All water comes from somewhere. Researchers who want to know where it comes from rely on water isotopes, variants of water molecules with slightly different masses, as location identifiers. In particular, the specific fraction of heavy to light water isotopes is unique to the water's origin and processes it has undergone and can provide information on how water travels across the globe. From 2002 to the present, eight different satellite missions have been measuring the isotopes of water vapor around the planet, creating a rich dataset of water's origins and movements.
"Most scientists and satellite missions want to share data," said Mampi Sarkar, a research scientist at Rice University. "But it's not always an easy task. Each satellite was designed to answer slightly different questions, so they have all different types of data even though they fundamentally measure the same thing. A giant collection of water isotope data was available, but there was no easy way for a researcher to use it."
These differing datasets made combining and comparing data from the satellites incredibly labor intensive, which made getting a comprehensive look at all the data challenging. Using data from two different satellites might mean a year spent cleaning and comparing the datasets before any analysis could be done. And since the datasets were kept in different locations, researchers around the world could be unknowingly replicating the labor-intensive work of reconciling the datasets.
"There are so many things this data could be used for," said Sylvia Dee , associate professor of Earth, environmental and planetary sciences at Rice. "Satellites access regions that field researchers can't, and they're incredibly important for consistent, long-term data collection. But for this to become a solid resource capturing the enormity of the water cycle, we needed to be able to treat it like one dataset."
To solve this problem, Sarkar collaborated with experts in the U.S. (NASA), Europe and Japan to create an open database, published in Nature Scientific Data . The database, called WISO-SAT, collected, standardized and cleaned all the data produced by these satellites over the past 24 years. Each expert had experience with a particular satellite, ensuring that Sarkar had access to the datasets and how data from each satellite was collected and recorded.
Once the raw data was collected, she carefully went through all of it to understand it then built a pipeline to standardize and share it. Now, any researcher can open the WISO-SAT public database, compare data across the eight satellite missions and easily access information on how the data has been standardized.
"The data is gridded and standardized," said Sarkar, the corresponding author on this study. "That means you can more easily compare all the datasets, while accounting for differences between instruments, and know exactly where each measurement was taken on the planet and what it's telling you, no matter which satellite it came from."
To encourage people to add new data, the pipeline used to standardize the data is publicly available as part of the dataset. This allows other researchers with access to similar data to grid and standardize it themselves before submitting it to the open database.
"Projects like this advance science through collaboration, accessibility and preservation of data," said Dee, who is also an author on the paper and funded the project initially as a part of her National Science Foundation CAREER award. "This database will allow researchers across the world to ask questions about cloud formation, moisture transport processes, El Niño and La Niña, deforestation, soil moisture and more. It's so important to highlight that it's not just the collection of data that matters; it's also the effort it takes to make the data truly usable for the broader research community, students and even the public."
The study was funded by the National Science Foundation (2338861, 2513024) and the NASA Energy and Water Study Satellite and Precipitation Isotope Constrained Estimates (80NSSC26K0676).
