Benjamin W. Green

Impacts of Air–Sea Flux Parameterizations on the Intensity and Structure of Tropical Cyclones

AbstractFluxes of momentum and moist enthalpy across the air–sea interface are believed to be one of the most important factors in determining tropical cyclone intensity. Because these surface fluxes cannot be directly resolved by numerical weather prediction models, their impacts on tropical cyclones must be accounted for through subgrid-scale parameterizations. There are several air–sea surface flux parameterization schemes available in the Weather Research and Forecasting (WRF) Model; these schemes differ from one another in their formulations of the wind speed–dependent exchange coefficients of momentum, sensible heat, and moisture (latent heat). The effects of surface fluxes on the intensity and structure of tropical cyclones are examined through convection-permitting WRF simulations of Hurricane Katrina (2005).It is found that the intensity (and, to a lesser extent, structure) of the simulated storms is sensitive to the choice of surface flux parameterization scheme. In agreement with recent studies...

Probabilistic Evaluation of the Dynamics and Prediction of Supertyphoon Megi (2010)

AbstractSupertyphoon Megi was the most intense tropical cyclone (TC) of 2010. Megi tracked westward through the western North Pacific and crossed the Philippines on 18 October. Two days later, Megi made a sharp turn to the north, an unusual track change that was not forecast by any of the leading operational centers. This failed forecast was a consequence of exceptionally large uncertainty in the numerical guidance—including the operational ensemble of the European Centre for Medium-Range Weather Forecasts (ECMWF)—at various lead times before the northward turn. This study uses The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble dataset to examine the uncertainties in the track forecast of the ECMWF operational ensemble. The results show that Megis sharp turn is sensitive to its own movement in the early period, the size and structure of the storm, the strength and extent of the western Pacific subtropical high, and an approaching eastward-moving midlat...

Sensitivity of Tropical Cyclone Simulations to Parametric Uncertainties in Air–Sea Fluxes and Implications for Parameter Estimation

AbstractTropical cyclones (TCs) are strongly influenced by fluxes of momentum and moist enthalpy across the air–sea interface. These fluxes cannot be resolved explicitly by current-generation numerical weather prediction models, and therefore must be accounted for via empirical parameterizations of surface exchange coefficients (CD for momentum and Ck for moist enthalpy). The resultant model uncertainty is examined through hundreds of convection-permitting Weather Research and Forecasting Model (WRF) simulations of Hurricane Katrina (2005) by varying four key parameters found in commonly used parameterizations of the exchange coefficient formulas. Two of these parameters effectively act as multiplicative factors for the exchange coefficients over all wind speeds (one each for CD and Ck); the other two parameters control the behavior of CD at very high wind speeds (i.e., above 33 m s−1). It is found that both the intensity and the structure of TCs are highly dependent upon the two multiplicative parameters...

Multiscale Processes Leading to Supercells in the Landfalling Outer Rainbands of Hurricane Katrina (2005)

AbstractShallow supercells are frequently observed within the outer rainbands—both onshore and offshore—of landfalling tropical cyclones (TCs). Such supercells can produce tornadoes along the coast even when the center of the parent TC is hundreds of kilometers from land, as was the case with Hurricane Katrina (2005). A convection-permitting simulation with 1.5-km grid spacing in the innermost domain is used in conjunction with radar, radiosonde, and surface observations to investigate the multiscale conditions conducive to supercells in the landfalling outer rainbands of Katrina. Several hours before the eye of the TC made landfall, a baroclinic zone developed along the coast; this front strongly influenced the horizontal distributions of cell-relative helicity and CAPE such that the largest values of these parameters were located over land and water, respectively. An example of a tornadic supercell in the outer rainbands of Katrina is examined. This cell intensified just before landfall and spawned a to...

Numerical simulations of Hurricane Katrina (2005) in the turbulent gray zone

Current numerical simulations of tropical cyclones (TCs) use a horizontal grid spacing as small as Δx = 103 m, with all boundary layer (BL) turbulence parameterized. Eventually, TC simulations can be conducted at Large Eddy Simulation (LES) resolution, which requires Δx to fall in the inertial subrange (often <102 m) to adequately resolve the large, energy-containing eddies. Between the two lies the so-called “terra incognita” because some of the assumptions used by mesoscale models and LES to treat BL turbulence are invalid. This study performs several 4–6 h simulations of Hurricane Katrina (2005) without a BL parameterization at extremely fine Δx [333, 200, and 111 m, hereafter “Large Eddy Permitting (LEP) runs”] and compares with mesoscale simulations with BL parameterizations (Δx = 3 km, 1 km, and 333 m, hereafter “PBL runs”). There are profound differences in the hurricane BL structure between the PBL and LEP runs: the former have a deeper inflow layer and secondary eyewall formation, whereas the latter have a shallow inflow layer without a secondary eyewall. Among the LEP runs, decreased Δx yields weaker subgrid-scale vertical momentum fluxes, but the sum of subgrid-scale and “grid-scale” fluxes remain similar. There is also evidence that the size of the prevalent BL eddies depends upon Δx, suggesting that convergence to true LES has not yet been reached. Nevertheless, the similarities in the storm-scale BL structure among the LEP runs indicate that the net effect of the BL on the rest of the hurricane may be somewhat independent of Δx.

