1. Building a Weather-Ready Nation Increasingly Common Heavy Rainfall Events in Iowa Jeff Zogg – NWS Des Moines, IA Doug Kluck – NOAA Central Region Climate Services 1

2. Building a Weather-Ready Nation Agenda  The Problem  Research & Methodology  Summary & Impacts 2

3. Building a Weather-Ready Nation  Flooding is Iowa’s #1 weather-related hazard.  43 of 55 (~80%) Presidential Disaster declarations.  Iowa ranks #2 in the U.S. for flood-related losses.  Flooding—happening more frequently?  A major driver of flooding—especially flash flooding—in Iowa is heavy rainfall.  Heavy rainfall events seem to be occurring more frequently.  Perception or reality? The Problem 3 Ames/Iowa State University, Aug 2010 – Des Moines Register

4. Building a Weather-Ready Nation  Mallakpour & Villarini (2015)  Flood frequency increasing, not severity Support of Flooding Trends 4 Changes in flood magnitude, 1962-2011 Changes in flood frequency, 1962-2011 Northern U.S.

5. Building a Weather-Ready Nation  Used two frequency publications for Iowa  Rainfall Frequency Atlas of the Midwest (1992)  Huff & Angel – MRCC & Illinois SWS  NOAA Precipitation-Frequency Atlas 14, Volume 8 (2013) Research & Methodology 5 Overview

6. Building a Weather-Ready Nation  Base: 275 stations (IA: 41) – NWS coop sites w/ POR > 50 yrs; supplemented w/ other data  Max precip conversion factors  ≥ 1 day: NWS empirical factors used (& verified)  < 1 day: factors from 1948-1983 data for 55 recording rain gages in IL & surrounding states – compared & verified with other studies  Partial Duration Series (PDS) extracted MRCC Rainfall Frequency Atlas 6 Data & Analytical Approach

7. Building a Weather-Ready Nation  3 techniques evaluated  Log-log graphical (Huff-Angel)  Maximum likelihood  L-moments  No significant differences  By design, L-moments tends to give more conservative (i.e., lower) precip values for same recurrence interval  Huff-Angel technique selected  Allows analyst to incorporate professional knowledge  Cutoff near 100-yr event MRCC Rainfall Frequency Atlas 7 Statistical Methods

8. Building a Weather-Ready Nation  Point-based  Isohyetal maps derived  More susceptible to subjectivity & inherent variability  Shows small-scale variability  Areal-based  Tabular data derived  NWS climate divisions used (& verified appropriate)  Average frequency distributions used  Mitigates impacts of sampling errors MRCC Rainfall Frequency Atlas 8 Output Iowa NWS climate divisions

9. Building a Weather-Ready Nation  Base: IA – 276  Most were NWS coop sites  Max precip conversion factors  ≥ 1 day: similar to Bull71  < 1 day: hourly data used then correction factors applied; results believed similar to Bull71  Annual Maximum Series (AMS) extracted, then PDS obtained from AMS NOAA Atlas 14, Volume 8 9 Data & Analytical Approach Iowa daily stations used

10. Building a Weather-Ready Nation  L-moments technique  Less impacts of outliers  Upper & lower 90% confidence intervals calculated  Monte-Carlo simulation approach  Longer recurrence intervals  Region of influence approach NOAA Atlas 14, Volume 8 10 Statistical Methods Interactively removing stations from a region—Minnesota

11. Building a Weather-Ready Nation MRCC Bulletin 71 BothNOAA Atlas 14, Vol 8 2-month 3-month 4-month 6-month 9-month 1-year 2-year 5-year 10-year 25-year 50-year 100-year 200-year 500-year 1000-year Overlapping Return Pds & Durations 11 MRCC Bulletin 71BothNOAA Atlas 14, Vol 8 5-minute 6-minute 10-minute 15-minute 30-minute 1-hour 2-hour 3-hour 6-hour 12-hour 18-hour 24-hour 2-day 3-day 4-day 5-day 7-day 10-day 20-day 30-day 45-day 60-day

12. Building a Weather-Ready Nation  Clip geographic area to Iowa  Compute zonal statistics  84 individual files, each with 228,347 grids  Index each of the 84 rasters to between 0 & 1  Create average index value GIS Analysis Procedure 12 NOAA Atlas 14, Volume 8 South Skunk River @ Colfax, Iowa (Aug 2010)

13. Building a Weather-Ready Nation GIS Results 13

14. Building a Weather-Ready Nation 14

15. Building a Weather-Ready Nation  Documented Bull71 & Atlas14 results for all 9 Iowa climate sections  Calculated statewide averages  Compared all 12 common durations of Bull71 vs. Atlas14 for all 7 common T r s Data Analysis Procedure 15 Spreadsheet Cedar River @ Cedar Rapids, Iowa (2008) – Scott Olson/Getty Images

16. Building a Weather-Ready Nation 16 Results Data Analysis Procedure Great Flood of 1993 – Des Moines – Des Moines Water Works x = Tr (yr); y = precip value (in)

17. Building a Weather-Ready Nation  All 7 common T r s (↕) of Bull71 vs. Atlas14 for all 12 common durations (↔)  Bull71 equation correlation: 0.9968  Atlas14 equation correlation: 0.9934  # Atlas14 elements > Bull71: 78 (93%)  # Atlas14 elements < Bull71: 6 (7%) Data Analysis Procedure 17 Results Iowa Hwy 92—Muchakinock Creek near Oskaloosa (Aug 2010) – NWS Des Moines

18. Building a Weather-Ready Nation 18 Results Data Analysis Procedure

19. Building a Weather-Ready Nation  BUT…  Not simple relationship for width vs. duration & T r but (Atlas14 – Bull71) remains within 90% intervals  15-min, 2-yr event: |∆| = 0.004 in  6-hr, 100-yr event: |∆| = 0.834 in (Atlas14 ∆ ≈ 1.54 in)  HOWEVER... 90% Confidence Intervals 19 Remember Them?

