On the Limits of Estimating the Maximum Wind Speeds in HurricanesSource: Monthly Weather Review:;2014:;volume( 142 ):;issue: 008::page 2814DOI: 10.1175/MWR-D-13-00337.1Publisher: American Meteorological Society
Abstract: his study uses an observing system simulation experiment (OSSE) approach to test the limitations of even nearly ideal observing systems to capture the peak wind speed occurring within a tropical storm or hurricane. The dataset is provided by a 1-km resolution simulation of an Atlantic hurricane with surface wind speeds saved every 10 s. An optimal observing system consisting of a dense field of anemometers provides perfect measurements of the peak 1-min wind speed as well as the average peak wind speed. Suboptimal observing systems consisting of a small number of anemometers are sampled and compared to the truth provided by the optimal observing system. Results show that a single, perfect anemometer experiencing a direct hit by the right side of the eyewall will underestimate the actual peak intensity by 10%?20%. Even an unusually large number of anemometers (e.g., 3?5) experiencing direct hits by the storm together will underestimate the peak wind speeds by 5%?10%. However, the peak winds of just one or two anemometers will provide on average a good estimate of the average peak intensity over several hours. Enhancing the variability of the simulated winds to better match observed winds does not change the results. Adding observational errors generally increases the reported peak winds, thus reducing the underestimates. If the average underestimate (negative bias) were known perfectly for each case, it could be used to correct the wind speeds, leaving only mean absolute errors of 3%?5%.
|
Collections
Show full item record
| contributor author | Nolan, David S. | |
| contributor author | Zhang, Jun A. | |
| contributor author | Uhlhorn, Eric W. | |
| date accessioned | 2017-06-09T17:31:44Z | |
| date available | 2017-06-09T17:31:44Z | |
| date copyright | 2014/08/01 | |
| date issued | 2014 | |
| identifier issn | 0027-0644 | |
| identifier other | ams-86766.pdf | |
| identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4230360 | |
| description abstract | his study uses an observing system simulation experiment (OSSE) approach to test the limitations of even nearly ideal observing systems to capture the peak wind speed occurring within a tropical storm or hurricane. The dataset is provided by a 1-km resolution simulation of an Atlantic hurricane with surface wind speeds saved every 10 s. An optimal observing system consisting of a dense field of anemometers provides perfect measurements of the peak 1-min wind speed as well as the average peak wind speed. Suboptimal observing systems consisting of a small number of anemometers are sampled and compared to the truth provided by the optimal observing system. Results show that a single, perfect anemometer experiencing a direct hit by the right side of the eyewall will underestimate the actual peak intensity by 10%?20%. Even an unusually large number of anemometers (e.g., 3?5) experiencing direct hits by the storm together will underestimate the peak wind speeds by 5%?10%. However, the peak winds of just one or two anemometers will provide on average a good estimate of the average peak intensity over several hours. Enhancing the variability of the simulated winds to better match observed winds does not change the results. Adding observational errors generally increases the reported peak winds, thus reducing the underestimates. If the average underestimate (negative bias) were known perfectly for each case, it could be used to correct the wind speeds, leaving only mean absolute errors of 3%?5%. | |
| publisher | American Meteorological Society | |
| title | On the Limits of Estimating the Maximum Wind Speeds in Hurricanes | |
| type | Journal Paper | |
| journal volume | 142 | |
| journal issue | 8 | |
| journal title | Monthly Weather Review | |
| identifier doi | 10.1175/MWR-D-13-00337.1 | |
| journal fristpage | 2814 | |
| journal lastpage | 2837 | |
| tree | Monthly Weather Review:;2014:;volume( 142 ):;issue: 008 | |
| contenttype | Fulltext |