Evaluation of MJO Predictive Skill in Multiphysics and Multimodel Global Ensembles

Monthlong hindcasts of the Madden-Julian oscillation (MJO) from the atmospheric Flow-following Icosahedral Model coupled with an icosahedral-grid version of the Hybrid Coordinate Ocean Model (FIM-iHYCOM), and from the coupled Climate Forecast System, version 2 (CFSv2), are evaluated over the 12-yr period 1999-2010. Two sets of FIM-iHYCOM hindcasts are run to test the impact of using Grell-Freitas (FIM-CGF) versus simplified Arakawa-Schubert (FIM-SAS) deep convection parameterizations. Each hindcast set consists of four time-lagged ensemble members initialized weekly every 6 h from 1200 UTC Tuesday to 0600 UTC Wednesday. The ensemble means of FIM-CGF, FIM-SAS, and CFSv2 produce skillful forecasts of a variant of the Real-time Multivariate MJO (RMM) index out to 19, 17, and 17 days, respectively; this is consistent with FIM-CGF having the lowest root-mean-square errors (RMSEs) for zonal winds at both 850 and 200 hPa. FIM-CGF and CFSv2 exhibit similar RMSEs in RMM, and their multimodel ensemble mean extends skillful RMM prediction out to 21 days. Conversely, adding FIM-SAS-with much higher RMSEs-to CFSv2 (as a multimodel ensemble) or FIM-CGF (as a multiphysics ensemble) yields either little benefit, or even a degradation, compared to the better single-model ensemble mean. This suggests that multiphysics/multimodel ensemble mean forecasts may only add value when the individual models possess similar skill and error. An atmosphere-only version of FIM-CGF loses skill after 11 days, highlighting the importance of ocean coupling. Further examination reveals some sensitivity in skill and error metrics to the choice of MJO index.

Idealized Large-Eddy Simulations of a Tropical Cyclone–like Boundary Layer

AbstractThe tropical cyclone (TC) boundary layer (TCBL)—featuring extreme winds over a rough ocean—is difficult to study observationally. With increasing computational power, high-resolution large-eddy simulation (LES) has become an attractive tool to advance understanding of the TCBL. Here, an idealized Cartesian-based LES is employed to investigate boundary layers driven by extreme TC-like winds. The LES includes the effects of centripetal acceleration through an “effective” Coriolis parameter f* = f + 2Vg/R, with the Earth Coriolis parameter f, gradient wind Vg, and (fixed) radius R. Multiple LES experiments are conducted to elucidate how the boundary layer develops and persists in the strongly rotating TC environment. In all simulations, an overshooting jet develops, the height of which increases with Vg, R, and surface drag. Normalized jet strength also increases with R and drag but decreases with Vg. Turbulent diffusivity Km—which must be parameterized in mesoscale and global models but can be diagn...

Mitigating atmospheric effects in InSAR measurements through high-resolution data assimilation and numerical simulations with a weather prediction model

Repeat-pass spaceborne interferometric synthetic aperture radar (InSAR) is commonly used to measure surface deformation; phase delays due to atmospheric water vapour may have significant impact on the accuracy of these measurements. In recent years, there has been a growing interest in using forecasts and analyses from numerical weather prediction (NWP) models – which can provide good estimates of the atmospheric state – to correct for atmospheric phase delays. In this study, three separate estimates of atmospheric water vapour content from NWP output are used in combination with Environmental Satellite (Envisat) Advanced Synthetic Aperture Radar (ASAR) data over the Pearl River Delta region in South China to mitigate atmospheric distortion. The NWP-based estimates are derived from: (1) interpolation of National Centers for Environmental Prediction (NCEP) Final Operational Global Analysis (FNL) data; (2) Weather Research and Forecasting (WRF) model simulations initialized with FNL analysis without additional data assimilation; and (3) WRF simulations initialized with a three-dimensional variational (3DVar) data assimilation system that ingests additional meteorological observations. The accuracy of the atmospheric corrections from these different NWP model outputs is further verified quantitatively with precipitable water vapour (PWV) data from several ground-based global positioning system (GPS) stations in Hong Kong. Inter-comparison shows a good agreement between the PWV derived from the WRF-3DVar simulations and the GPS measurements, suggesting that atmospheric correction by convection-permitting WRF simulations initialized with mesoscale data assimilation may effectively mitigate atmospheric distortion in InSAR measurements, especially for coastal areas.

Subseasonal Forecasting with an Icosahedral, Vertically Quasi-Lagrangian Coupled Model. Part I: Model Overview and Evaluation of Systematic Errors

AbstractThe atmospheric hydrostatic Flow-Following Icosahedral Model (FIM), developed for medium-range weather prediction, provides a unique three-dimensional grid structure—a quasi-uniform icosahe...

Subseasonal Forecasting with an Icosahedral, Vertically Quasi-Lagrangian Coupled Model. Part II: Probabilistic and Deterministic Forecast Skill

AbstractSubseasonal forecast skill of the global hydrostatic atmospheric Flow-Following Icosahedral Model (FIM) coupled to an icosahedral-grid version of the Hybrid Coordinate Ocean Model (iHYCOM) ...