every 10 km, RUC winds every 80 km
2100 UTC
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?
LAPS sounding near LBF
1600 UTC
LAPS sounding near LBF
1700 UTC
LAPS sounding near LBF
1800 UTC
LAPS sounding near LBF
2100 UTC
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)
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.
LAPS Analysis at 1500 UTC, Generated with Volume Browser
Visible image
1600 UTC
Visible image
1700 UTC
LAPS cross-section
1700 UTC
LAPS cross-section
1800 UTC
LAPS cross-section
1900 UTC
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.
Case Study Example (cont.)
• Another field that can be monitored with LAPS is helicity. A description of LAPS helicity is at http://laps.fsl.noaa.gov/frd/laps/LAPB/AWIPS_WFO_page.htm
• 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.
NOWRAD with METARS and LAPS surface helicity
1900 UTC
NOWRAD with METARS and LAPS surface helicity
2000 UTC
NOWRAD with METARS and LAPS surface helicity
2100 UTC
NOWRAD with METARS and LAPS surface helicity
2200 UTC
NOWRAD with METARS and LAPS surface helicity
2300 UTC
Case Study Example (cont.)
• Now we’ll show some other LAPS fields that might be useful (and some that might not…)
Divergence compares favorably with the RUC
The omega field has considerable detail (which is highly influenced by topography
LAPS Topography
Vorticity is a smooth field in LAPS
Comparison with the Eta does show some differences.
Are they real?
Stay Away from DivQ at 10 km
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!
• 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
Why Run Models in the Weather Office? (cont.)
SFM forecast showing details of the orographic precipitation, as well as capturing the Longmont anticyclone flow on the plains
• You can see more about our local modeling efforts at
http://laps.fsl.noaa.gov/szoke/lapsreview/start.html
• What else in the future? (hopefully a more complete input data stream to AWIPS LAPS analysis)
LAPS Summary
Reflectivity (800 hPa)
Derived products flow chart
Cloud/precip cross section
Precip type and snow cover
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– Reflectivity limit helps reduce bright band effect
Storm-Total Precipitation
Storm-Total Precipitation (RCWF narrowband)
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
• Continue adding multiple radars and radar types– Evaluate Ground Clutter / AP rejection
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)
Gauge Radar Analysis
Gauge Radar Analysis
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.
The End
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?
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
Cloud type diagnosis
Cloud type is derived as a function of temperature and stability
LAPS data ingest strategy
Dummy Image