Development of a Local
Analysis System over Highly Variable Terrain
Steven Lazarus, Carol Ciliberti, and John Horel
NOAA Cooperative Institute for Regional Prediction
University of Utah
The Utah Arps Data Assimilation
System (ADAS)
Based on the Oklahoma
ARPS (Advanced Regional Prediction System) Data Assimilation System
- Developed by the Center for Analysis and Prediction of
Storms (CAPS)
Project Goals:
- Obtain real-time, high resolution analyses over complex
terrain
- Assist in local weather forecasting
Description of the Utah ADAS
3-Dimensional
mesoscale analysis system
220x220
km domain
2
km horizontal resolution
Stretched
vertical coordinate
Run
at one-hour intervals
Analyses
run in two parts
- temperature, relative humidity,
pressure and wind analysis
- cloud analysis
Data Used in the Analyses
Main
Analysis:
- RUC2 analysis used for initial
background field
- Regression data replaces T, Td
at first model level
- Surface obs from Utah mesonet
- NWS rawinsonde at 0 and 12 UTC
- NWS WSR-88D velocity and reflectivity
data
Cloud
Analysis
- 3-D background field from ADAS
RH analysis
- Option to use METAR data
- Visible and Infrared satellite
imagery
- Radar reflectivities
ADAS Features
Bratseth Interpolation
Scheme
- Successive correction technique
- Accounts for background-to-observation
error
- Generally insensitive to observation
density
Automated
Quality Control
New
Vertical Weighting Added to Analysis
Future Goals
Incorporate Additional
Data Sources
- Satellite sounder data
- Dugway Proving Grounds wind profiler
data
- ACARS data
- FAA radar data
Implement
Linear Regression Q-C Flags
Experiment
with domain size and resolution
Use
ADAS to initialize ARPS
- short term, high resolution forecasts
Products Available
http://www.met.utah.edu/jhorel/mesonet/data.html
Utah
ADAS Information
http://www.met.utah.edu/jhorel/html/adas/info/information.html
Conference
Papers:
Application
of a Local Data Analysis System in Highly Variable Terrain.