TITLE

Quantifying Interagency Differences in Tropical Cyclone Best-Track Wind Speed Estimates

AUTHOR(S)
Knapp, Kenneth R.; Kruk, Michael C.
PUB. DATE
April 2010
SOURCE
Monthly Weather Review;Apr2010, Vol. 138 Issue 4, p1459
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Numerous agencies around the world perform postseason analysis of tropical cyclone position and intensity, a process described as “best tracking.” However, this process is temporally and spatially inhomogeneous because data availability, operational techniques, and knowledge have changed over time and differ among agencies. The net result is that positions and intensities often vary for any given storm for different agencies. In light of these differences, it is imperative to analyze and document the interagency differences in tropical cyclone intensities. To that end, maximum sustained winds from different agencies were compared using data from the International Best Track Archive for Climate Stewardship (IBTrACS) global tropical cyclone dataset. Comparisons were made for a recent 5-yr period to investigate the current differences, where linear systematic differences were evident. Time series of the comparisons also showed temporal changes in the systematic differences, which suggest changes in operational procedures. Initial attempts were made to normalize maximum sustained winds by correcting for known changes in operational procedures. The result was mixed, in that the adjustments removed some but not all of the systematic differences. This suggests that more details on operational procedures are needed and that a complete reanalysis of tropical cyclone intensities should be performed.
ACCESSION #
52008995

 

Related Articles

  • Retrieval of Kinematic Fields Using a Single-Beam Airborne Doppler Radar Performing Circular Trajectories. Protat, A.; Lemaitre, Y.; Scialom, G. // Journal of Atmospheric & Oceanic Technology;Aug97, Vol. 14 Issue 4, p769 

    The present study is devoted to new analyses of single-beam airborne Doppler radar data referred to as SAVAD (single-beam airborne velocity-azimuth display) and double SAVAD. These techniques permit processing of Doppler radial velocities from circular trajectories performed by the aircraft. As...

  • Detection of Cirrus Clouds with UHF Wind-Profiling Radar. Kobayashi, T.; Adachi, A.; Nagai, T.; Asano, S. // Journal of Atmospheric & Oceanic Technology;Feb99, Vol. 16 Issue 2, p298 

    Simultaneous measurements of cirrus clouds with a 404-MHz wind-profiling radar and a lidar were made to examine the sensitivity of a wind-profiling radar to cirrus clouds. The results show that a 404-MHz wind-profiling radar can detect cirrus clouds with the most ice content. Although the...

  • Validation of NCAR 10.6-μm CO[sub2] Doppler Lidar Radial Velocity Measurements and Comparison with a 915-MHz Profiler.  // Journal of Atmospheric & Oceanic Technology;Oct97, Vol. 14 Issue 5, p1110 

    The capability of the NCAR 10.6-μm-wavelength CO[sub2] Doppler lidar to measure radial air motion is validated by examining hard-target test data, comparing measurements with those from a two-axis propeller anemometer and a 915-MHz profiling radar, and analyzing power spectra and...

  • Estimates of tropical cyclone geometry parameters based on best track data. Nederhoff, Kees; Giardino, Alessio; van Ormondt, Maarten; Vatvani, Deepak // Natural Hazards & Earth System Sciences Discussions;2019, p1 

    Parametric wind profiles are commonly applied in a number of engineering applications for the generation of tropical cyclone (TC) wind and pressure fields. Nevertheless, existing formulations for computing wind fields often lack the required accuracy when the TC geometry is not known. This may...

  • Comments on “Reexamination of Tropical Cyclone Wind–Pressure Relationship”. Veterasamy, Shyamnath // Weather & Forecasting;Aug2008, Vol. 23 Issue 4, p758 

    In their study on the wind–pressure relationship (WPR) that exists in tropical cyclones, Knaff and Zehr presented results of the use of the Dvorak Atlantic WPR for estimating central pressure and maximum wind speed of tropical cyclones. These show some fairly large departures of estimated...

  • TOWARAD HOMOGENGUS GLOBAL TROPICAL CYCLONE BEST-TRACK DATASET. Levinson, David H.; Diamond, Howard J.; Knapp, Kenneth R.; Kruk, Michael C.; Gibney, Ethan J. // Bulletin of the American Meteorological Society;Mar2010, Vol. 91 Issue 3, p377 

    Information about several reports discussed at the International Best Track Archive for Climate Stewardship (IBTraCS) workshop is presented. Topics include the operational procedures towards producing tropical cyclone best-track data at various agencies, wind pressure relationships and wind...

  • New York City Storm Surges: Climatology and an Analysis of the Wind and Cyclone Evolution. Colle, Brian A.; Rojowsky, Katherine; Buonaito, Frank // Journal of Applied Meteorology & Climatology;Jan2010, Vol. 49 Issue 1, p85 

    A climatological description (�climatology�) of storm surges and actual flooding (storm tide) events from 1959 to 2007 is presented for the New York City (NYC) harbor. The prevailing meteorological conditions associated with these surges are also highlighted. Two surge thresholds of...

  • Effects of Rain Rate and Wind Magnitude on SeaWinds Scatterometer Wind Speed Errors. Weissman, David E.; Bourassa, Mark A.; Tongue, Jeffrey // Journal of Atmospheric & Oceanic Technology;May2002, Vol. 19 Issue 5, p738 

    Provides information on a study which examined the effects of rain rate and wind magnitude on sea winds scatterometer wind speed errors. Properties of the Next Generation Weather Radar; Issues surrounding electromagnetic backscatter and radar.

  • Doppler Radar Wind Data Assimilation with HIRLAM 3DVAR. Lindskog, M.; Salonen, K.; Järvinen, H.; Michelson, D. B. // Monthly Weather Review;May2004, Vol. 132 Issue 5, p1081 

    A Doppler radar wind data assimilation system has been developed for the three-dimensional variational data assimilation (3DVAR) scheme of the High Resolution Limited Area Model (HIRLAM). Radar wind observations can be input for the multivariate HIRLAM 3DVAR either as radial wind...

Share

Read the Article

Courtesy of MICHIGAN ELIBRARY

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics