Expanding climate data available for research in watershed observatories: workflows
|Authors:||Jimmy Phuong Christina Bandaragoda|
|Owners:||Christina Bandaragoda Jimmy Phuong|
|Resource type:||Composite Resource|
|Storage:||The size of this resource is 33.0 MB|
|Created:||Mar 30, 2018 at 6:07 p.m.|
|Last updated:||Apr 04, 2018 at 1:11 a.m. by Christina Bandaragoda|
|Citation:||See how to cite this resource|
Studies of earth surface and environmental systems are becoming increasingly complex with integration of knowledge across multiple domains, enabled by technological advances to provide the collection of massive quantities of data, but requiring data science advances to improve usability of the largest of these datasets - spatially distributed time series of precipitation, temperature, and related atmospheric forcing data (hydrometeorology) used to drive hydrologic processes in models. Increasing the efficiency of using gridded, hydrometeorology data by scientists can be achieved by 1) increasing access to the latest research products such that 2) there is a decrease in effort spent on data processing and 3) an increase in time spent analyzing spatial and temporal characteristics which impact earth surface and environmental modeling experiments. The development of digital land-based Observatories supports ongoing improvements of knowledge at the watershed scale, critical for local decision-making, policy development, and natural disaster planning. The Observatory Gridded Hydrometerology (OGH) python library is designed as an open source software tool for environmental scientists and modelers to easily download and access time series from within regional, continental or global scale hydrometeorology products. This is especially useful for scientists and modelers who are not trained to select the most appropriate climate forcing data for their modeling study, do not have software tools for downloading and processing large datasets for watershed scale applications, and want to publish and run models in a cloud environment. We demonstrate the the use of this library with examples from three publicly available climate research products generated from interpolated gridded observations, hydrologic model and atmospheric model generated climate forcings. Our use cases include download, subset, and generation of statistics useful for for hydrologic and geomorphology modelers who study processes requiring time series of precipitation and temperature data for long term (+50 year) modeling studies. The OGH library is available on publicly accessible Github repository to encourage use in model research studies, and to expand the number of hydrometeorology products supported by this software with future contributions by researchers and software developers.
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