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Calibration of GOES-R ABI cloud products and TRMM/GPM observations to ground-based radar rainfall estimates for the MRMS system – Status and future plans. Heather Grams, Pierre Kirstetter CIMMS/NSSL, Norman, OK J.J. Gourley , Robert Rabin NOAA/NSSL, Norman, OK. - PowerPoint PPT Presentation
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Calibration of GOES-R ABI cloud products and TRMM/GPM
observations to ground-based radar rainfall estimates for the MRMS
system – Status and future plansHeather Grams, Pierre Kirstetter
CIMMS/NSSL, Norman, OK
J.J. Gourley, Robert RabinNOAA/NSSL, Norman, OK
2
146 WSR-88Ds 30 Canadian Radars
The Multi-Radar/Multi-Sensor System (MRMS)
QPE Products Instantaneous Precip Type/Rate Radar QPE (1 hr – 10-day accums) Gauge QPE Local gauge-adjusted radar QPE Gauge + orographic pcp climatology
QPE
Domain: 20-55°N, 130-60°W Resolution
0.01°lat x 0.01°long 2 min update cycle
~ 9000 hourly gauges~ 8000 daily gauges
Data Sources ~180 radars every 4-5min ~9000 gauges every hour RAP model hourly 3D analyses Satellite and lightning: optional
Operational at NCEP: 10/2014
3
Flooded Locations And Simulated Hydrographs (FLASH) A CONUS-wide flash-flood forecasting system – Operational at NCEP
2015
Stormscale Rainfall Observations (MRMS)
Stormscale Distributed Hydrologic Models
Probabilistic Forecast Return Periods and Estimated Impacts
10-11 June 2010, Albert Pike Rec Area, Arkansas
10”8”6”
Hydrograph of Simulated and Observed Discharge
Simulated surface water flow
20 fatalities
80%
60%40%
Probability of life-threatening flash flood
t=2300
t=0000t=0100
Q2
Q5
5 hr
4
5
Winter Summer
6
Impact of missing data on calibration
7
Filling Gaps with Satellite QPE?
Renewed Opportunity with GOES-R Spatiotemporal resolution improvements for flash
flood scale 15 min 5 min over CONUS 4 km 2 km for ABI-derived products
Geostationary Lightning Mapper Convective/Stratiform Precip Type Segregation in data-
sparse areas
Expanded list of cloud properties from ABI: Cloud top height, temperature, phase, pressure;
emissivity, effective radius, optical depth, etc.
~ MRMS scale
MRMS Calibrated GOES-R/TRMM Rainfall
Complementary Observing Systems
Geostationary Satellites (GOES)
TRMM/GPM PR
MRMS mosaic of ground radars + environment + gauges
Advantages of GOES/GOES-R:• Rapidly updating (5-15
minutes)• Full CONUS coverage and
beyond
Advantages of TRMM/GPM:• Fine-scale vertical profiles
through cloud to surface• PR products
complementary to NEXRAD
Advantages of MRMS:• Near-surface
observations• High spatiotemporal
resolution• Precip/No Precip QC
9
GOES Inputs: Derived cloud properties
GOES-13 Proxy of GOES-R ABI cloud products (parallax-corrected)
Cloud Top Height/Temperature/Pressure
Cloud Top Phase Cloud Top Emissivity Optical Depth/Effective Radius
(daytime only)
Geostationary Lightning Mapper Convective/Stratiform Precip Type
Segregation in data-sparse areas TRMM LIS available for training
period
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MRMS Inputs: Near-surface rainfall properties
Surface precipitation • Rainfall Rate• Precipitation Type
(conv/strat/tropical/hail/snow/BB)
• Radar Quality Index• Quality Control of
Precip/No-Precip
3-D Reflectivity Mosaic• Vertical Profiles of
Reflectivity
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TRMM/GPM Inputs: Vertical structure of precipitation
TRMM Precipitation Radar • 2A25 Version 7 vertical
profiles of attenuation-corrected reflectivity factor
• Rain Type
GPM Dual-Frequency Radar• Full CONUS coverage• Better characterization of
particle size distributions and precipitation phase
Lightning Imaging Sensor• Identification of convective
rainfall
(Photo Credit: JAXA/NASA)
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MRMS Calibrated GOES-R/TRMM Rainfall
• Preprocessing of Datasetsa. Remap all inputs to GOES resolution b. Derive S-band-like vertical profiles of reflectivity
from Ku-band TRMM PR (Wen et al. 2013)c. Filter by precip type and
NEXRAD coverage quality
• Develop Rainfall Modela. Two versions: TRMM
and no-TRMMb. Joint-PDF Bayesian approach
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Current Status and Future PlansYear 1: Current work (June 2014)
a. Build training archive (1 year initially, up to 3 years available)b. Database entries of all inputs matched to GOES pixel resolution
and scan time• TRMM pass within 1 hour of GOES scan time• MRMS rain rate >= 10 mm hr-1
• Radar Quality Index = 1
GOES-RProxyVariables
TRMMPR
MRMSMatchedPixels
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Current Status and Future PlansYear 2: Product development and MRMS integration
a. Dec 2014: Prototype CONUS precipitation rates and typesb. Feb 2015: Merge satellite-based rainfall products with
MRMS ground-based QPE (RQI-based weighting scheme)
Radar Quality Index 10
NEXRAD QPE
SatelliteQPE
1
Wei
ght
15
Current Status and Future PlansYear 3: Validation and FLASH integration
a. Evaluate model QPE performance (both with TRMM/GPM and without)
b. Test blended MRMS QPE+satellite QPE as input to FLASH in real-time
c. After GOES-R launch, adjust model to use real-time GOES-R input (ABI and GLM)
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Thank you! Contact: Heather Grams ([email protected]
)
For more info: http://mrms.ou.edu http://flash.ou.edu