Performance of convection‐permitting hurricane initialization and prediction during 2008–2010 with ensemble data assimilation of inner‐core airborne Doppler radar observations

Zhang, Fuqing; Weng, Yonghui; Gamache, John F.; Marks, Frank D.

doi:10.1029/2011gl048469

Cited by 159 publications

(147 citation statements)

References 25 publications

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“…Accounting for uncertainties in the wind forcing is essential for practical short-and long-range storm surge forecast operations and this problem will be addressed in future work. One straightforward way to do that is to use the meteorological uncertainties from weather ensemble analysis and forecasts, which are now produced in real time (Zhang et al 2011), to force ensemble storm surge forecasts. Other input parameters to ADCIRC, such as bathymetry and bottom friction, could also change the trajectory of the surge under identical forcing terms.…”

Section: Discussionmentioning

confidence: 99%

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Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

Altaf

Butler

Luo

et al. 2013

Monthly Weather Review

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This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H ' filter. By design, an H ' filter is more robust than the common Kalman filter in the sense that the estimation error in the H ' filter has, in general, a finite growth rate with respect to the uncertainties in assimilation. The computational hydrodynamical model used in this study is the Advanced Circulation (ADCIRC) model. The authors assimilate data obtained from Hurricanes Katrina and Ike as test cases. The results clearly show that the H ' -based SEIK filter provides more accurate short-range forecasts of storm surge compared to recently reported data assimilation results resulting from the standard SEIK filter.

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Section: Discussionmentioning

confidence: 99%

“…Covariance inflation is often implemented by postmultiplication of the forecast or analysis error covariance matrix by a constant factor larger than 1. Other inflation schemes have been also proposed through, for example, relaxation to prior (Zhang et al 2004) or using a multimodel multiphysics approach (Meng and Zhang 2007).…”

Section: Introductionmentioning

confidence: 99%

Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

Altaf

Butler

Luo

et al. 2013

Monthly Weather Review

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“…Munsell and Zhang [6] presented the details of the WRF-EnKF Sandy runs, extending the analysis of Weng and Zhang [5] and Zhang et al [15]. The EnKF system used an ensemble of WRF forecasts to estimate flow-dependent background error covariance for the data assimilation cycling.…”

Section: Methodsmentioning

confidence: 99%

Exploring Water Level Sensitivity for Metropolitan New York during Sandy (2012) Using Ensemble Storm Surge Simulations

Colle

Bowman

Roberts

et al. 2015

JMSE

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This paper describes storm surge simulations made for Sandy (2012) for the Metropolitan New York (NYC) area using the Advanced Circulation (ADCIRC) model forced by the Weather Research and Forecasting (WRF) model. The atmospheric forecast uncertainty was quantified using 11-members from an atmospheric Ensemble Kalman Filter (EnKF) system. A control WRF member re-initialized every 24 h demonstrated the capability of the WRF-ADCIRC models to realistically simulate the 2.83 m surge and 4.40 m storm tide (surge + astronomical tide) above mean lower low water (MLLW) for NYC. Starting about four days before landfall, an ensemble of model runs based on the 11 "best" meteorological predictions illustrate how modest changes in the track (20-100 km) and winds (3-5 m s flooding was not the worst case for this particular event. Had Sandy made landfall at differing times, locations and stages of the tide, peak water levels could have been up to 0.5 m higher than experienced.

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“…This is, in part, attributed to our limited understanding of the physical mechanisms that are responsible for the changes of TC intensity (e.g., Emanuel, 2000;Wang and Wu, 2004), and both the practical and intrinsic predictability under the current generation of numerical models and observing networks for the TCs (e.g., Zhang and Sippel, 2009;Zhang et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Environmental influences on the intensity changes of tropical cyclones over the western North Pacific

et al. 2014

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Abstract. The influence of environmental conditions on the intensity changes of tropical cyclones (TCs) over the western North Pacific (WNP) is investigated through examination of 37 TCs during 2000-2011 that interacted directly with the western North Pacific subtropical high (WNPSH). Comprehensive composite analysis of the environmental conditions is performed for two stages of storms: one is categorized as intensifying events (maximum wind speed increases by 15 kn over 48 h) and the other is categorized as weakening events (maximum wind speed decreases by 15 kn over 48 h). Comparison of the composite analysis of these two cases show that environmental conditions associated with the WNPSH play important roles in the intensity changes of TCs over the WNP. When a TC moves along the southern periphery of the WNPSH, the relatively weaker easterly environmental vertical wind shear helps bring warm moist air from the south and southeast to its southeast quadrant within 500 km, which is favorable for the TC to intensify. However, when a TC moves along the western edge of the WNPSH, under the combined influences of the WNPSH and an upper-level westerly trough, a strong westerly vertical shear promotes the intrusion of dry environmental air associated with the WNPSH from the north and northwest, which may lead to the inhibition of moisture supply and convection over the western half of the TC and thus its weakening. These composite results are consistent with those with additional geographic restrictions, suggesting that the dry air intrusion and the vertical wind shear (VWS) associated with the WNPSH, indeed affect the intensity changes of TCs over the WNP beyond the difference related solely to variations in geographical locations. The average sea surface temperature (SST) of 27.6 • C for the weakening events is also lower than an average of 28.9 • C for the strengthening events, but remains above the critical value of 27 • C for TC intensification, suggesting that the SST may be regarded as a less positive factor for the weakening events.

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Performance of convection‐permitting hurricane initialization and prediction during 2008–2010 with ensemble data assimilation of inner‐core airborne Doppler radar observations

Cited by 159 publications

References 25 publications

Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

Exploring Water Level Sensitivity for Metropolitan New York during Sandy (2012) Using Ensemble Storm Surge Simulations

Environmental influences on the intensity changes of tropical cyclones over the western North Pacific

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