2 edition of Comparison and verification of dynamical and statistical Lake Erie storm surge forecasts found in the catalog.
Comparison and verification of dynamical and statistical Lake Erie storm surge forecasts
W. S. Richardson
by U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service in [Silver Spring, Md.]
Written in English
|Statement||William S. Richardson and David J. Schwab.|
|Series||NOAA technical memorandum NWS TDL -- 69.|
|Contributions||Schwab, David J., United States. National Weather Service. Techniques Development Laboratory., Great Lakes Environmental Research Laboratory.|
|The Physical Object|
|Pagination||iii, 19 p. :|
|Number of Pages||19|
We will use storm surge models with a horizontal resolution of 1/12° (for ensemble forecasts) and 1/30° (for deterministic forecasts) to demonstrate an increase in the lead time of useful forecasts from two to six days; (iii) Explore novel ways of visualizing the results from the ensemble forecast by: storm surge and aggregate sea level forecasting service: • Enhancing the existing storm surge forecasting and warning capabilities and practices • Based on solid science including the latest approaches to dynamical storm surge forecasting • Utilising synergies with existing operational forecast systems available at the Bureau.
Know the Basics A storm surge is water that is pushed onto shore by a hurricane. It is rarely a "wall of water" as often claimed, but rather a rise of water that can be as rapid as several feet in. Title: Simulation and forecasting of Lake Erie storm surges. Author: Schwab Created Date: 3/31/ PM.
Here, I’ll be talking about dynamical models, which use complex physical equations to predict the future, rather than statistical models. Statistical models are simpler, and use historical observations and their relationships to predict how conditions might evolve. Tony has a brief explanation of statistical models in the notes of this post. An Ensemble-Based Storm Surge Forecasting System for the Coast of Norway Øyvind Saetra, Nils Melsom Kristensen, Anne-Mette Olsen, (same for the deterministic storm surge model) 7. Forecast verification based on data for 1 October - 30 April
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Get this from a library. Comparison and verification of dynamical and statistical Lake Erie storm surge forecasts. [W S Richardson; David J Schwab; United States. National Weather Service.
Techniques Development Laboratory,; Great Lakes Environmental Research Laboratory,] -- The Great Lakes Environmental Research Laboratory and the Techniques Development Laboratory have compared. Storm Surge (ppt MB) - Talk provided to storm surge workshop in Mobile, AL (May ) SLOSH Display Program (ppt MB) - Talk provided to storm surge workshop in Mobile, AL (May ) SLOSH Display Program to ESRI Arc GIS (pptx MB) - Created June ; Storm Surge at MDL (ppt 28 MB) - SLOSH, P-Surge, and ETSS (Created.
To continually improve the quality of operational storm surge guidance and decision support tools used by NWS's National Hurricane Center (NHC), Ocean Prediction Center (OPC), regional headquarters, coastal Weather Forecast Offices (WFOs) and River Forecast Centers (RFCs), along with NWS operational partners such as local Emergency Managers (EMs), Department of Homeland Security (DHS) and the.
Dynamical models of the atmosphere, also known as numerical weather prediction (NWP) models, are extremely complex and use supercomputers to solve the mathematical equations governing the physics and motion of the tanding these equations requires knowledge of not only meteorology, but also high-level mathematics, including calculus and differential equations.
of several surge events on Lake Erie in –93 was made by Kelley et al. () using the GLCFS forced by the Penn State–NCAR MM4 model output.
Recently the km Eta Model output has been used to force the POM and produce forecasts for Lake Erie (Kelley et al. The GLCFS forecasts are made available on the.
Lake Erie is an enclosed, shallow sea with approximate mean dimensions of 60 feet in depth, miles in length, and 40 miles in width. It is located in the region of confluence of the principal winter-time tracks associated with Alberta and Colorado lows, and therefore is exposed to wind action from severe cyclonic storms many of which reach Cited by: A time-independent dynamical model of storm surge along island coasts using orthogonal curvilinear coordinates is presented.
The curved annulus between an island coast and an arbitrary deep-water boundary is mapped conformally onto a rectangular image. Two configurations of island coasts are investigated; circular and elliptic coasts. The corresponding coordinates are circular polar and Cited by: 1.
