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| GLOBALRAIN | |
|---|---|
| Name | GLOBALRAIN |
| Type | International research consortium |
| Established | 2008 |
| Headquarters | Geneva |
| Region served | Global |
GLOBALRAIN
GLOBALRAIN is an international research consortium focused on producing high-resolution global precipitation datasets by integrating satellite observations, ground-based measurements, and numerical models. It supports operational forecasting and climate research through collaborative work with agencies, universities, and metrological centers aiming to improve risk management for floods, droughts, and agriculture. GLOBALRAIN partners with major space agencies, scientific institutions, and humanitarian organizations to deliver standardized precipitation products for users across sectors.
GLOBALRAIN aggregates data from satellites such as TRMM, GPM (Global Precipitation Measurement), NOAA-POES, Meteosat, MetOp and Himawari while assimilating observations from networks like GSOD, GHCN, EUMETNET, CRN, and SEVIRI-linked systems. The consortium collaborates with research centers including NASA, ESA, JAXA, CNSA, ISRO, UK Met Office, ECMWF, NIWA, CMA (China Meteorological Administration), AEMET, SMHI, DWD, and Météo-France. GLOBALRAIN's data pipelines interoperate with infrastructures such as Copernicus, GEOSS, CEOS, WMO programs and regional initiatives like SERVIR, RCCs, RCOF, and APEC Climate Center. End users include UNICEF, World Food Programme, IFRC, UNDP, World Bank, FAO, UNEP, regional hydropower utilities, and municipal water authorities.
GLOBALRAIN was founded through a memorandum among research groups from ETH Zurich, Imperial College London, Massachusetts Institute of Technology, University of Washington, CSIRO, University of Tokyo, Peking University, Indian Institute of Science, Pontifical Catholic University of Chile, Universidad de São Paulo, University of Cape Town, and Cairo University. Early milestones include integration trials with TRMM era datasets and prototype demonstrations at conferences like AGU Fall Meeting, EGU General Assembly, AMS Annual Meeting, and workshops hosted by IPCC working groups. Funding and initial coordination were supported via grants from Horizon 2020, the European Research Council, NSF, NERC, DFID, Gates Foundation, and bilateral agreements involving Japan Science and Technology Agency and NSFC. Subsequent expansions incorporated operational partnerships with NOAA National Weather Service, Canadian Meteorological Centre, Brazilian INMET, Argentine SMN, and South African Weather Service.
GLOBALRAIN uses retrieval algorithms developed from academic research at Princeton University, Columbia University, University of California, Los Angeles, University of Colorado Boulder, Johns Hopkins University, and University of Reading. Key methods include merged radiometric retrievals, microwave brightness temperature inversion, radar reflectivity compositing, and reanalysis-driven bias correction linked to systems like ERA5, MERRA-2, JRA-55, and CFSv2. Software and platforms used include GDAL, NetCDF, HDF5, OpenDAP, Python, R Project, Julia (programming language), Dask, Apache Spark, Docker, and Kubernetes for scalable processing. Quality-control pipelines utilize geospatial tools from USGS, NOAA NCEI, and community libraries from GitHub repositories maintained by university and agency teams. Machine learning contributions originate from labs at Stanford University, Carnegie Mellon University, Tsinghua University, and University of Toronto applying convolutional neural networks, random forests, and Bayesian melding.
GLOBALRAIN distributes gridded precipitation products at multiple spatial and temporal resolutions, including hourly, daily, and monthly aggregates, compatible with formats used by CMIP6 model intercomparison projects and regional downscaling efforts like CORDEX. Product suites range from near-real-time monitoring, seasonal climatologies, trend atlases, extreme-event catalogs, to merged gauge-satellite-radar analyses suited for HydroSHEDS, GRDC basin studies, and flood-inundation mapping used by USAID missions. Distribution channels include portals interoperable with THREDDS, OpenDAP, Zenodo, and data citation indices tracked by DataCite and ORCID identifiers for dataset authorship.
GLOBALRAIN products inform tropical cyclone rainfall estimates for NOAA National Hurricane Center, flash-flood warnings for USGS and regional river services, agricultural advisories for CGIAR centers, and drought monitoring for Famine Early Warning Systems Network and FEWS NET. Climate researchers at IPSL, Hadley Centre, LSCE, NCAR, GFDL, and CEA use GLOBALRAIN to validate precipitation in climate models and attribution studies for extreme events discussed in IPCC AR6 reports. Humanitarian operations by Médecins Sans Frontières and ICRC use rapid-assessment rainfall layers during response planning. Urban resilience initiatives in cities like New York City, Tokyo, Mumbai, Lagos, São Paulo, and Cairo integrate GLOBALRAIN into stormwater design and insurance risk models by firms such as Munich Re and Swiss Re.
Validation campaigns have been conducted in collaboration with field projects like GPM Ground Validation, ICECAP, AMMA, VAMOS, HEPEX, and national networks including CoCoRaHS and RAINFALL. Known limitations include reduced retrieval skill over complex terrain (e.g., Himalayas, Andes, Rocky Mountains), biases in cold-season solid precipitation over Alaska and Greenland, and challenges in capturing sub-hourly convective bursts in the Sahel, Amazon Basin, and Maritime Continent. Intercomparison studies against GPCC, CMAP, TRMM 3B42, and IMERG quantify uncertainty metrics such as bias, RMSE, and categorical scores used by WMO verification panels. Continuous improvement relies on community campaigns supported by GEWEX, PICO, and national funding agencies.
GLOBALRAIN's governance board includes representatives from World Meteorological Organization, UNESCO, OECD, World Bank Group, major space agencies (NASA, ESA, JAXA), and academic consortia from Universities UK, AAAS, and The Royal Society. Funding streams combine competitive grants from Horizon Europe, NSF, DFG, and philanthropic awards from foundations like Rockefeller Foundation and Wellcome Trust, plus in-kind contributions from commercial partners including Maxar Technologies and Planet Labs. Collaborative agreements formalize data sharing with national services and humanitarian agencies via memoranda with UN OCHA, UNICEF, FAO, and regional development banks. Governance emphasizes open data, reproducible science, and alignment with international initiatives such as Sendai Framework disaster risk reduction and Sustainable Development Goals.