Transcript Updated_RTMA_+_RUA_Review_2013

Real-Time Mesoscale Analysis Review
and Plans for Rapid Updating Analysis
Jason Levit
NOAA NextGen Weather Program
June, 2013
Agenda
•RTMA Evolution: 2006  Today
– Drivers for RTMA
– Background
– Development Organization
– Analysis Domains and Resolution
– RTMA Techniques
•Plans for Near Term Enhancements to RTMA
•Plans for Long Term Transition to Rapid Updating Analysis
•Characteristics of the Multiple-Radar Multiple-Sensor project
•Discussion
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RTMA 2006 - Today
Drivers for RTMA Development:
•Verification of NDFD forecasts
•Initialization of gridded forecasts at
Weather Forecast Offices
•Situational awareness for sensible weather
Background:
•Requirements defined in OSIP
•Initial analyses for CONUS in 2006
•OCONUS analyses added in 2008
•Official NWS product in 2011
•NextGen Program funding in FYs 2010
and 2011
Development Organizations:
•NCEP, Environmental Modeling Center
•Geoff DiMego, Federal Manager
•Manuel Pondeca, Developer
•Steve Levine, Developer
•Yanqiu Zhu, Developer
•Stan Benjamin, ESRL/GSD, Developer
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Analyses + Resolution + Domains
Analyses:
•Wind Speed and Direction
•Temperature
•Dew Point Temperature
•Surface Pressure
•Effective Cloud Amount –
(remapped GOES by NESDIS)
•Accumulated precipitation
(remapped Stage 2 by Ying Lin)
Analysis Uncertainty:
•Temperature
•Dew Point Temperature
•Wind Speed
•Wind Direction
Cross-validation:
•A subset of observations are withheld
•Scores computed for each analysis
Model Terrain:
•Fixed field
Hourly Domains:
•CONUS (5 and 2.5 km)
•Hawaii (2.5 km)
•Alaska (6 km)
•Puerto Rico (2.5km)
3 hourly Domain:
•Guam (2.5km)
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RTMA Techniques
Analysis Generation:
• First Guess obtained from Rapid Refresh downscaled to NDFD domain
• First Guess at the Appropriate Time (FGAT)
• Terrain following background error covariance
• Gridded Statistical Interpolation (GSI) used in Two Dimensional Variation (2D Var)
mode
• Observations from Meteorological Assimilation Data Ingest System (MADIS):
– Satellite derived winds
– ASOS – METAR
– Mesonet
– Buoy, ship, tide gage and Coastal-Marine Automated Network (CMAN)
– Approximately 15,000 observations used per analysis
• Quality control of observations beyond that done in MADIS:
– Gross error check
– Predefined reject list of sites from WFOs
– Reject selected mesonet winds
Cross-Validation
- Make multiple disjoint datasets for each ob type, each containing
about 10% of the data. Datasets contain representative data from
all the geographical regions observed but without the redundancy
of close pairs or tight clusters
-For each analysis, randomly pick one of the disjoint datasets to
use for cross-validation
PARALLEL RTMA CONUS-2.5 km
PARALLEL RTMA CONUS-2.5 km
Note:
Analyzed
at the 10-m
level
PARALLEL RTMA CONUS-2.5 km
RTMA Enhancements Planned 2013
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3 km Analysis upgrade for
Alaska
1.5 KM Analysis domain for
Juneau
2.5 km Analyses for
Northwest RFC domain
Science and quality control
technique improvements:
– Improved handling of
snowpack in RAP
– Winds from Hurricane
WRF added to improve
analyses of tropical
cyclones
New analysis variables:
– Wind gusts
– Visibility
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Next Steps for RTMA Development
Explore potential for additional
Aviation impact analysis variables:
•Total cloud cover
•Cloud base heights
•Mean sea level pressure
Continue to enhance quality control
of observations:
• Real-time monitoring system
• Real-time data mining
• Add metadata into GSI
• Improved Land sea mask
Delayed Mesoscale Analysis:
•Run 4 hours after RTMA
•Collects more complete set of
observations
•Improved product verification
•RTMA will continue to be available
•Enables transition to Analysis of
Record capability
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Transition to Rapid Updating Analysis
Rapid Updating Analysis (RUA)
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Benefits:
– Enhance forecaster situational awareness
– Enable issuance of warnings and forecasts with greater lead time and accuracy
– Provide a more accurate data set for model and forecast verification
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Concepts:
– Updated every five minutes
– 1km horizontal resolution
– Expands coverage to atmosphere
– Uses satellite, radar and soundings (aircraft, etc.)
– Phased Implementation: Use the MRMS in the initial phase and then moving to a GSI-based system
– Multiple-Radar-Multiple-Sensor (MRMS) system serves as the initial backbone
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VIL
Vertical wind shear
Precipitating species (hail)
Lightning
Reflectivity and radar quality
(see spreadsheet for list of variables)
– Products will execute on NCEP mainframe
At full capability, will generate the most state-of-the-art analyses of the atmosphere currently possible, with
the best scientific techniques
RUA data will serve as both a real-time analysis and eventually as initialization for high resolution models
for Warn-on-Forecast applications
Utilizes the GSI framework for code compatibility across NOAA
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What is MRMS?
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MRMS = Multiple-Radar / Multiple-Sensor
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Multi-Radar: Exploits the overlapping
coverage of the WSR-88D network and the
Level-II real-time data feeds to build a
seamless rapidly-updating high-resolution
three-dimensional cube of radar data.
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Multi-Sensor: Objectively blends data from
the multiple-radar 3D cubes with surface,
upper air, lightning, satellite, rain gauges, and
NWP environmental data, to produce highlyrobust decision assistance products.
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Improvements demonstrated in QPE, severe
weather diagnosis, warning decision efficiency,
NWP, etc.
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MRMS
MRMS Outputs
• 3D Reflectivity
CONUS cube
• 3D Azimuthal
Shear CONUS
cube
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MRMS