Visualize, analyze, and download rainfall intensity-duration-frequency data
The IDF Curve Tool in NIH-DHAARA is built using three major rainfall datasets: IMDAA reanalysis, ERA5 reanalysis, and future climate projections from the BCC-CSM2-MR model (bias-corrected CMIP6 data). These datasets together provide historical, high-resolution rainfall information and future climate scenarios, enabling robust hydrological design and climate-resilient planning.
The Indian Monsoon Data Assimilation and Analysis (IMDAA) dataset is a high-resolution regional reanalysis developed by NCMRWF. It uses the Met Office Unified Model with 4D-Var assimilation to generate accurate rainfall fields for the Indian region.
IMDAA provides one of the most realistic reconstructions of Indian monsoon rainfall in the satellite era, making it suitable for short-duration extreme rainfall analysis and design applications.
Reference:
Rani, S.I., et al. (2021). IMDAA: High-resolution satellite-era reanalysis for the Indian monsoon region. Journal of Climate, 34(12), 5109–5133. DOI: 10.1175/JCLI-D-20-0412.1
Data Access:
ERA5, produced by the Copernicus Climate Change Service, provides globally consistent hourly rainfall estimates. It is widely used for hydrological and climate assessments due to its long-term reliability and spatial uniformity.
ERA5 serves as a reliable baseline dataset offering long-term climate consistency and global comparability.
Reference:
Hersbach, H., et al. (2023). ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Data Store. DOI: 10.24381/cds.adbb2d47
Data Access:
https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels?tab=download
To estimate IDF curves under climate change, the tool uses bias-corrected and downscaled projections from the BCC-CSM2-MR Global Climate Model (CMIP6). Raw GCM rainfall often contains systematic biases; therefore, bias correction significantly improves realism, particularly over South Asia.
Climate Scenarios (SSPs):
The tool supports multiple Shared Socioeconomic Pathways (SSPs) representing different global emission and development trajectories:
These scenarios help users understand potential changes in extreme rainfall under different future climate conditions.
References:
Wu, T., et al. (2019). The Beijing Climate Center Climate System Model (BCC-CSM): Progress from CMIP5 to CMIP6. Geoscientific Model Development, 12, 1573–1600.
Mishra, V., Bhatia, U., Tiwari, A.D. (2020). Bias-corrected climate projections for South Asia from CMIP6. Scientific Data, 7, 338. DOI: 10.1038/s41597-020-00681-1
| Dataset | Type | Spatial Resolution | Temporal Resolution | Years Used | Purpose |
|---|---|---|---|---|---|
| IMDAA | Regional reanalysis | ~12 km | 1-hourly | 2000–2022 | High-resolution Indian rainfall reconstruction |
| ERA5 | Global reanalysis | ~25 km | 1-hourly | 2000–2022 | Long-term consistent rainfall dataset |
| BCC-CSM2-MR (Bias-Corrected CMIP6) | Future climate projections | ~25 km | Daily | 2015–2100 | Future IDF curves under climate change |
Select a location and click Analyze to view results
Data table will appear here