1B.4 Spatial and Temporal Distribution of “Heaviest Precipitation each Day” Based on CoCoRaHS Data

Monday, 23 January 2017: 11:45 AM
602 (Washington State Convention Center )
Nolan J. Doesken, Colorado State Univ., Fort Collins, CO; and A. Stewart, J. Turner, Z. Schwalbe, P. Goble, N. Newman, and H. Reges

CoCoRaHS (the Community Collaborative Rain, Hail and Snow network) has provided nationwide coverage of daily precipitation observations since late 2009.  With typically 10,000 – 12,000 measurements of daily (24-hour) precipitation each day, this data set is proving very valuable for identifying and displaying many attributes of daily precipitation. This presentation features a thorough analysis of a fascinating and significant precipitation attribute – the “heaviest precipitation each day.”  This is simply the wettest place in the nation (CONUS only and CONUS plus AK and HI) each day based on the greatest observed 24-hour precipitation amount for each and every day of the year.  Daily data, 2010-2016 are used.  Time lapse animation captures how this varies in magnitude and geography as a function of season and how it often repeats this general pattern from year to year.  The magnitude of heaviest daily precipitation amount ranges from less than 25mm a few days each year to over 450mm on rare occasions.   Most days the heaviest precipitation measurement falls in the range from 75 to 150mm.  While practically any location can be the wettest point in the nation on any given day, there are clearly a number of preferred heavy rain hot spots through the year.  For example, Pacific Northwest coastal areas and the east coast of Florida maximize in mid-winter.  From late spring to early fall, the heaviest daily rainfall amount is most likely to occur somewhere in the middle portions of the country.  The Gulf Coast, not surprising, has the highest overall concentration of “highest daily” amounts and also the highest magnitudes.  The Big Island of Hawaii is also a frequent “winner”.  Seasonality and other statistical characteristics will be described.  The significance of these patterns will be discussed as well as data limitations.
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