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Improvements to QPE using GOES visible ABI and model data PIs: Robert Rabin, Jian Zhang: NOAA/NSSL Bob Kuligowski: NOAA/NESDIS/STAR Objective: Improvements to ScaMPR ( Self-Calibrating Multivariate Precipitation Retrieval): The GOES-R Rainfall algorithm

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slide1

Improvements to QPE using GOES visible ABI

  • and model data
  • PIs:
  • Robert Rabin, Jian Zhang: NOAA/NSSL
  • Bob Kuligowski: NOAA/NESDIS/STAR
  • Objective:
  • Improvements to ScaMPR (Self-Calibrating Multivariate Precipitation Retrieval):
  • The GOES-R Rainfall algorithm
  • High resolution visible cloud structure
  • Cloud-top phase and particle size derived from GOES imagery
  • NWP model data
slide2

Milestones: Year 1

  • Obtain SCaMPR software and modify for introduction of new

variables.

  • Collect initial case studies (current GOES and NMQ; SEVIRI

and NIMROD data).

  • Perform enhanced analysis of visible cloud structure for

input to SCaMPR

  • Extract archived cloud-model output and simulated imagery.
  • Perform statistical analysis of added value of new parameters

with SCaMPR.

  • Compare results with observed and simulated GOES data.
slide3

Milestones: Year 2:

  • Extend the analysis completed in year 1 to independent cases

for further testing of SCaMPR.

  • Setup real time processing of with current GOES data for

evaluation of QPE accuracy in site specific areas such as

the Tar basin of North Carolina.

  • Document and submit results for publication
slide4

Use of visible and NSSL-WRF stats in QPE: 24 Aug 22:45 UTC

WRF: Visible

WRF:IR Band 13

WRF: Rain Rate (R)

-40 -60C

10 20 30 40 50/hr

G13: Vis

G13: IR Band 4

R: WRF stats

50 75 100%

-40 -60C

G13: Overshoot probability

R: WRF+overshoot stats

R: radar NMQ

10 20 30 40 50/hr

10 20 30 40 50/hr

10 20 30 40 50/hr

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