using laps as a cwb nowcasting tool by steve albers december 2002

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

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

http://laps.fsl.noaa.gov/presentations/presentations.html

http://laps.fsl.noaa.gov/presentations/presentations.html

The End

Taiwan Short Term Forecast System

LAPS (Local Analysis and Prediction System)

Diabatic Initialization technique

Hot-Start MM5

http://www.cwb.gov.tw/index.html

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


1700 UTC


1800 UTC


2100 UTC


• 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


• 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.


• 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


2000 UTC


2100 UTC


2200 UTC


2300 UTC


• 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

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

using laps as a cwb nowcasting tool by steve albers december 2002

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