Predicting Hurricane Intensity and Associated Hazards: A Five-Year Real-Time Forecast Experiment with Assimilation of Airborne Doppler Radar Observations

2015 ◽  
Vol 96 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Fuqing Zhang ◽  
Yonghui Weng
Keyword(s):  
Inner Core ◽  
Doppler Radar ◽  
Surface Wind ◽  
Forecast Errors ◽  
Hurricane Intensity ◽  
Radar Observations ◽  
Intensity Forecast ◽  
Probabilistic Forecasts ◽  
Atlantic Hurricanes ◽  
Airborne Doppler Radar

Abstract Performance in the prediction of hurricane intensity and associated hazards has been evaluated for a newly developed convection-permitting forecast system that uses ensemble data assimilation techniques to ingest high-resolution airborne radar observations from the inner core. This system performed well for three of the ten costliest Atlantic hurricanes: Ike (2008), Irene (2011), and Sandy (2012). Four to five days before these storms made landfall, the system produced good deterministic and probabilistic forecasts of not only track and intensity, but also of the spatial distributions of surface wind and rainfall. Averaged over all 102 applicable cases that have inner-core airborne Doppler radar observations during 2008–2012, the system reduced the day-2-to-day-4 intensity forecast errors by 25%–28% compared to the corresponding National Hurricane Center’s official forecasts (which have seen little or no decrease in intensity forecast errors over the past two decades). Empowered by sufficient computing resources, advances in both deterministic and probabilistic hurricane prediction will enable emergency management officials, the private sector, and the general public to make more informed decisions that minimize the losses of life and property.

scholarly journals Understanding Error Distributions of Hurricane Intensity Forecasts during Rapid Intensity Changes

2020 ◽  
Vol 35 (6) ◽  
pp. 2219-2234
Author(s):  
Benjamin C. Trabing ◽  
Michael M. Bell
Keyword(s):  
Inner Core ◽  
Forecast Error ◽  
Vertical Wind Shear ◽  
Probability Of Detection ◽  
Intensity Change ◽  
Forecast Errors ◽  
Hurricane Intensity ◽  
East Pacific ◽  
Intensity Forecast ◽  
Error Distributions

AbstractThe characteristics of official National Hurricane Center (NHC) intensity forecast errors are examined for the North Atlantic and east Pacific basins from 1989 to 2018. It is shown how rapid intensification (RI) and rapid weakening (RW) influence yearly NHC forecast errors for forecasts between 12 and 48 h in length. In addition to being the tail of the intensity change distribution, RI and RW are at the tails of the forecast error distribution. Yearly mean absolute forecast errors are positively correlated with the yearly number of RI/RW occurrences and explain roughly 20% of the variance in the Atlantic and 30% in the east Pacific. The higher occurrence of RI events in the east Pacific contributes to larger intensity forecast errors overall but also a better probability of detection and success ratio. Statistically significant improvements to 24-h RI forecast biases have been made in the east Pacific and to 24-h RW biases in the Atlantic. Over-ocean 24-h RW events cause larger mean errors in the east Pacific that have not improved with time. Environmental predictors from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) are used to diagnose what conditions lead to the largest RI and RW forecast errors on average. The forecast error distributions widen for both RI and RW when tropical systems experience low vertical wind shear, warm sea surface temperature, and moderate low-level relative humidity. Consistent with existing literature, the forecast error distributions suggest that improvements to our observational capabilities, understanding, and prediction of inner-core processes is paramount to both RI and RW prediction.

Inner Core Structure of Hurricane Alicia from Airborne Doppler Radar Observations

1987 ◽  
Vol 44 (9) ◽  
pp. 1296-1317 ◽  
Author(s):  
Frank D. Marks ◽  
Robert A. Houze
Keyword(s):  
Inner Core ◽  
Doppler Radar ◽  
Core Structure ◽  
Radar Observations ◽  
Airborne Doppler Radar

The Effects of Sampling Errors on the EnKF Assimilation of Inner-Core Hurricane Observations

2014 ◽  
Vol 142 (4) ◽  
pp. 1609-1630 ◽  
Author(s):  
Jonathan Poterjoy ◽  
Fuqing Zhang ◽  
Yonghui Weng
Keyword(s):  
Data Assimilation ◽  
Hurricane Katrina ◽  
Inner Core ◽  
Doppler Radar ◽  
Mesoscale Model ◽  
Outer Core ◽  
State Variables ◽  
Sampling Errors ◽  
Relaxation Coefficient ◽  
Airborne Doppler Radar

Abstract Atmospheric data assimilation methods that estimate flow-dependent forecast statistics from ensembles are sensitive to sampling errors. This sensitivity is investigated in the context of vortex-scale hurricane data assimilation by cycling an ensemble Kalman filter to assimilate observations with a convection-permitting mesoscale model. In a set of numerical experiments, airborne Doppler radar observations are assimilated for Hurricane Katrina (2005) using an ensemble size that ranges from 30 to 300 members, and a varying degree of covariance inflation through relaxation to the prior. The range of ensemble sizes is shown to produce variations in posterior storm structure that persist for days in deterministic forecasts, with the most substantial differences appearing in the vortex outer-core wind and pressure fields. Ensembles with 60 or more members converge toward similar axisymmetric and asymmetric inner-core solutions by the end of the cycling, while producing qualitatively similar sample correlations between the state variables. Though covariance relaxation has little impact on model variables far from the observations, the structure of the inner-core vortex can benefit from a more optimal tuning of the relaxation coefficient. Results from this study provide insight into how sampling errors may affect the performance of an ensemble hurricane data assimilation system during cycling.

