Local Analysis and Prediction System

Paul Schultz

June 10, 1999

LAPSA 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

Basic data sources

• Radar

• Satellite

• Surface Obs

• RAOBs

• Profilers

• ACARS

• Larger-scale models (background, LBC)

We’ll emphasize LAPS in NWS AWIPS today...

…but LAPS is being used by Space Flight Centers (Vandenburg,

Kennedy), USAF Global Weather Center, many others

Here’s how it looks on AWIPS

Relationship between NWS and FSL

N ation a l W eath erS ervice

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N O A A

“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 DATA TO BE INTEGRATED INTO 3-DIMENSIONAL DEPICTIONS OF THE RAPIDLY CHANGING STATE OF THE ENVIRONMENT.”

-- from the strategic plan for the modernization and associated restructuring of the National Weather Service

A decade of NWS development

• All new satellites, radars, surface observation equipment

• Satellite-based telecommunications to support field offices

• Cool computer workstations (AWIPS)• New telecommunications front end to support

users (LDAD)• New forecast products and services

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Basic AWIPS setup

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Observing platforms

Spotters, coop observers

Public schools, police cars

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ExistingRouter

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Hydro nets, roadsensors, agriculturemesonets

LDAD in NWS Forecast OfficesLDAD in NWS Forecast Offices

LAPS on AWIPS

• Analysis only (for now).• Domain is (for now) at 61x61x21,

dx=dy=10km, dp=50mb. Cycle time is 1 hr.• 3d temperature, wind, humidity, cloud

fraction, mixing ratios of vapor, cloud liquid, cloud ice, rain, snow, graupel.

• Lots of derived fields.

Data sources for LAPS in AWIPS

• RUC provides first guess• Surface: metars, buoys, satellite IR for T, local

obs via LDAD (v4.2)• Upper winds: profiler (not ACARS, WSR88D)• Clouds: WSR88D reflectivity, satellite IR+vis,

metars (not pireps, radiometers)• Water vapor: cloud fields + 11.7 (not ACARS,

radiometers, GPS)

Why Run Models in the Weather Office?

• Diagnose local weather features to enhance conceptual models– 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

• Best reason: better precip forecasts

Why Run Models in the Weather Office? (cont.)

Threat scores for 24-hr precip forecasts

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Bias scores of 24-hr precip forecasts

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Why not run models in NWS forecast offices?

• NWS hasn’t figured out how to support modeling.

• NWS/NCEP/EMC is not convinced it will provide useful guidance or otherwise lead to better forecasts.

• NWS/NCEP/EMC believes AWIPS telecomms will eventually catch up.

• NWS and PRC haven’t negotiated the infrastructure management.

• Hardware cost is not an issue.

Hardware cost is not an issue!

The computer required to run a nested grid with an interior 5-km grid covering WFO area of responsibility plus plenty more, costs less than $5000 today! (Based on an assumed requirement to complete a 27-hr forecast in under three hours.)

Which model?

• Practically any public-domain nestable nonhydrostatic model is fine (MM5, COAMPS, ARPS, SFM).

• Eta okay too, but it’s not nestable, so a larger fine grid is required; offsets efficiency advantage.

• No technical reason not to have them all.

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AWIPS local model implementation options

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Here’s how it looks on AWIPS ------>

Same grid as analyses

LBC from Eta

Runs four times out to 18 hrs per day at WFO/BOU

Runs automatically, >95% reliability

Cloud liquid

Cloud ice

Snow

Graupel

Rain

precipsaturated updraft

freeze/melt

coalescence

melting

freeze/melt

nucleation

depositionaggregation

precip precip precip

NWP Explicit Microphysics

Evaporation is not shown

accretion

Plans

• Better integration of surface and 3D fields• Direct assimilation methods of satellite radiances,

microwave sensors, radar reflectivity• Hot start for model• Shallow cumulus parameterization• Graphical user interface for grid configuration,

data quality control, process monitoring, verification

LAPS People

• Steve Albers: 3d winds, temperature, clouds• Pete Stamus: surface analyzed and derived

products• Dan Birkenheuer: 3d humidity• John Smart: data ingest, preprocessing• Jim Edwards: software design• John McGinley: variational methods, QC• Paul Schultz, John Snook: local model

Here’s our web site:

http://laps.fsl.noaa.gov

Email anybody in the group:

lastname@fsl.noaa.gov

John McGinley, LAPS Branch Chief, FSL

Paul Schultz, AWIPS contact