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 IV&V 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 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  Validation against Nimrod radar indicates spec compliance.

4 Algorithm Description

5  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 between features in consecutive images »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.

Example Rainfall Potential Output Rainfall Potential from UTC 8 July 2005 derived from Rainfall Rate fields (retrieved from SEVIRI data) at 1445 and 1500 UTC.

8 ADEB and IV&V 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 IV&V 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-house—visit in summer 2012?) »EUMETSAT Hydrology SAF—reaching 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 10 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 FDN/A2.0 km 1.0 km 0 to 100 mm 5 mm for pixels designated as raining FD: 15 min FD: 5 min 266 sec5 mm for pixels designated as raining Temporal Coverage Qualifiers Product Extent Qualifier Cloud Cover Conditions Qualifier Product Statistics Qualifier Day and nightQuantitative out to at least 70 degrees LZA or 60 degrees latitude, whichever is less, and qualitative beyond N/AOver rainfall cases

11 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 Europe—5-km grid composite Sample Nimrod 3-h accumulation

13 Validation Strategy  Derive rainfall potential from rainfall rates retrieved from GOES-R ABI proxy data µm »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 CDF’s of (absolute) errors of Rainfall Potential vs.Nimrod radar data (Western Europe only) for the 5 th -9 th of April, July, and October CDF’s of (absolute) errors of Rainfall Potential vs. Nimrod radar data (Western Europe only) for the 5 th -9 th 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: 6-9 th of April, July, and October 2005: F&PSEvaluation vs. Nimrod radar mmAccuracyPrecisionAccuracyPrecision Rainfall Potential

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 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  Validation against Nimrod radar indicates spec compliance.