Passive-Microwave-Enhanced Statistical Hurricane Intensity Prediction Scheme

Jones, Thomas A.; Cecil, Daniel J.; DeMaria, Mark

doi:10.1175/waf941.1

Cited by 24 publications

(23 citation statements)

References 20 publications

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“…Similar phenomena exist for other lead times. The MAEs of the total samples are 2.6, 4.2, 5.5, 6.1, 6.1, and 6.3 m s −1 from 12 to 72 h, respectively, showing a similar leveling-off of the errors at longer lead times to that described by Jones et al (2006). It should be pointed out that a fair comparison among different prediction schemes for TC intensity can only be made based on a unique best-track dataset.…”

Section: Forecast Errors Of the Dependent Samplessupporting

confidence: 62%

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A western North Pacific tropical cyclone intensity prediction scheme

Chen

Chan

2011

Acta Meteorol Sin

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A western North Pacific tropical cyclone (TC) intensity prediction scheme (WIPS) is developed based on TC samples from 1996 to 2002 using the stepwise regression technique, with the western North Pacific divided into three sub-regions: the region near the coast of East China (ECR), the South China Sea region (SCR), and the far oceanic region (FOR). Only the TCs with maximum sustained surface wind speed greater than 17.2 m s −1 are used in the scheme. Potential predictors include the climatology and persistence factors, synoptic environmental conditions, potential intensity of a TC and proximity of a TC to land. Variances explained by the selected predictors suggest that the potential intensity of a TC and the proximity of a TC to land are significant in almost all the forecast equations. Other important predictors include vertical wind shear in ECR, 500-hPa geopotential height anomaly at the TC center, zonal component of TC translation speed in SCR, intensity change of TC 12 or 24 h prior to initial time, and the longitude of TC center in FOR.Independent tests are carried out for TCs in 4 yr (2004)(2005)(2006)(2007), with mean absolute errors of the maximum surface wind being 3.0, 5.0, 6.5, 7.3, 7.6, and 7.9 m s −1 for 12-to 72-h predictions at 12-h intervals, respectively. Positive skills are obtained at all leading time levels as compared to the climatology and persistence prediction scheme, and the large skill scores (near or over 20%) after 36 h imply that WIPS performs especially better at longer leading times. Furthermore, it is found that the amendment in TC track prediction and real-time model analysis can significantly improve the performance of WIPS in the SCR and ECR. Future improvements will focus on applying the scheme for weakening TCs and those near the coastal regions.

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Section: Forecast Errors Of the Dependent Samplessupporting

confidence: 62%

“…Efforts are being continuously made to improve the skill of these techniques by including the passive microwave information (Jones et al, 2006), considering inland decay factors , or proposing consensus/ensemble schemes .…”

Section: Introductionmentioning

confidence: 99%

A western North Pacific tropical cyclone intensity prediction scheme

Chen

Chan

2011

Acta Meteorol Sin

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“…Lonfat et al (2004) evaluated spatial asymmetries in TRMM Microwave Imager (TMI) rain rates for global TCs over 1998-2000, noting a preference for rainfall in the forward quadrants of the TC relative to its motion while tropical storms exhibited greater asymmetries than hurricanes. Jones et al (2006) incorporated a PM component across the TC's innermost 100 km into the Statistical Hurricane Intensity Prediction Scheme (SHIPS) using the T b mean, maximum, minimum, and standard deviation, with standard deviation found to be a skillful predictor for the east Pacific. Overall, Jones et al (2006) note PM inclusion in SHIPS improved intensity prediction by 4%-8%, with the greatest improvement found for TCs undergoing an intensity change of 610 kt (1 kt 5 0.5144 m s 21 ) over 24-48 h.…”

Section: Introductionmentioning

confidence: 99%

Passive Microwave Quantification of Tropical Cyclone Inner-Core Cloud Populations Relative to Subsequent Intensity Change

