The International Best Track Archive for Climate Stewardship (IBTrACS)

Knapp, Kenneth R.; Kruk, Michael C.; Levinson, David H.; Diamond, Howard J.; Neumann, Charles J.

doi:10.1175/2009bams2755.1

Cited by 2,125 publications

(1,657 citation statements)

References 10 publications

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“…This is confirmed when the NRCM is driven with the raw CCSM3 model data with resulting suppression of almost all tropical cyclone development (Fig. 3a) to an average of only 1.5 storms per year, compared to the observed average of *9-12 (Knapp et al 2010). The storms that occur also tend to develop much further poleward than observed (Fig.…”

Section: Bias Correctionsupporting

confidence: 60%

Bias corrections of global models for regional climate simulations of high-impact weather

et al. 2013

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All global circulation models (GCMs) suffer from some form of bias, which when used as boundary conditions for regional climate models may impact the simulations, perhaps severely. Here we present a bias correction method that corrects the mean error in the GCM, but retains the sixhourly weather, longer-period climate-variability and climate change from the GCM. We utilize six different bias correction experiments; each correcting different bias components. The impact of the full bias correction and the individual components are examined in relation to tropical cyclones, precipitation and temperature. We show that correcting of all boundary data provides the greatest improvement.

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Section: Bias Correctionsupporting

confidence: 60%

Bias corrections of global models for regional climate simulations of high-impact weather

et al. 2013

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“…The centre of the TC is defined as the minimum of the mean sea-level pressure that is closest to the 850 hPa vorticity maximum. The best-track data used to assess the ensemble performance are taken from the International Best Track Archive for Climate Stewardship (IBTrACS: Knapp et al, 2010). …”

Section: Methodsmentioning

confidence: 99%

Impact of perturbation methods in the ECMWF ensemble prediction system on tropical cyclone forecasts

Lang

Leutbecher

Jones

2012

Quart J Royal Meteoro Soc

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In the operational configuration of the ensemble prediction system of the European Centre for Medium-Range Weather Forecasts, different methods are applied to account for initial condition and model uncertainties. Singular vectors and an ensemble of data assimilations are used to generate perturbations to the initial conditions. Two stochastic tendency perturbation schemes aim to mimic model errors: the stochastic kinetic-energy backscatter scheme and the stochastically perturbed parametrization tendency scheme. In this study, the impact of the different perturbation methods on the ensemble spread during tropical cyclone (TC) events is compared and the time evolution of the spatial perturbation structure is investigated. The structure of perturbations due to different methods initially is quite different. However, our results show that they converge toward a TC displacement and an intensity-change pattern during the first two days of the forecast, on average. The perturbations generated by the stochastic tendency perturbation schemes grow rapidly and effectively excite growing modes of the flow. After 48 hours, a large part of the total energy of the singular vector perturbations in the vicinity of the TCs can be explained by the perturbations of other methods. The perturbations by the ensemble of data assimilations dominate the ensemble spread for a rather short lead time (around 24 hours). In about 40% of cases, the perturbations due to the tendency perturbation schemes or those generated from singular vectors produce a larger TC track and central pressure spread than the perturbations by the ensemble of data assimilations after two days forecast time. If all methods are applied, the average TC track spread of the ensemble matches the average error of the ensemble-mean well. In addition, the ensemble captures the anisotropy in the position uncertainty of the TCs.

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“…The tropical cyclone analysis is based on the global IBTrACS data set (Knapp et al 2010). A homogeneous satellite reanalysis by Kossin et al (2007) found close agreement of the archived intensities in the North Atlantic and western North Pacific, but there were inconsistencies for more intense storms in the other regions.…”

Section: Datamentioning

confidence: 99%

“…IBTrACS has been converted to a uniform 10-min mean wind definition (Knapp et al 2010). For the western North Pacific, we use the JTWC data set without correction aside from conversion to 10-min mean.…”

Section: Datamentioning

confidence: 99%

Recent intense hurricane response to global climate change

2013

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An Anthropogenic Climate Change Index (ACCI) is developed and used to investigate the potential global warming contribution to current tropical cyclone activity. The ACCI is defined as the difference between the means of ensembles of climate simulations with and without anthropogenic gases and aerosols. This index indicates that the bulk of the current anthropogenic warming has occurred in the past four decades, which enables improved confidence in assessing hurricane changes as it removes many of the data issues from previous eras. We find no anthropogenic signal in annual global tropical cyclone or hurricane frequencies. But a strong signal is found in proportions of both weaker and stronger hurricanes: the proportion of Category 4 and 5 hurricanes has increased at a rate of *25-30 % per°C of global warming after accounting for analysis and observing system changes. This has been balanced by a similar decrease in Category 1 and 2 hurricane proportions, leading to development of a distinctly bimodal intensity distribution, with the secondary maximum at Category 4 hurricanes. This global signal is reproduced in all ocean basins. The observed increase in Category 4-5 hurricanes may not continue at the same rate with future global warming. The analysis suggests that following an initial climate increase in intense hurricane proportions a saturation level will be reached beyond which any further global warming will have little effect.

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The International Best Track Archive for Climate Stewardship (IBTrACS)

Cited by 2,125 publications

References 10 publications

Bias corrections of global models for regional climate simulations of high-impact weather

Bias corrections of global models for regional climate simulations of high-impact weather

Impact of perturbation methods in the ECMWF ensemble prediction system on tropical cyclone forecasts

Recent intense hurricane response to global climate change

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