Multi-Sensor Precipitation Estimator (MPE)
Transcript of Multi-Sensor Precipitation Estimator (MPE)
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Multi-sensor Precipitation Estimator (MPE)
Jennifer H. MaxwellColorado Basin River Forecast Center
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What Is MPE?
• MPE = multi-sensor precipitation estimator• “MPE’s focus is on areal estimations of
rainfall amounts based on both remotely sensed data (radar, and eventually satellite) and actual observations (rain gages).”
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Original Purpose
• The purpose of RFC-wide MPE is to create hourly gridded precipitation estimates which can be used to produce MAPX time series for input into NWSRFS
• MPE is intended to replace the stage2/ stage3 processing at River Forecast Centers
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History
• Stage III (still being used by several RFC’s)• Stand alone version of RFC_wide (now
called MPE) used at river forecast centers• HMAP_MPE as part of WHFS Hydroview
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MPE Primary Inputs/Outputs
• The primary inputs to MPE are the griddedDPA products and precipitation gage data.
• MPE creates hourly, gridded, multi-sensor precipitation estimates on a 4 km HRAP grid.
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MPE Capabilities
• Multi-radar mosaic according to the lowest available height above sea level
• Individual radar coverage maps determined by HDP/DPA climatology
• Mean field bias adjustment of raw radar estimates through multiple time scales
• Merging of rain gage and radar data
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MPE Capabilities Cont.
• Local bias adjustment which varies from grid point to grid point
• Use and display of PRISM data• Manual quality control of gage and radar
data (GUI)• Display and use of satellite-derived
precipitation estimates (build OB1?)
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Why Are We Using MPE?
• MPE creates a 1 hourly precipitation estimate that we can now feed into the model to support 1 hourly time segments
• Incorporates radar data• Can QC the data
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1 Hourly Time Segment Areas
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Radar Climatology
• Determination of “trusted” radar coverage– To compute radar-derived precipitation
climatologies we used:• Frequency of precipitation• Defined a threshold to be placed on the precipitation
estimates• Created different radar masks based on season and
latitude• Choose lowest available coverage
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Summer Radar Masks
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Fall/spring Radar Masks
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Displays in MPE
• Gridded precipitation products• Other Gridded fields • Tables • Radar masks
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Raw Radar (RMOSAIC)
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Bias Corrected Radar (BMOSAIC)
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Bias Table
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Local Bias (LMOSAIC)
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Bias Correction Factor (LOCBIAS)
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Memory Span (LOCSPAN)
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Gage Only
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Multi-sensor (MMOSAIC)
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XMRG (Saved Product)
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Height of Radar Coverage
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Prism Data
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Gage Table
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Single Radar Site
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Forecaster Input
• Ability to edit the gridded data fields as well as the point gage observations
• Provides tools to edit gage values, bias values, Z-R relationship values, and then rerun estimation algorithms
• The user can add a pseudo gage to adjust the radar values
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Forecaster Input
• There is also an edit precipitation capability which allows the user to draw a polygon around a region of interest. The user can then substitute any of the precipitation fields (RMOSAIC, BMOSAIC, MMOSAIC, LMOSAIC, SATELLITE) into the region outlined by the polygon.
• After a forecaster has finished analyzing and editing the precipitation data, the final analysis can be saved as an xmrg file for input into MAPX.
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Problems in the West
• Limited “trusted” radar coverage• Some areas with no gage/radar values• Gage radius of influence• Radar bias (i.e. RIW problems)• Satellite estimates not available yet• Adding our own estimates?
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Local Changes
• Increased radius of influence on gages• Changed precipitation amount for gage-
radar pairs (take fewer pairs to adjust radar bias)
• Modified radar coverage
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Documentation
• http://www.nws.noaa.gov/oh/hrl/presentations/mpe_training_wkshp_0601/course_outline.htm
• http://www.nws.noaa.gov/oh/hod_whfs