Harnos

Nesbitt

2016

Monthly Weather Review

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Characteristics of over 15 000 tropical cyclone (TC) inner cores are evaluated coincidentally using 37-and 85-GHz passive microwave data to quantify the relative prevalence of cold clouds (i.e., deep convection and stratiform clouds) versus predominantly warm clouds (i.e., shallow cumuli and cumulus congestus). Results indicate greater presence of combined liquid and frozen hydrometeors associated with cold clouds within the atmospheric column for TCs undergoing subsequent rapid intensification (RI) or intensification. RI episodes compared to the full intensity change distribution exhibit approximately an order of magnitude increase for inner-core cold cloud frequency relative to warm cloud presence. Incorporation of an objective ring detection algorithm shows the robust presence of rings associated with hydrometeors for 85-GHz polarization corrected temperatures (P 85 ) and 37-GHz vertically polarized brightness temperatures (V 37 ) for differentiating RI with significance levels $99.99%, while 37-GHz false color rings of a combined cyan and pink appearance surrounding a region that is not cyan or pink lack statistical significance for discriminating RI against lesser intensification. Rings of depressed P 85 and enhanced V 37 tied to RI suggest the combined presence of liquid and frozen hydrometeors within the atmospheric column, indicative of cold clouds. The V 37 rings also exhibit preferences for those with collocated more widespread P 85 ice scattering signatures to be more commonly associated with RI and general intensification.

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“…Widely-used Tropical Cyclone (TC) models include regional air-sea coupled dynamical models such as COAMPS-TC (Hao, et al, 2013), HWRF (Tallapragada, et al, 2014;Kim, et al, 2014) and GFDL (Bender et al, 2007;Gall, et al, 2011), global dynamical models such as GFS and ECMWF, and statistical-dynamical intensity-prediction models such as SHIPS, STIPS, L-GEM, RII (DeMaria and Kaplan, 1999;DeMaria, et al, 2005;Knaff et al, 2005;Jones, et al, 2006;DeMaria, 2009;DeMaria, 2010;Kaplan, et al, 2010). All of these models benefit from improved 3-D spatial observational plus enhanced temporal resolution, i.e.…”

Section: Introductionmentioning

confidence: 99%

High-Definition Sounding System (HDSS) for Atmospheric Profiling

Black¹,

Harrison

Beaubien

et al. 2017

Journal of Atmospheric and Oceanic Technology

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The High-Definition Sounding System (HDSS) is an automated system deploying the expendable digital dropsonde (XDD) designed to measure wind and pressure–temperature–humidity (PTH) profiles, and skin sea surface temperature (SST) within and around tropical cyclones (TCs) and other high-impact weather events needing high sampling density. Three experiments were conducted to validate the XDD. On two successive days off the California coast, 10 XDDs and 14 Vaisala RD-94s were deployed from the navy’s Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft over offshore buoys. The Twin Otter made spiral descents from 4 km to 60 m at the same descent rate as the sondes. Differences between successive XDD and RD-94 profiles due to true meteorological variability were on the same order as the profile differences between the spirals, XDDs, and RD-94s. XDD SST measured via infrared microradiometer, referred to as infrared skin SST (SSTir), and surface wind measurements were within 0.5°C and 1.5 m s−1, respectively, of buoy and Twin Otter values. A NASA DC-8 flight launched six XDDs from 12 km between ex-TC Cosme and the Baja California coast. Repeatability was shown with good agreement between features in successive profiles. XDD SSTir measurements from 18° to 28°C and surface winds agreed well with drifting buoy- and satellite-derived estimates. Excellent agreement was found between PTH and wind profiles measured by XDDs deployed from a NASA WB-57 at 18-km altitude offshore from the Texas coast and NWS radiosonde profiles from Brownsville and Corpus Christi, Texas. Successful XDD profiles were obtained in the clear and within precipitation over an offshore squall line.

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Passive-Microwave-Enhanced Statistical Hurricane Intensity Prediction Scheme

Cited by 24 publications

References 20 publications

A western North Pacific tropical cyclone intensity prediction scheme

A western North Pacific tropical cyclone intensity prediction scheme

Passive Microwave Quantification of Tropical Cyclone Inner-Core Cloud Populations Relative to Subsequent Intensity Change

High-Definition Sounding System (HDSS) for Atmospheric Profiling

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