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Theme for 2008:
Estimating and Forecasting Extreme Floods
University of California, Davis
Special Recognition Award
Proceedings
How to Extrapolate Frequency Curves — with No Regrets!!
- Download the presentation (PDF*, 944 KB)
- View the video (MP4†, 25:34 minutes)
This paper provides information on how not to extrapolate statistically derived frequency curves. In particular, careful evaluation of the federally approved methods described in the Bulletin 17B guidelines is given. A new/old method that considers the physical limitations of a watershed to produce runoff was utilized. A new Monte Carlo method of establishing uncertainty around the derived curve was employed. Specifically, an example of integrating the Probable Maximum Flood (PMF) into the process of frequency curve development and extrapolation is described.
Updating Flood Frequency in California
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- View the video (MP4†, 26:09 minutes)
Annual Exceedance Probability of Extreme Events
- Download the presentation (PDF*, 878 KB)
- View the video (MP4†, 32:24 minutes)
Australian Methods for Estimating Large to Extreme Floods
- Download the presentation (PDF*, 666 KB)
- View the video (MP4†, 31:05 minutes)
Updating California Precipitation Frequency Estimates
- Download the presentation (PDF*, 1.2 MB)
- View the video (MP4†, 34:45 minutes)
Atmospheric Rivers and Their Role in Generating Heavy Orographic Precipitation and Flooding Along the U.S. West Coast
- Download the presentation (PDF*, 2.7 MB)
- View the video (MP4†, 31:59 minutes)
Lower-tropospheric conditions during the landfall of ARs are anomalously warm and moist with weak static stability and strong onshore flow, resulting in orographically enhanced precipitation and unusually high melting levels. Hence, ARs are critical contributors to extreme precipitation and flooding events. Despite these deleterious impacts, ARs also replenish snowpacks and reservoirs across parts of the semiarid West, so they represent a key to understanding regional impacts of climate change on water resources. A winter-season analysis of quantitative precipitation forecasts during NOAA’s Hydrometeorological Testbed (HMT) in California in 2006 reveals that the heavy precipitation associated with ARs is often challenging to predict, even though the heaviest areas of precipitation tend to be orographically anchored. These challenges arise due to hard-to-forecast frontal waves and differential rain shadowing between adjacent watersheds, among other factors.
Improving Observations of Coastal Storms
- Download the presentation (PDF*, 3.7 MB)
- View the video (MP4†, 24:31 minutes)
These experiments collected new meteorological observations, both to support research on the physical processes related to coastal storms and to aid operational 0-48 h weather forecasting. In particular, a new bulk water vapor transport tool has been developed to help improve short-term (<~6 h) precipitation forecasts in mountainous terrain. The tool uses coastal Doppler wind profilers to measure the upslope component of the flow aloft and collocated GPS receivers to measure the integrated water vapor content. The product of these two variables produces a bulk water vapor flux. The flow at the surface often bears little resemblance to that at a controlling level (where the correlation between the water vapor flux and mountain precipitation is maximized) due to the ubiquitous presence of shallow terrain-blocked flows, thus highlighting the need to obtain upper-air wind measurements for this particular application. The tool is described in the context of the intense West Coast storm that inundated California with heavy precipitation in early January 2008. Numerical weather prediction results are also shown to highlight the deficiency of model and human forecasts of heavy precipitation enhanced by mountains.
Quantitative Precipitation Forecasting and Estimating During the HMT Field Experiment: Ensemble Applications
- Download the presentation (PDF*, 1.8 MB)
- View the video (MP4†, 33:44 minutes)
This talk will focus on two areas: 1) a QPF-focused case study of the recent, powerful 4-7 January, 2008 storm that impacted central California, and summary results from the last two years of running the experimental ensemble; and 2) an exploration of utilizing a running ensemble to improve the diagnosis or estimate of precipitation in real time. In the former (1) we found that the ensemble mean captured the time-evolving precipitation patterns with some onset and cessation error and more RMS error as the precipitation amounts increased. Ensemble mean ETS scores were clearly superior to any of the individual models and were significantly better than the model configuration of the current NWS NAM model, running at 3km resolution. Verification of the probabilistic products did show that the ensemble had some skill for predicting rain rates as high as 25.4mm/6hr, but did not show skill for higher rates. For the second area (2), we will demonstrate that a 3-D variational approach where the needed error covariance can be specified fully in 2-D space, can improve the areal estimates of precipitation relative to the standard methods that interpolate rain gauges to a grid. By withholding random sets of rain gauges 183 times, we found that the 3-D var method that combines the model ensemble precipitation structure with precise measurements at gauge locations, can provide improved precipitation estimates relative to current methods.
Extreme Precipitation Analysis Tool (EPAT)
- Download the presentation (PDF*, 2.2 MB)
- View the video (MP4†, 28:57 minutes)
The primary differences of these studies from the HMR-PMP estimates are: (1) SSPMP and RPMP are storm-based studies and incorporate recent research on storm characteristics while HMR studies provide more general and overly conservative estimates of PMP potential; and (2) SSPMP and RPMP studies consider the characteristics of specific basins while HMR studies rely on a general consideration of topographic impacts on precipitation.
Currently, SSPMP and RPMP studies have no designated standard of practice. Due to this problem, HDR with help from the Colorado Division of Water Resources developed an Extreme Precipitation Analysis Tool (EPAT).
The EPAT is an ArcGIS-based developed software that provides an automated objective application of accepted SSPMP and RPMP analysis techniques to a specific basin based on analyses of state approved extreme precipitation event climatology. This tool was created by using ArcObject programming functions.
The application works by inputting a basin into the software in shapefile format. The software then runs a number of calculations using stored historical storms over that basin based on location and elevation of the basin. In the end, the application determines the controlling storm that creates the greatest amount of volume due to the elevation change and spatial extent of the storm in the basin.
Sponsors
- American River Watershed Institute
- Center for Watershed Sciences, University of California, Davis
- David Ford Consulting Engineers, Inc.
- HDR Engineering, Inc.
- MBK Engineers
- Placer County Water Agency
- Sacramento Area Flood Control Agency
- Sierra College Natural History Museum
Coordinator
Phone: 530–889–9025
Email: coord@cepsym.info
