Abstract
Monsoon precipitation demonstrates a wide range of spatial and temporal variability in the U.S. Southwest. A variety of precipitation monitoring networks, including official networks, municipal flood control districts, and citizen science observers, can help improve our characterization and understanding of the monsoon. The data management challenges of integrating these diverse data sources can be formidable. Computer science and data management techniques provide a pathway for the design of forward looking climate services, especially those developed in collaboration with experts in this field. In this paper we present such a collaboration, integrating natural, social and computer science expertise. We document how we identified data networks and their sources and the computer science and data management workflow we employed to integrate and curate these data. We also present the web based data visualization tool and API that we developed as part of this process (monsoon.environment.arizona.edu). We use case study examples from the Tucson, AZ region to demonstrate the visualizer. We also discuss how this type of collaboration could be extended to existing or potential stakeholder collaborations, as we facilitate access to a curated set of data that gives an increasingly granular perspective on monsoon precipitation variability. We also discuss what this collaborative approach integrating natural, social and computer science perspectives can add to the evolution of climate services.
Highlights
The North American Monsoon (NAM) is a seasonal phenomenon characterized by increased precipitation driven by a shift in the mid-level circulation pattern across the western U.S and subsequent increase in moisture availability in the Southwest U.S (Adams and Comrie, 1997; Higgins et al, 1997)
The results we present here demonstrate the strength of systematic aggregation of monsoon data, as well as the utility of making these data available in an intuitive/visual platform
This aggregated data captures aspects of monsoon variability that are not represented by single station metrics, and analysis and visualization of these data is not possible without a centralized database and visualization platform
Summary
The North American Monsoon (NAM) is a seasonal phenomenon characterized by increased precipitation driven by a shift in the mid-level circulation pattern across the western U.S and subsequent increase in moisture availability in the Southwest U.S (Adams and Comrie, 1997; Higgins et al, 1997). To aid in messaging and public outreach over seasonal hazards and to facilitate standardized comparisons of cumulative precipitation totals, the official National Weather Service definition of the monsoon was changed in 2008 to the period between June 15th and September 30th. Single station metrics using a limited number of stations typically a municipal airport or other long term National Weather Service stations - provide benchmarks that track the daily and cumulative totals for the monsoon during the aforementioned standardized seasonal window. This facilitates comparisons to long term averages and daily and seasonal records at these stations. And seasonal totals are some of the primary metrics used to track the seasonal progression and rank of each year of the monsoon, while the impacts associated with extreme events are of great interest to emergency managers, planners, and flood control district analysts (Shoemaker and Davis, 2008; Demaria et al, 2019)
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