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GOES-R AWG Hydrology Algorithm Team: Rainfall Potential June 14, 2011

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GOES-R AWG Hydrology Algorithm Team: Rainfall Potential June 14, 2011 Presented By: Bob Kuligowski NOAA/NESDIS/STAR* – PowerPoint PPT presentation

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Title: GOES-R AWG Hydrology Algorithm Team: Rainfall Potential June 14, 2011


1
GOES-R AWG Hydrology Algorithm Team Rainfall
Potential June 14, 2011
Presented By Bob Kuligowski NOAA/NESDIS/STAR
2
Outline
  • Executive Summary
  • Algorithm Description
  • ADEB and IVV Response Summary
  • Requirements Specification Evolution
  • Validation Strategy
  • Validation Results
  • Summary

3
Executive Summary
  • This Rainfall Potential Algorithm generates the
    Option 2 product of predicted rainfall
    accumulation for the next 3 h on the ABI grid.
  • The NOAA / NSSL K-Means algorithm has been
    adapted to produce extrapolation-based forecasts
    of rainfall from the current and previous GOES-R
    Rainfall Rate fields.
  • Version 3 (80) was delivered in September 2010.
    Version 5 (100) delivery has been delayed 12
    months in response to GPO guidance.
  • Preliminary validation of the version 3 algorithm
    has been performed against 20 days of SEVIRI
    data from 2005.
  • Validation against Nimrod radar indicates spec
    compliance.

4
  • Algorithm Description

5
Algorithm Description
  • This Rainfall Potential Algorithm generates the
    Option 2 product of predicted rainfall
    accumulation for the next 3 h on the ABI grid
    using the NOAA / NSSL K-Means algorithm.
  • Rainfall is extrapolated based on a comparison of
    current and previous Rainfall Rate imagery
  • ONLY motion is extrapolated (no growth / decay)
  • No initiation in an extrapolation-based approach
  • Three basic algorithm components
  • Identify features in rain rate imagery
  • Determine motion between features in consecutive
    images
  • Apply motion vectors to create rainfall nowcasts

6
Motivation for Algorithm Selection
  • In 2007 the Hydrology AT compared the results
    from 4 different experimental real-time rainfall
    forecasting algorithms
  • Hydro-Nowcaster (NESDIS / STAR)
  • K-Means (NOAA / NSSL)
  • TITAN (UCAR)
  • MAPLE (McGill University)
  • MAPLE gave the best results but licensing issues
    could not be resolved K-Means (second-base
    performer) was selected instead.

7
Example Rainfall Potential Output
Rainfall Potential from 1500-1800 UTC 8 July 2005
derived from Rainfall Rate fields (retrieved from
SEVIRI data) at 1445 and 1500 UTC.
8
ADEB and IVV Response Summary
  • ADEB did not recommend advancing to 100, stating
    the algorithm needs more validation and
    reconsideration of the choice of algorithm.
  • As a result, the algorithm development schedule
    has been delayed by 12 months.
  • Regarding reconsideration of the choice of
    algorithm, the AT responded that the algorithm
    selection process was well-documented and that
    validation has been made difficult by the paucity
    of validation data. The AT also requested
    clarification on these comments.

9
ADEB and IVV Response Summary
  • Regarding the algorithm needs more validation,
    high-quality rainfall data at time scales of 3 h
    or less have been extremely difficult to find.
    Planned solutions
  • CHUVA (Brazil) field campaign data
  • Global Precipitation Climatology Center (GPCC)
    gauge data (can only be used in-housevisit in
    summer 2012?)
  • EUMETSAT Hydrology SAFreaching out to see if
    their data (also in-house only) could be used via
    a visit.
  • In response to a phone request, the AT also
    surveyed users from OSPO/SAB, NWS/HPC, NWS/OHD,
    and NWS/WGRFC and found significant interest in
    the product and for it to be available at launch.

10
Requirements Specification Evolution
Name User Priority Geographic Coverage (G, H, C, M) Vertical Resolution Horizontal Resolution Mapping Accuracy Measurement Range Measurement Accuracy Product Refresh Rate / Coverage Time (Mode 3) Refreshment Rate / Coverage Time (Mode 4) Vendor Allocated Ground Latency Product Measurement Precision
Rainfall Potential GOES-R FD N/A 2.0 km 1.0 km 0 to 100 mm 5 mm for pixels designated as raining FD 15 min FD 5 min 266 sec 5 mm for pixels designated as raining
Temporal Coverage Qualifiers Product Extent Qualifier Cloud Cover Conditions Qualifier Product Statistics Qualifier
Day and night Quantitative out to at least 70 degrees LZA or 60 degrees latitude, whichever is less, and qualitative beyond N/A Over rainfall cases
10
11
  • Validation Strategy

12
Validation Strategy
  • Since the requirement is for rainfall
    accumulations of 3 h, radar and short-term gauges
    are the only available source of data for
    validation against spec
  • Ground-based radars
  • Nimrod radars in UK and Western Europe5-km grid
    composite

Sample Nimrod 3-h accumulation
13
Validation Strategy
  • Derive rainfall potential from rainfall rates
    retrieved from GOES-R ABI proxy data
  • Meteosat-8 SEVIRI inputs to rainfall rates
    Bands 5 (6.2 µm), 6 (7.3 µm), 7 (8.7 µm), 9 (10.8
    µm), and 10 (12.0 µm)
  • Collocate (in space and time) derived rainfall
    potential with ground validation rainfall
    accumulations
  • 3-hour observed rainfall accumulation derived
    from Nimrod radar
  • Generate comparative statistics (satellite
    rainfall accumulation ground truth rainfall
    accumulation)
  • Accuracy
  • Precision

14
  • Validation Results

15
Rainfall Potential Validation
CDFs of (absolute) errors of Rainfall Potential
vs. Nimrod radar data (Western Europe only) for
the 5th-9th of April, July, and October 2005.
16
Rainfall Potential Validation vs. Spec
Validation versus Nimrod radar data (covering
Western Europe only) for 15 days of data 6-9th
of April, July, and October 2005
FPS FPS Evaluation vs. Nimrod radar Evaluation vs. Nimrod radar
mm Accuracy Precision Accuracy Precision
Rainfall Potential 5.0 5.0 2.4 3.1
17
Next Steps
  • AIT determined that the highly object-oriented
    C K-Means code could not be readily implemented
    into the prototype framework
  • Consequently, NSSL has been asked to deliver a
    detailed ATBD and the algorithm is being re-coded
    from it
  • Once this is done, the K-Means parameters will be
    tuned to further enhance algorithm performance
  • Experiment with growth / decay option (currently
    turned off)
  • Alter minimum rainfall threshold to reduce
    effects of light rain on motion estimates
  • Tune scaling parameters

18
Summary
  • This Rainfall Potential Algorithm generates the
    Option 2 product of predicted rainfall
    accumulation for the next 3 h on the ABI grid.
  • The NOAA / NSSL K-Means algorithm has been
    adapted to produce extrapolation-based forecasts
    of rainfall from the current and previous GOES-R
    Rainfall Rate fields.
  • Version 3 (80) was delivered in September 2010.
    Version 5 (100) delivery has been delayed 12
    months in response to GPO guidance.
  • Preliminary validation of the version 3 algorithm
    has been performed against 20 days of SEVIRI
    data from 2005.
  • Validation against Nimrod radar indicates spec
    compliance.
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