1 goes-r awg hydrology algorithm team: rainfall probability june 14, 2011 presented by: bob...
TRANSCRIPT
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GOES-R AWG Hydrology Algorithm Team:
Rainfall ProbabilityJune 14, 2011
Presented By: Bob KuligowskiNOAA/NESDIS/STAR
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Outline
Executive Summary Algorithm Description ADEB and IV&V Response Summary Requirements Specification Evolution Validation Strategy Validation Results Summary
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Executive Summary This Rainfall Probability Algorithm generates the Option 2
product of predicted probability rainfall accumulation exceeding 1 mm for the next 3 h on the ABI grid.
Version 3 (80%) was delivered in September 2010. Version 5 (100%) delivery has been delayed 12 months in response to GPO guidance.
An algorithm has been developed that produces conditional probabilities based on the outputs and intermediate products of the Rainfall Potential algorithm.
Preliminary validation of the version 3 algorithm has been performed against 20 days of SEVIRI data from 2005.
Validation against Nimrod radar indicates partial spec compliance, and modifications have brought it closer to spec.
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Algorithm Description
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Algorithm Description
This Rainfall Probability Algorithm generates the Option 2 product of predicted probability rainfall accumulation exceeding 1 mm for the next 3 h on the ABI grid.
The algorithm derives the probability of rainfall during the next 3 h from the current Rainfall Rate product and intermediate (every 15 min) nowcasts of rainfall from the Rainfall Potential algorithm.
The algorithm was calibrated using regression against the Rainfall Rate product instead of ground measurements to:» Eliminate uncertainties associated with errors in the Rainfall Rate
algorithm;
» Allow much more spatially widespread calibration (ground truth is generally available over Western Europe only)
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(Original) Algorithm Description
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Distance to Closest Neighbor with Non-Zero Rain Potential
Probability of Rainfall if pixel has one or more intermediate Rainfall Potential
forecasts of non-zero rainfall
Probability of Rainfall if pixel Rainfall Potential is zero but a neighbor pixel has a
non-zero Rainfall Potential
More intermediate forecasts at pixel with non-zero rain ratehigher probability
Greater distance to nearest neighbor with non-zero rain
ratelower probability
Example Probability of Rainfall Output
Probability of Rainfall from 1500-1800 UTC 8 July 2005 derived from intermediate output of Rainfall Potential algorithm (which in turn uses SEVIRI-derived Rainfall Rate fields from 1445 and 1500 UTC as input).
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ADEB and IV&V Response Summary
ADEB did not recommend advancing the Rainfall Probability algorithm to 100% based on» Concerns about the 1 mm/h threshold—should be higher» Concerns about the “method and utility” of the algorithm
As a result, the algorithm development schedule has been delayed by 12 months.
Regarding the 1 mm/h threshold, the AT surveyed users from OSPO/SAB, NWS/HPC, NWS/OHD, and NWS/WGRFC users who indicated interested in probabilities at multiple thresholds.» However, the thresholds and additional data volume would
need GPO approval.
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ADEB and IV&V Response Summary
Regarding concerns about the “method”, the algorithm is currently being re-developed based on feedback from the ADEB, testing new predictors and evaluating the skill of the resulting algorithm.
Regarding concerns about the “utility” of the algorithm, the user survey found significant interest in the product and for it to be available at launch.
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ADEB and IV&V Response Summary
The ADEB also raised general concerns about the amount of 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.
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Requirements Specification Evolution
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Temporal Coverage Qualifiers
Product Extent QualifierCloud 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 and mesoscale-sized surrounding regions
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Validation Strategy
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
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Validation Strategy
Derive probability of rainfall from intermediate Rainfall Potential outputs (in turn derived from rainfall rates retrieved from GOES-R ABI proxy datasets)» Meteosat-8 SEVIRI inputs to rainfall rates: Bands 5 (6.2 µm),
6 (7.3 µm), 7 (8.7 µmµm), 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 probability of rainfall (0 or 1) derived from
Nimrod radar
Generate comparative statistics (satellite rainfall accumulation – ground truth rainfall accumulation)» Accuracy
» Precision
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Validation Results
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Rainfall Potential Validation(Original algorithm)
Reliability diagram for Probability of Rainfall vs.Reliability diagram for Probability of Rainfall vs. Nimrod radar data (Western Nimrod radar data (Western Europe only) for the 5Europe only) for the 5thth-9-9thth of April, July, and October 2005. of April, July, and October 2005.
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Rainfall Potential Validation(Original algorithm)
CDF’s of (absolute) errors of Probability of Rainfall vs.CDF’s of (absolute) errors of Probability of Rainfall vs. Nimrod radar data Nimrod radar data (Western Europe only) for the 5(Western Europe only) for the 5thth-9-9thth of April, July, and October 2005. of April, July, and October 2005.
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Rainfall Potential Validation vs. Spec
Original algorithm Original algorithm validation versus Nimrod radar data (covering Western validation versus Nimrod radar data (covering Western Europe only) for 15 days of data: 5Europe only) for 15 days of data: 5thth-9-9thth of April, July, and October 2005: of April, July, and October 2005:
F&PS Evaluation vs. Nimrod radar
% Accuracy Precision Accuracy Precision
Probability of Rainfall 25 40 11 71
F&PS Evaluation vs. Nimrod radar
% Accuracy Precision Accuracy Precision
Probability of Rainfall 25 40 15 57
Preliminary new algorithm Preliminary new algorithm validation versus Nimrod radar data (covering validation versus Nimrod radar data (covering Western Europe only) for 15 days of data: 5Western Europe only) for 15 days of data: 5 thth-9-9thth of April, July, and of April, July, and October 2005:October 2005:
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Next Steps
The Rainfall Probability calibration cannot be finalized until the Rainfall Potential algorithm is finalized.
In the meantime, additional predictors are being explored for use in the Rainfall Probability algorithm and have brought the algorithm closer to spec.
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Summary This Rainfall Probability Algorithm generates the Option 2
product of predicted probability rainfall accumulation exceeding 1 mm for the next 3 h on the ABI grid.
Version 3 (80%) was delivered in September 2010. Version 5 (100%) delivery has been delayed 12 months in response to GPO guidance.
An algorithm has been developed that produces conditional probabilities based on the outputs and intermediate products of the Rainfall Potential algorithm.
Preliminary validation of the version 3 algorithm has been performed against 20 days of SEVIRI data from 2005.
Validation against Nimrod radar indicates partial spec compliance, and modifications have brought it closer to spec.