The regional water cycle and heavy spring rainfall in Iowa: Observational and modeling analyses from the IFloodS campaign

Young Hee Ryu, James A. Smith, Mary Lynn Baeck, Luciana K. Cunha, Elie Bou-Zeid, Witold Krajewski

Research output: Contribution to journalArticlepeer-review


The regional water cycle is examined with a special focus on water vapor transport in Iowa during the Iowa Flood Studies (IFloodS) campaign period, April-June 2013. The period had exceptionally large rainfall accumulations, and rainfall was distributed over an unusually large number of storm days. Radar-derived rainfall fields covering the 200 000 km2 study region; precipitable water from a network of global positioning system (GPS) measurements; and vertically integrated water vapor flux derived from GPS precipitable water, radar velocity-azimuth display (VAD) wind profiles, and radiosonde humidity profiles are utilized. They show that heavy rainfall is relatively weakly correlated with precipitable water and precipitable water change, with somewhat stronger direct relationships to water vapor flux. Thermodynamic properties tied to the vertical distribution of water vapor play an important role in determining heavy rainfall distribution, especially for periods of strong southerly water vapor flux. The diurnal variation of the water cycle during the IFloodS field campaign is pronounced, especially for rainfall and water vapor flux. To examine the potential effects of relative humidity in the lower atmosphere on heavy rainfall, numerical simulations are performed. It is found that low-level moisture can greatly affect heavy rainfall amount under favorable large-scale environmental conditions.

Original languageEnglish
Pages (from-to)2763-2784
Number of pages22
JournalJournal of Hydrometeorology
Issue number11
Publication statusPublished - 2016

Bibliographical note

Funding Information:
This research was supported by the National Science Foundation (NSF Grant EAR-0847347), NASA (Grant NNX10AI46G), the NOAA Cooperative Institute for Climate Science (CICS), and the Iowa Flood Center. The simulations were performed on the super computing clusters of the National Center for Atmospheric Research, through project P36861020. We acknowledge the helpful comments of Russ Schumacher and one anonymous reviewer; they markedly improved the paper.

Publisher Copyright:
© 2016 American Meteorological Society.

All Science Journal Classification (ASJC) codes

  • Atmospheric Science


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