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A Survey of Precipitation Data for Environmental Modeling (iEMSs 2018)
Citation:
Sitterson, J., Chris Knightes, R. Parmar, K. Wolfe, B. Avant, A. Ignatius, AND D. Smith. A Survey of Precipitation Data for Environmental Modeling (iEMSs 2018). iEMSs 2018, Fort Collins, CO, June 24 - 28, 2018.
Impact/Purpose:
An introduction to precipitation and precipitation in models.
Description:
There is always a challenge of obtaining the “best” data to inform environmental models. Here we present different types of available precipitation datasets while detailing temporal and spatial resolution, potential errors in the dataset, and optimal performance scenarios. Our goal is to inform modelers of the various types, resolutions, and sources of precipitation data available for environmental modeling. Precipitation is the main driver in the hydrological cycle and modelers use this information to understand water quality and water availability. Environmental models use observed precipitation information for modeling past or current conditions, while simulated data are used to predict future conditions as well as recreate historic conditions. Several precipitation datasets and data generation methods such as National Climatic Data Center rain gauges, National and Global Land Data Assimilation, Next Generation Weather Radar, and Stochastic Weather Generators are described, giving their strengths and weaknesses. USEPA’s Hydrologic Micro Services (HMS) project has developed a collection of interoperable water quantity and quality modeling components that leverage existing internet-based data sources and sensors via a web service. Each component may have multiple implementations ranging from coarse to detailed levels of physical process modeling. The precipitation component of HMS will provide the information and data from multiple sources through the web service for modeling purposes.
