Precipitation Estimates and the National Mosaic and QPE (NMQ)
An accurate analysis of the amount of precipitation that has fallen
from a tropical cyclone is extremely important to forecasters. The amount of
precipitation is a critical factor in determining the likelihood of
flash flooding and eventual river flooding. Because flooding is typically a
result of significant precipitation over an area such as a river or stream basin,
relying on point observations of precipitation (rain gauges) only provides
a portion of the needed information. The estimation of the amount of
precipitation that has fallen is often referred to as Quantitative Precipitation
Estimation or QPE. Studies have shown that algorithms which combine sensor inputs
such as radar, gauge, and satellite yield more accurate precipitation estimates
than those which rely on a single sensor. Recent advances in QPE integrates radar data with
other data sources such as rain gauges and satellite information in a
process called Muti-sensor Precipitation Estimation or MPE.
In February 2000, the National Severe Storms Laboratory (NSSL), National Sea Grant (NSG) College Program,
University of Oklahoma, North Carolina State University (NCSU), and the North and South Carolina
Sea Grant programs established a joint project, centered in North Carolina areas affected by Hurricane Floyd.
The original collaborators were later joined by the National Weather Service Office of Hydrologic
Development and the National Environmental Satellite, Data and Information Service (NESDIS). The
primary demonstration area was the Tar-Pamlico River basin. This project, called
CI-FLOW, has established
a research and demonstration program for the evaluation and testing of new technologies and techniques to
produce accurate and timely identification of inland and coastal floods and flash floods. CI-FLOW
leverages scientific expertise from three ongoing NOAA research activities namely the
NSSL NMQ/Q2, the NWS/OHD MPE/EMPE program,
and the NESDIS HydroEstimator program.
The National Mosaic
and QPE (NMQ) Web Page provides real
time evaluation and display of experimental techniques and applications
used for high resolution 3D mosaics of radar reflectivity data and QPE.
The NMQ serves as a test bed for research, development, and
evaluation of data and methods for
the monitoring and warnings of floods and flash floods and in support
of comprehensive hydrology and ecosystem modeling.
There are 4 major components of the NMQ system:
Data ingest
Products
Analysis tools
Verification
The NMQ system ingests data from a number of sensors and products from various sources:
128 WSR-88D radars (5 min)
Gauge data set that includes 5500 gauges from many different networks (hourly)
Satellite IR images (15 min)
Rapid Update Cycle 20 km resolution (RUC) model analysis variables (hourly)
NWS Hydro Estimator (satellite-based) precipitation (hourly)
NWS Stage IV precipitation (1, 6, and 24 hour)
Data and processing flow:
Ingest all data (they arrive at different rates)
Quality control radar data
Derive vertical profile of reflectivity from each radar
Analyze radar data to 8 tiles and stitch the tiles together to form the CONUS 3D grid (1 km x 1 km x 31 levels
Derive hybrid scan reflectivity and other products
Produce experimental Q2 products
Use gauges to validate Q2 and other products
Comparison of QPE Products
QPE products for the same 24 hour period ending at 12 UTC on 08/28/2008 are shown below. The
various QPE products provide a slightly different analysis but the most detailed and most
representative analysis is produced by the Local gauge corrected radar QPE product otherwise
known as the Q2RAD_HSR_GC.
Q2GAUGE
The Q2GAUGE is gauge-only precipitation analysis that uses a local
gauge correction scheme based on an inverse distance weighted (IDW) mean scheme. The
two parameters in the IDW scheme, exponent and radius of influence, are determined through
a cross-validation procedure. The interpolated gauge bias field is used to create
the Q2GAUGE product.
HYDRO_EST
The HYDRO_EST is a
NWS operational satellite precipitation hydroestimator product.
Precipitation rates are primarily based on the
cloud top temperature obtained from GOES 12 and GOES 10 (10.7 micron). Instantaneous, 1 hour,
3 hour, 6 hour, and 24 hour precipitation estimates are available. Numerous other factors,
including the cloud-top geometry, the available atmospheric moisture, stability parameters,
radar, and local topography, are used to further adjust the rain rate.
STAGE4
STAGE4 data is based on operational 24 hour NWS Stage IV hourly and 24-hr precipitation
analyses from NCEP. Stage IV is a final stage term used to describe nationwide mosaicing
of manually-edited, regional MPE products produced by each of River Forecast Center (RFC) on
an hourly basis. Stage IV is a readily available operational product (real time Stage IV data for North Carolina).
Q2RAD_HSR
The Q2RAD_HSR is a radar-based precipitation rate and accumulation product with data
available over various time periods. The rate is derived from the
hybrid scan reflectivity (HSR) using convective, stratiform and
tropical Z-R relations.
Q2RAD_HSR_GC
The Q2RAD_HSR_GC is a local gauge corrected radar QPE field. The local gauge correction is applied onto the
one hour Q2RAD_HSR precipitation field. It runs hourly and uses hourly rain gauge observations
from the HADS (Hydrometeorological Automated Data System) data sets at NCEP. In the local
gauge correction scheme, radar-gauge biases are calculated at each gauge site and then
interpolated onto the NMQ grid using an inverse distance weighted (IDW) mean scheme. The
two parameters in the IDW scheme, exponent and radius of influence, are determined through
a cross-validation procedure. The interpolated radar-gauge bias field is applied back to
the Q2RAD_HSR one hour precipitation field and a local gauge bias corrected one hour precipitation
field is obtained. Longer-term accumulations are computed by aggregating the one hour local
gauge corrected precipitation fields.
KRAX Precipitation Estimate
The krax precipitation estimate is a radar-based precipitation accumulation
produced at the RPG. The precipitation estimate is derived from the Hybrid Scan Reflectivity
(HSR) product from the Enhanced Precipitation Preprocessing (EPRE) algorithm using a
specific Z-R relationship. The image below is the product from the KRAX RDA displayed
in AWIPS (click on the image to enlarge.)
Comparison of the local gauge corrected radar QPE product with the Stage IV QPE product
The local gauge corrected radar QPE product or Q2RAD_HSR_GC generally provided the most
accurate and detailed analysis of the precipitation associated with the remnants of
tropical storm Fay. The comparison below shows the
local gauge corrected radar QPE product from the NMQ web site with the
Stage IV QPE product from the NWS AHPS web site for the 24 hour period ending
at 12 UTC 08/28/08 (click on the image to enlarge).
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