20. Building a Weather-Ready Nation  Bull71 – Yes  Examine ratio of 2nd 40-yr period to 1st 40-yr period  Ratio > 1.1  “The increases appear to be greater than expected from natural climatic variability”  “Findings suggest that the assumption of a stationary time series for fitting statistical distributions to historical precipitation data may be invalid.”  “An update on the order of every 20 years would be appropriate to capture any substantial changes.” Rainfall Frequency Distribution 20 Changing Over Time?

21. Building a Weather-Ready Nation  Studies suggest flood frequency—not severity— increasing over time  Also suggest increases in heavy rainfall days but not rainfall severity  Atlas14 values > Bull71 values, but Bull71 values fall within the Atlas14 90% confidence intervals  Bull71 suggests heavy rainfall frequency distribution is changing over time, Atlas 14 says precip AMS is not changing  Does not address precip PDS trend Summary & Impacts 21

22. Building a Weather-Ready Nation  Mallakpour & Villarini (2015)  Findings similar to 3rd Nat’l Climate Assessment (2014) Support of Precip PDS Trends 22 Changes in heavy rainfall magnitude, 1948-2012 Changes in heavy rainfall frequency, 1948-2012 Northern U.S.

23. Building a Weather-Ready Nation  Most likely explanation  Precip PDS trends are changing – heavy rainfall becoming more frequent but not more severe  What if rainfall trends are to blame?  Under-designed municipal storm water systems?  More frequent flash flooding especially urban  Increased soil erosion  Timing of rainfall important Summary & Impacts 23 Central Iowa soil erosion – ISU Extension / Drake Larson Continued

24. Building a Weather-Ready Nation Thank You 24 For questions & additional information: NWS Des Moines, IA http://www.weather.gov/desmoines Email: jeff.zogg@noaa.govjeff.zogg@noaa.gov Phone: 515-270-4501

25. Building a Weather-Ready Nation 25

26. Building a Weather-Ready Nation Supporting Slides 26

27. Building a Weather-Ready Nation  Website  hdsc.nws.noaa.gov/hdsc/pfds/  Gridded NOAA Atlas 14, Volume 8 27 Output NOAA Atlas 14, Volume 8 Data

28. Building a Weather-Ready Nation  Download NOAA Atlas 14, Volume 8 data (ascii)  Convert data to raster format  Each grid cell ≈ 0.247 mi² or 0.50 mi/side  Define projection  Raster math to obtain true values  Clip geographic area to Iowa  Compute zonal statistics  84 individual files, each with 228,347 grids GIS Analysis Procedure 28 NOAA Atlas 14, Volume 8

29. Building a Weather-Ready Nation  Index each of the 84 rasters to values between 0 & 1 using: (1)  Add all 84 rasters to make sum raster  Divide sum raster by 84 to make average raster GIS Analysis Procedure 29 NOAA Atlas 14, Volume 8 (Continued) South Skunk River @ Colfax, Iowa (Aug 2010)

30. Building a Weather-Ready Nation  Compared all 7 common T r s (↕) of Bull71 vs. Atlas14 for all 12 common durations (↔)  For each duration, use all 7 common T r s to calculate c & b in: (2)  x = T r (yr); y = precip value (in)  Do for both Bull71 & Atlas14 (separate c & b values)  Use (2) to calculate predicted values for all 7 Bull71 & Atlas14 T r s for all 12 common durations  Compare predicted vs. actual values Data Analysis Procedure 30 Spreadsheet (Continued)

31. Building a Weather-Ready Nation  Compared all 7 common T r s (↕) of Bull71 vs. Atlas14 for all 12 common durations (↔) (cont’d)  Solve (2) for x: (3)  x = T r (yr); y = precip value (in)  For each T r plug actual Bull71 precip values into Atlas14 equation to find Atlas14 T r for Bull71 event  Calculate corresponding annual percent chance & compare to Bull71 Data Analysis Procedure 31 Spreadsheet (Continued)

32. Building a Weather-Ready Nation BUT... 32

33. Building a Weather-Ready Nation  Calculated in Atlas14 for each element  Width increases for increasing duration & T r  Example: Des Moines (min90 – expected – max90)  10-min, 1-yr event: 0.482 – 0.569 – 0.677 in, ∆ ≈ 0.098 in  10-day, 100-yr event: 9.06 – 11.5 – 14.1 in, ∆ ≈ 2.52 in  Atlas14 – Bull71  Not simple relationship for width vs. duration & T r but (Atlas14 – Bull71) remains within 90% intervals  15-min, 2-yr event: |∆| = 0.004 in  6-hr, 100-yr event: |∆| = 0.834 in (Atlas14 ∆ ≈ 1.54 in) 90% Confidence Intervals 33 Remember Them?

34. Building a Weather-Ready Nation HOWEVER... 34

35. Building a Weather-Ready Nation  Atlas14 – precip AMS not changing over time  Assumed stationarity  Tested @ 5% significance level, 1-day & 1-hr AMS data  Parametric t-test & non-parametric Mann-Kendal test for trends in means  1-day / 1-hr: no trends @ 93% / 86% of stations  Levene’s test for trends in variance  1-day / 1 hr: no trends @ 100% / 92% of stations  No trend noted in any climate region @ 5% level  Precip AMS ≠ PDS! Heavy Rainfall Frequency Distribution 35 Changing Over Time?