scholarly journals Reducing Operational Hurricane Intensity Forecast Errors during Eyewall Replacement Cycles

2016 ◽  
Vol 31 (2) ◽  
pp. 601-608 ◽  
Author(s):  
James P. Kossin ◽  
Mark DeMaria
Keyword(s):  
Forecast Error ◽  
Intensity Change ◽  
Forecast Errors ◽  
Hurricane Intensity ◽  
Intensity Forecast ◽  
Prediction Scheme ◽  
Hurricane Prediction ◽  
Eyewall Replacement Cycles ◽  
National Hurricane Center ◽  
Intensity Evolution

Abstract Eyewall replacement cycles (ERCs) are fairly common events in tropical cyclones (TCs) of hurricane intensity or greater and typically cause large and sometimes rapid changes in the intensity evolution of the TC. Although the details of the intensity evolution associated with ERCs appear to have some dependence on the ambient environmental conditions that the TCs move through, these dependencies can also be quite different than those of TCs that are not undergoing an ERC. For example, the Statistical Hurricane Prediction Scheme (SHIPS), which is used in National Hurricane Center operations and provides intensity forecast skill that is, on average, equal to or greater than deterministic numerical model skill, typically identifies an environment that is not indicative of weakening during the onset and subsequent evolution of an ERC. Contrarily, a period of substantial weakening does typically begin near the onset of an ERC, and this disparity can cause large SHIPS intensity forecast errors. Here, a simple model based on a climatology of ERC intensity change is introduced and tested against SHIPS. It is found that the application of the model can reduce intensity forecast error substantially when applied at, or shortly after, the onset of ERC weakening.

scholarly journals Doppler Radar Observations of a Wintertime Anticyclonic Misocyclone Associated with Surface Wind Gust on the Coast of the Sea of Japan

SOLA ◽  
2019 ◽  
Vol 15 (0) ◽  
pp. 234-237
Author(s):  
Kenichi Kusunoki ◽  
Ken-ichiro Arai ◽  
Hanako Y. Inoue ◽  
Chusei Fujiwara
Keyword(s):  
Sea Of Japan ◽  
Doppler Radar ◽  
Surface Wind ◽  
The Sea Of Japan ◽  
Wind Gust ◽  
Radar Observations

scholarly journals On the Use of Dual-Doppler Radar Measurements for Very Short-Term Wind Power Forecasts

2018 ◽  
Vol 10 (11) ◽  
pp. 1701 ◽  
Author(s):  
Laura Valldecabres ◽  
Nicolai Nygaard ◽  
Luis Vera-Tudela ◽  
Lueder von Bremen ◽  
Martin Kühn
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Electricity Market ◽  
Doppler Radar ◽  
Short Term ◽  
Radar Observations ◽  
Spatial Coverage ◽  
Probabilistic Forecasts ◽  
Dual Doppler Radar

Very short-term forecasts of wind power provide electricity market participants with extremely valuable information, especially in power systems with high penetration of wind energy. In very short-term horizons, statistical methods based on historical data are frequently used. This paper explores the use of dual-Doppler radar observations of wind speed and direction to derive five-minute ahead deterministic and probabilistic forecasts of wind power. An advection-based technique is introduced, which estimates the predictive densities of wind speed at the target wind turbine. In a case study, the proposed methodology is used to forecast the power generated by seven turbines in the North Sea with a temporal resolution of one minute. The radar-based forecast outperforms the persistence and climatology benchmarks in terms of overall forecasting skill. Results indicate that when a large spatial coverage of the inflow of the wind turbine is available, the proposed methodology is also able to generate reliable density forecasts. Future perspectives on the application of Doppler radar observations for very short-term wind power forecasting are discussed in this paper.

scholarly journals A Latent Heat Retrieval and Its Effects on the Intensity and Structure Change of Hurricane Guillermo (1997). Part II: Numerical Simulations

2012 ◽  
Vol 69 (11) ◽  
pp. 3128-3146 ◽  
Author(s):  
Stephen R. Guimond ◽  
Jon M. Reisner
Keyword(s):  
Numerical Simulations ◽  
Tropical Cyclones ◽  
Latent Heat ◽  
Inner Core ◽  
Doppler Radar ◽  
Model Parameters ◽  
Saturation State ◽  
Wind Structure ◽  
Tangential Wind ◽  
Airborne Doppler Radar

Abstract In Part I of this study, a new algorithm for retrieving the latent heat field in tropical cyclones from airborne Doppler radar was presented and fields from rapidly intensifying Hurricane Guillermo (1997) were shown. In Part II, the usefulness and relative accuracy of the retrievals is assessed by inserting the heating into realistic numerical simulations at 2-km resolution and comparing the generated wind structure to the radar analyses of Guillermo. Results show that using the latent heat retrievals as forcing produces very low intensity and structure errors (in terms of tangential wind speed errors and explained wind variance) and significantly improves simulations relative to a predictive run that is highly calibrated to the latent heat retrievals by using an ensemble Kalman filter procedure to estimate values of key model parameters. Releasing all the heating/cooling in the latent heat retrieval results in a simulation with a large positive bias in Guillermo’s intensity that motivates the need to determine the saturation state in the hurricane inner-core retrieval through a procedure similar to that described in Part I of this study. The heating retrievals accomplish high-quality structure statistics by forcing asymmetries in the wind field with the generally correct amplitude, placement, and timing. In contrast, the latent heating fields generated in the predictive simulation contain a significant bias toward large values and are concentrated in bands (rather than discrete cells) stretched around the vortex. The Doppler radar–based latent heat retrievals presented in this series of papers should prove useful for convection initialization and data assimilation to reduce errors in numerical simulations of tropical cyclones.

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