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Assimilating best track Minimum Sea Level Pressure Data Together with Doppler Radar Data Using an Ensemble Kalman Filter for Hurricane Ike (2008) at a Cloud-Resolving Resolution

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Acta meteorologica Sinica 2013年第3期27卷 379-399页

作者：薛明董继立 Center for Analysis and Prediction of Storms University of Oklahoma School of Meteorology University of Oklahoma Key Laboratory for Mesoscale Severe Weather/Ministry of Education and School of Atmospheric ScienceNanjing University

Extending an earlier study, the best track minimum sea level pressure （MSLP） data are assimilated for landfalling Hurricane Ike （2008） using an ensemble Kalman filter （EnKF）, in addition to data from two coastal ground-based Doppler radars, at a 4-km grid spacing. Treated as a sea level pressure observation, the MSLP assimilation by the EnKF enhances the hurricane warm core structure and results in a stronger and deeper analyzed vortex than that in the GFS （Global Forecast System） analysis; it also improves the subsequent 18-h hurricane intensity and track forecasts. With a 2-h total assimilation window length, the assimilation of MSLP data interpolated to 10-min intervals results in more balanced analyses with smaller subsequent forecast error growth and better intensity and track forecasts than when the data are assimilated every 60 minutes. Radar data are always assimilated at 10-min intervals. For both intensity and track forecasts, assimilating MSLP only outperforms assimilating radar reflectivity （Z） only. For intensity forecast, assimilating MSLP at 10-min intervals outperforms radar radial wind （Vr） data （assimilated at 10-min intervals）, but assimilating MSLP at 60-rain intervals fails to beat Vr data. For track forecast, MSLP assimilation has a slightly （noticeably） larger positive impact than Vr （Z） data. When V~ or Z is combined with MSLP, both intensity and track forecasts are improved more than the assimilation of individual observation type. When the total assimilation window length is reduced to 1 h or less, the assimilation of MSLP alone even at 10-min intervals produces poorer 18-h intensity forecasts than assimilating Vr only, indicating that many assimilation cycles are needed to establish balanced analyses when MSLP data alone are assimilated; this is due to the very limited pieces of information that MSLP data provide.

关键词： hurricane data assimilation ensemble Kalman filter best track

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The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data:An Evaluation of Homogeneity

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Advances in Atmospheric Sciences 2024年第4期41卷 639-654页

作者： Ming YING Xiaoqin LU Shanghai Typhoon Institute China Meteorological AdministrationShanghai 200030China

This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone(TC)best track data for the seasons 1949-1987 generated by the China Meteorological Administration(CMA).The evaluation of the reconnaissance data shows that the minimum central sea level pressure(MCP)data are relatively homogeneous,whereas the maximum sustained wind(MSW)data show both overestimations and spurious abrupt changes.Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset.Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data,two spurious changepoints were identified in the remainder of the best-track MCP data.Furthermore,the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance,which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind“observations”.In addition,the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades,which reflects the important influence of reconnaissance data on the CMA TC best track dataset.The wind-pressure relationship(WPR)used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW,which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.

关键词： tropical cyclone intensity homogeneity best track aircraft reconnaissance

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Estimating tropical cyclone surface winds: Current status, emerging technologies, historical evolution, and a look to the future

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Tropical Cyclone Research and Review 2021年第3期10卷 125-150页

作者： John A.Knaff Charles R.Sampson Matthew E.Kucas Christopher J.Slocum Michael J.Brennan Thomas Meissner Lucrezia Ricciardulli Alexis Mouche Nicolas Reul Mary Morris Galina Chirokova Philippe Caroff NOAA/Center for Satellite Applications and Research Fort CollinsCOUSA Naval Research Laboratory MontereyCAUSA Joint Typhoon Warning Center Pearl HarborHawaiiUSA NOAA/NWS/NCEP National Hurricane Center MiamiFLUSA Remote Sensing Systems Santa RosaCAUSA Ifremer Univ.BrestCNRSIRDLaboratoire d’Océanographie Physique et SpatialeIUEM29280 BrestFrance NASA/Jet Propulsion Laboratory PasadenaCAUSA Cooperative Institute for Research in the Atmosphere Fort CollinsCOUSA Tropical Cyclone/Regional Specialized Meteorological Center Météo FranceRéunionFrance

This article provides a review of tropical cyclone(TC)surface wind estimation from an operational forecasting perspective.First,we provide a summary of operational forecast center practices and historical databases.Next,we discuss current and emerging objective estimates of TC surface winds,including algorithms,archive datasets,and individual algorithm strengths and weaknesses as applied to operational TC surface wind forecast parameters.Our review leads to recommendations about required surface coverage—an area covering at least 1100 km from center of TC at a 2-km resolution in the inner-core,and at a frequency of at least once every 6 h.This is enough coverage to support a complete analysis of the TC surface wind field from center to the extent of the 34-kt(17 m s^(-1))winds at 6-h intervals.We also suggest future designs of TC surface wind capabilities include funding to ensure near real-time data delivery to operators so that operational evaluation and use are feasible within proposed budgets.Finally,we suggest that users of archived operational wind radii datasets contact operational organizations to ensure these datasets are appropriate for their needs as the datasets vary in quality through time and space,even from a single organisation.

关键词： Tropical cyclone Surface wind Satellite best track Operations

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