Accurate prediction of storm surge is a difficult problem. Most forecast systems produce multiple possible forecasts depending on the variability in weather conditions, possible temperature levels, winds, etc.
Ensemble modeling techniques have been developed with the stated purpose of obtaining the best forecast (in some specific sense) from the individual by: 2.
• Great Lakes Storm Surge Operational System (GLSSOS) was developed for the purpose of providing a flood early warning system for Canadian communities located along the shorelines of the Great Lakes −Lake Superior, Lake Huron, Lake St.
Clair, Lake Erie and Lake Ontario • DHI was hired to develop and calibrate hydrodynamic and wave models for. Storm surge and storm tide information Present winds and the expected time of onset of tropical storm or hurricane-force winds Tornado, flood, flash flood, rip current, beach erosion, and inland high wind potential Below is an example of the storm surge portion of an Hurricane Local Statement.
A subgroup was organized to focus on MJO operational prediction and was tasked to develop a MJO forecast metric for comparison of dynamical models from operational global prediction systems.
The activity is housed at CPC where the application, display, and evaluation of these MJO model forecasts is being done. Three real-time storm surge forecasting systems [the eight-member Stony Brook ensemble (SBSS), the Stevens Institute of Technology’s New York Harbor Observing and Prediction System (SIT-NYHOPS), and the NOAA Extratropical Storm Surge (NOAA-ET) model] are verified for 74 available days during the –08 and –09 cool seasons for five stations around the New York City–Long Island by: example of the model’s application to storm surge events in Southeast Asia.
Performance of the model In this section, we describe the performance of the storm surge model with two case studies and a comparative verification of surge prediction with two different forcing fields. (a) (b) File Size: KB. used in wind and surge analysis, but the wind and surge calculated using these profiles have yet to be compared in a statistical sense (though case studies do exist [e.g., Phadke.
Storm surges can then be predicted based on the current hurricane forecast, and the pre-generated storm surge of the closest match can be chosen through a table lookup or using a statistical.
the existing European storm surge models. The best performance of European storm surge models for non-storm and storm conditions was achieved by KNMI (with Kalman ﬁlter data assimilation) and BSH with errors of cm and cm, respectively.
Whereas the chaotic model can provide 6 and 48 hours forecasts with errors of cm. The storm surge that followed Tropical Storm Sandy in produced waves of water over 9 feet above normal tides, which slammed into the Northeastern United.
2 Storm surge modeling Storm surge modeling has advanced signiﬁcantly over the past 30years which turns out to be very essential to anticipate the occurrence of coastal ﬂooding.
Some advances on physically-based storm surge modeling have been reported by Bode and Hardy (), Battjes et al. () and Verlaan et al.
().Cited by: Shinnecock Inlet: Temp ° F Wind mph from the WNW. Smith Point Bridge: Temp ° F Wind mph from the NW. Southampton: Temp ° F Wind mph from the N.
The air-sea drag coefficient controls the transfer of momentum from wind to water. In modeling storm surge, this coefficient is a crucial parameter for estimating the surge height.
This study uses two strong wind events on Lake Erie to calibrate the drag coefficient using the Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) modeling system and the the Regional Ocean Modeling System.
Lake St. Clair 3 2 Lake Erie 9 2 Lake Ontario 7 2 3. METEOROLOGICAL DATA AND FORECASTS For a storm surge and wave forecasting system, the wind speed and direction are the main drivers influencing water level changes and wave generation.
As such, the availability and accessibility of accurate.Storm surges are the result of low barometric pressure and high winds, and they can have devastating effects on coastal areas. Numerical models provide a viable way to examine the potential impacts of storm surges on coastal areas.
Flooding and structural damage from storm surges can be more fully understood with these models.Predicting Storm Surge “One swell of a problem” Dack Stuart, Brian Pierce, Amy Gartman, Matt Grossi Mast – Physical Oceanography Storm surge is defined to be the difference between the observed water lever and the predicted level of the astronomical tides and is a probable and dangerous consequence of high wind events.