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Guyana Rainfall Validation Dashboard: Evaluation of NASA GPM IMERG V07 Against Ground-Based Rainfall Observations
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| Created: | Nov 11, 2026 at 5:25 p.m. (UTC) | |
| Last updated: | Nov 11, 2026 at 6:40 p.m. (UTC) | |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
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Abstract
https://ulfloodcenter.github.io/guyana-rainfall-validation
This resource provides an interactive dashboard evaluating NASA Global Precipitation Measurement (GPM) IMERG Version 07 rainfall estimates against ground-based rainfall observations in Guyana. The assessment supports the evaluation of satellite-derived precipitation as rainfall forcing for hydrodynamic flood modeling using HEC-RAS 2D.
The primary validation covers 2020–2021 and includes nine rainfall stations and 6,517 paired gauge-day observations. The analysis examines cumulative rainfall bias, daily agreement, rainfall occurrence, spatial variability, intensity-dependent bias, seasonality, and selected rainfall events.
Results indicate that IMERG reproduces overall rainfall volume reasonably well, with a pooled bias of approximately −2%. However, station-level biases range from approximately −18.6% to +19.4%, and daily rainfall exceeding 100 mm is underestimated by approximately 52% in the available sample. These findings demonstrate the importance of evaluating rainfall products beyond aggregate rainfall totals, particularly when applied to flood modeling.
The resource includes an archived HTML dashboard and accompanying README documentation. The live interactive dashboard is available at https://ulfloodcenter.github.io/guyana-rainfall-validation/.
This work was conducted at the University of Louisiana at Lafayette's Louisiana Watershed Flood Center as part of NSF Award No. 2426270.
Subject Keywords
Coverage
Spatial
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Content
readme.md
Guyana Rainfall Validation Dashboard
Assessment of NASA GPM IMERG V07 Precipitation Against Ground-Based Rainfall Observations
Research project: Collaboratively Designed and Managed Flood Resilience Framework for Affected Communities in the Caribbean Region
Institution: University of Louisiana at Lafayette · Louisiana Watershed Flood Center
Funding: U.S. National Science Foundation, Award No. 2426270
Research Team
| Role | Name | Contact |
|---|---|---|
| Principal Investigator | Dr. Emad Habib | emad.habib@louisiana.edu |
| Research Engineer | Dr. Mohamed Morsy | mohamed.morsy@louisiana.edu |
| PhD Candidate | Gregory Williams | gregory.williams2@louisiana.edu |
Explore the interactive dashboard: https://ulfloodcenter.github.io/guyana-rainfall-validation/
Overview
This dashboard evaluates NASA Global Precipitation Measurement (GPM) IMERG Version 07 precipitation estimates against ground-based rainfall observations in Guyana. The assessment examines the suitability of the processed IMERG rainfall field as input to a HEC-RAS 2D flood model, focusing on rainfall magnitude, timing, spatial differences, occurrence, and intense rainfall.
Data and Approach
The primary assessment covers 2020–2021, using nine stations with sufficiently complete daily observations and 6,517 paired station-days. Daily gauge observations were compared with rainfall extracted from the nearest valid cell of the processed IMERG V07 grid. A 3 × 3 grid-cell neighborhood mean was also examined to assess point-to-grid representativeness.
Diagnostics include cumulative percentage bias (PBIAS), daily correlation, mean absolute error (MAE), root mean square error (RMSE), wet-day detection statistics (using a 1 mm/day threshold), station-to-station variability, rainfall-intensity and monthly biases, selected storm events, and sensitivity to the daily accumulation boundary.
Key Findings
- Overall volume: Pooled PBIAS was approximately −2.0% over 2020–2021, but station-level PBIAS ranged from approximately −18.6% to +19.4%.
- Daily agreement: Pooled daily Pearson correlation was approximately 0.66 after the best-performing daily accumulation alignment.
- High rainfall: IMERG tended to overrepresent light rainfall and underestimate heavier rainfall; the observed ≥100 mm/day class was underestimated by approximately 52% in the available sample.
- Uniform correction: A correction factor estimated from 2020 improved 2021 cumulative bias but slightly worsened daily RMSE, indicating that a single multiplier does not necessarily improve rainfall timing or event magnitudes.
These findings underscore why near-neutral long-period volume bias should not be interpreted as evidence of accurate rainfall forcing for individual flood events.
Dashboard Features
The dashboard includes an interactive station map; station-level time series, scatterplots, annual totals, and performance metrics; rainfall-intensity and seasonal diagnostics; selected-event comparisons; daily accumulation-boundary sensitivity; and a summary of the methodology and correction considerations.
Limitations
Only stations with usable daily observations were included in the primary quantitative comparison; the results do not represent complete coverage of Guyana. The best-performing accumulation boundary near 12:00 UTC is an empirical alignment result, not a confirmed gauge observation time. Point-gauge and gridded-rainfall estimates differ in spatial support, and daily comparisons do not establish the accuracy of subdaily rainfall intensities.
Access and Citation
- Live dashboard: https://ulfloodcenter.github.io/guyana-rainfall-validation/
- HydroShare archival resource and DOI: To be added after publication.
- Citation: To be finalized after confirming authorship and obtaining the HydroShare DOI.
Acknowledgment
This work was supported by the U.S. National Science Foundation under Award No. 2426270, Collaboratively Designed and Managed Flood Resilience Framework for Affected Communities in the Caribbean Region.
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| National Science Foundation (NSF) | Collaboratively Designed and Managed Flood Resilience Framework for Affected Communities in the Caribbean Region | 2426270 |
Contributors
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
| Name | Organization | Address | Phone | Author Identifiers |
|---|---|---|---|---|
| Guyana Hydrometeorological Service | Hydrometeorological Service, Guyana |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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