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This project aims to create an updated, comprehensive extreme precipitation atlas for the Northeast US, providing real-time monitoring and climate change tools. Data collection and quality control methods are used to analyze daily, hourly, and sub-hourly precipitation data to determine the probability of extreme precipitation events.
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Extreme Precipitation in New York & New EnglandBackground / Methodology Dan Zarrow Northeast Regional Climate Center Fall 2010
History of Extreme Precipitation Technical Paper 40 (1961) Wilks (1993) NOAA Atlas 14 (2004) NRCC (2010)
Project Goals • Create an updated, comprehensive extreme precipitation atlas for the Northeast US. • Match the products and output of NOAA Atlas 14 for NRCS compatability. • Add additional products to supplement NRCS hydrologic design. • Produce real-time monitoring and climate change tools.
It’s all about probability… • 100-yr Storm • 1 / 100 = 1% chance of occurrence in any year • 25-yr Storm • 1 / 25 = 4% chance of occurrence in any year • 1-yr Storm • 1 / 1 = 100% chance of occurrence???
The Process It rains! Data Collection & Quality Control Distribution Filtering Gridding Smoothing Output
Fitting the Distribution 25yr Storm 3.37” 100yr Storm 4.54”
Fitting the Distribution 25yr Storm 4.60” 100yr Storm 6.45”
Fitting the Distribution 25yr Storm 4.46” 100yr Storm 6.21”
Fitting the Distribution 25yr Storm 5.93” 100yr Storm 8.68”
Fitting the Distribution 25yr Storm 5.36” 100yr Storm 7.40”
Fitting the Distribution 25yr Storm 5.13” 100yr Storm 7.15”
Period of Record From start of record to end of 2008 Must have 20 complete years of data <25% of data record missing
Analysis of Daily Data • Used NRCC database to obtain data for 2,070 NOAA Cooperative Network stations in the Northeast. • Ran distribution for durations of 1day, 2day, 4day, 7day, and 10day.
Analysis of Hourly Data • Obtained historical precipitation data from NCDC hourly dataset for 603 stations in the Northeast. • Ran distribution for durations of 1hr, 2hr, 3hr, 6hr, 12hr, 24hr, and 48hr. • Calculated 24hr/1day ratio of 1.13, using data from initial Daily analysis. *Same as Atlas14
Analysis of Sub-Hourly Data • Used 5-minute data for 30 stations in the Northeast to run distribution for 5min, 10min, 15min, 30min, 60min, and 120min durations. • Calculated 60min/1hr ratio of 1.16, using data from Hourly analysis. *Same as Atlas14 • Calculated Nmin/60min ratios based on sub-hourly results.
Injection of Canadian Data • Used NCDC dataset with 649 daily stations in eastern Canada. • Ran Beta-P distribution for durations of 1day, 2day, 4day, 7day, and 10day. • Used average ratios throughout Northeast US study region to estimate hourly and subhourly return periods.
NRCC QC Process Data is pre-screened by NOAA and climate center staff each month, and flagged if suspect, erroneous, or an accumulated value. Unusually high daily data values are checked against nearby stations. If a daily rainfall value exceeds 10”, at least two nearby stations (within 200 miles) must also have reported amounts of at least 5”. If a daily rainfall value exceeds 5”, at least two nearby stations must also have reported amounts of at least 3”. Hourly precipitation data are checked against corresponding daily data. For each hour's data, at least one nearby station must have recorded a higher daily total rainfall amount. After the distribution is run for the entire Northeast, stations outside more than 2 standard deviations than the mean of all stations are removed.
NRCC QC Process AUTOMATIC Data is pre-screened by NOAA and climate center staff each month, and flagged if suspect, erroneous, or an accumulated value. Unusually high daily data values are checked against nearby stations. If a daily rainfall value exceeds 10”, at least two nearby stations (within 200 miles) must also have reported amounts of at least 5”. If a daily rainfall value exceeds 5”, at least two nearby stations must also have reported amounts of at least 3”. Hourly precipitation data are checked against corresponding daily data. For each hour's data, at least one nearby station must have recorded a higher daily total rainfall amount. After the distribution is run for the entire Northeast, stations outside more than 2 standard deviations than the mean of all stations are removed.
PDS vs. AMS Partial Duration Series (PDS) for n years in a station’s record, use the n highest independent rainfall amounts. Annual Maximum Series (AMS) use the highest rainfall amount for each year in a station’s record that has sufficient data.
Selecting a Distribution Wilks,D.S., 1993: Comparison of three-parameter probability distributions for representing annual extreme and partial duration precipitation series, Water Resources Research, 29, 3543-3549.
Selecting a Distribution Wilks,D.S., 1993: Comparison of three-parameter probability distributions for representing annual extreme and partial duration precipitation series, Water Resources Research, 29, 3543-3549.
Spatial Interpolation and Smoothing • It became clear we needed to smooth our Beta-P results based on Distance to Nearby Stations and the Period of Record of Nearby Stations. • From the August 2004 Journal of Hydrology: “Regionalization of extreme precipitation estimated for the Alabama rainfall atlas” (Durrans & Kirby)
Regionalization Demonstration Tully, NY 1day 100yr: 5.95” Distance: 28 miles Record Len.: 40 yrs. Auburn, NY 1day 100yr: 4.89” Distance: 33 miles Record Len.: 93 yrs. Ithaca, NY 1day 100yr: 5.58” Ithaca, NY Estimate 1day 100yr: 5.30” Elmira, NY 1day 100yr: 5.45” Distance: 31 miles Record Len.: 114 yrs. Binghamton, NY 1day 100yr: 5.46” Distance: 29 miles Record Len.: 61 yrs.
NRCC QC Process AUTOMATIC Data is pre-screened by climate center staff each month, and flagged if suspect, erroneous, or an accumulated value. Unusually high daily data values are checked against nearby stations. If a daily rainfall value exceeds 10”, at least two nearby stations (within 200 miles) must also have reported amounts of at least 5”. If a daily rainfall value exceeds 5”, at least two nearby stations must also have reported amounts of at least 3”. Hourly precipitation data are checked against corresponding daily data. For each hour's data, at least one nearby station must have recorded a higher daily total rainfall amount. After the distribution is run for the entire Northeast, stations outside more than 2 standard deviations than the mean of all stations are removed.