Communicating the impacts of projected climate change on heavy rainfall using a weighted ensemble approach

Momcilo Markus, James Angel, Gregory Byard, Sally McConkey, Chen Zhang, Ximing Cai, Michael Notaro, Moetasim Ashfaq

Research output: Contribution to journalArticle

Abstract

Urban flood risks are often determined by the frequency analysis of observed rainfall data, communicated using isohyetal maps showing rainfall totals for a range of durations and recurrence intervals. However, to assess future changes in heavy rainfall, it is necessary to study the future projected rainfall time series. Impacts of climate change are typically assessed using climate projections based on global climate model (GCM) outputs and downscaled to finer temporal and spatial scales. The projected data, however, are not generated in a format that urban planners and engineers can easily use to design for future conditions. This research presents a method to analyze and express climate data in a format that can be readily used in hydrologic models to assess the effects of future extreme rainfall events. Future conditions' climate data were analyzed using a weighted ensemble approach, which resulted in projected rainfall frequency estimates and their confidence limits. Two multimodel data sets were selected to illustrate this approach in Cook County, Illinois, which belongs to the Chicago metropolitan area. The first data set included statistical downscaling data based on the Intergovernmental Panel for Climate Change's (IPCC) Coupled Model Intercomparison Project Phase 3 (CMIP3) data. The weighted ensemble analysis applied to this data set produced results that indicated significant increases in projected heavy rainfall. For example, for CMIP3 Scenario A2, for the late 21st century, the 100-year, 24-h rainfall in the northern parts of the county was 29% larger than the model-generated rainfall for the present time. For the same time horizon and scenario, the confidence interval based on projected data was 87% wider compared with that of the published source (NOAA Atlas 14), calculated using the past observed data. Also, equal-weight delta-corrected IPCC CMIP5-based dynamical downscaling data were applied to the same region for the mid-21st century, producing increases in heavy rainfall fairly similar to those of CMIP3.

Original languageEnglish (US)
Article number04018004
JournalJournal of Hydrologic Engineering
Volume23
Issue number4
DOIs
StatePublished - Apr 1 2018

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Climate change
Rain
rainfall
climate change
twenty first century
downscaling
Climate models
recurrence interval
frequency analysis
climate
climate conditions
atlas
confidence interval
metropolitan area
global climate
Time series
climate modeling
time series
Engineers
CMIP

ASJC Scopus subject areas

  • Environmental Chemistry
  • Civil and Structural Engineering
  • Water Science and Technology
  • Environmental Science(all)

Cite this

Communicating the impacts of projected climate change on heavy rainfall using a weighted ensemble approach. / Markus, Momcilo; Angel, James; Byard, Gregory; McConkey, Sally; Zhang, Chen; Cai, Ximing; Notaro, Michael; Ashfaq, Moetasim.

In: Journal of Hydrologic Engineering, Vol. 23, No. 4, 04018004, 01.04.2018.

Research output: Contribution to journalArticle

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