scholarly journals A Probabilistic Tropical Cyclone Track Forecast Scheme Based on the Selective Consensus of Ensemble Prediction Systems

2017 ◽  
Vol 32 (6) ◽  
pp. 2143-2157 ◽  
Author(s):  
Xiping Zhang ◽  
Hui Yu
Keyword(s):  
Tropical Cyclone ◽  
Ensemble Prediction ◽  
Lead Times ◽  
Track Forecast ◽  
Forecast Errors ◽  
Forecast Uncertainty ◽  
Ensemble Prediction System ◽  
The Mean ◽  
Environmental Prediction ◽  
Uncertainty Information

Abstract Selective consensus and a grand ensemble based on an ensemble prediction system (EPS) have been found to be effective in improving deterministic tropical cyclone (TC) track forecasts, while little attention has been paid to quantitative applications of the forecast uncertainty information provided by EPSs. In this paper the forecast uncertainty information is evaluated for two operational EPSs and their grand ensemble. Then, a probabilistic TC track forecast scheme is proposed based on the selective consensus of the two EPSs; this scheme is composed of member picking, mean track shifting, and probability ellipses. The operational EPSs are from the European Centre for Medium-Range Weather Forecasts (ECMWF-EPS) and the National Centers for Environmental Prediction (NCEP-GEFS). Evaluation exhibits that the hit ratios of ECMWF-EPS are above 80% for the 70% probability ellipses at all lead times until 120 h and are used in the proposed scheme. The other components of the proposed scheme are about picking potentially good EPS members. A picking ratio of 1/2 is found to be the best choice, and the member-picking technique is used for the grand ensemble but only for lead times out to 48 h. For lead times longer than 48 h, all of the grand ensemble members are used in obtaining the mean track. The effectiveness of the proposed scheme shows a 10% improvement in the mean track forecast errors over the grand ensemble and a 4.5% improvement in the hit ratio of 70% probability ellipses over the ECMWF-EPS at 24 h, demonstrating its good potential to be applied in operations.

scholarly journals Novel Metrics for Evaluation of Ensemble Forecasts of Tropical Cyclone Structure

2009 ◽  
Vol 137 (9) ◽  
pp. 2830-2850 ◽  
Author(s):  
Daniel Veren ◽  
Jenni L. Evans ◽  
Sarah Jones ◽  
Francesca Chiaromonte
Keyword(s):  
Tropical Cyclone ◽  
Forecast Accuracy ◽  
Ensemble Member ◽  
Life Cycles ◽  
Ensemble Prediction ◽  
Structure Evolution ◽  
Track Forecast ◽  
Forecast Errors ◽  
Reference Structure ◽  
Ensemble Prediction System

Abstract Predicting extratropical transition (ET) of a tropical cyclone poses a significant challenge to numerical forecast models because the storm evolution depends on both the timing of the phasing between the tropical cyclone and midlatitude weather systems and the structures of each system. Ensemble prediction systems offer the potential for assessing confidence in numerical guidance during ET cases. Thus, forecasts of storm structure changes during ET from the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system (EPS) are explored using two novel validation approaches. The evolution of the (initially tropical) storm structure is characterized in the framework of the cyclone phase space (CPS) and the validation metrics are based on separation between the EPS forecasts and verifying analyses in the CPS. The first validation approach utilizes two metrics and most closely resembles traditional forecast validation techniques. The second approach involves clustering the ensemble member initializations and operational analyses during the life cycles of each tropical cyclone to provide a reference structure evolution against which to evaluate the EPS forecasts. Application of these metrics is demonstrated for two case studies of ET in the western North Pacific: Typhoons Tokage (2004) and Maemi (2003). Both validation approaches identify a decline in EPS structure forecast accuracy for all valid times coinciding with ET onset and beyond, as well as during a weakening tropical stage prior to ET for Tokage. While track forecast errors contribute to structure errors in the EPS forecasts, they are not an overwhelming factor. The two validation approaches highlight the inability of ensemble member forecasts to appropriately weaken the warm core prior to and during ET, and the effects this has on forecasts of ET timing. The analyses adopted in this study provide a basis for future assessments of ensemble forecast skill of cyclone structure during ET.

OBEST: An Observation-Based Ensemble Subsetting Technique for Tropical Cyclone Track Prediction

2016 ◽  
Vol 31 (1) ◽  
pp. 57-70 ◽  
Author(s):  
Lin Dong ◽  
Fuqing Zhang
Keyword(s):  
Tropical Cyclone ◽  
Lead Times ◽  
Track Forecast ◽  
Forecast Errors ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Weather Forecasts ◽  
Ensemble Mean ◽  
Medium Range ◽  
Environmental Prediction

Abstract An observation-based ensemble subsetting technique (OBEST) is developed for tropical cyclone track prediction in which a subset of members from either a single- or multimodel ensemble is selected based on the distance from the latest best-track position. The performance of OBEST is examined using both the 2-yr hindcasts for 2010–11 and the 2-yr operational predictions during 2012–13. It is found that OBEST outperforms both the simple ensemble mean (without subsetting) and the corresponding deterministic high-resolution control forecast for most forecast lead times up to 5 days. Applying OBEST to a superensemble of global ensembles from both the European Centre for Medium-Range Weather Forecasts and the National Centers for Environmental Prediction yielded a further reduction in track forecast errors by 5%–10% for lead times of 24–120 h.

Extended Prediction of North Indian Ocean Tropical Cyclones

2012 ◽  
Vol 27 (3) ◽  
pp. 757-769 ◽  
Author(s):  
James I. Belanger ◽  
Peter J. Webster ◽  
Judith A. Curry ◽  
Mark T. Jelinek
Keyword(s):  
Tropical Cyclone ◽  
Indian Ocean ◽  
Tropical Cyclones ◽  
North Indian Ocean ◽  
Ensemble Prediction ◽  
Tropical Cyclone Genesis ◽  
Lead Times ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
The North

Abstract This analysis examines the predictability of several key forecasting parameters using the ECMWF Variable Ensemble Prediction System (VarEPS) for tropical cyclones (TCs) in the North Indian Ocean (NIO) including tropical cyclone genesis, pregenesis and postgenesis track and intensity projections, and regional outlooks of tropical cyclone activity for the Arabian Sea and the Bay of Bengal. Based on the evaluation period from 2007 to 2010, the VarEPS TC genesis forecasts demonstrate low false-alarm rates and moderate to high probabilities of detection for lead times of 1–7 days. In addition, VarEPS pregenesis track forecasts on average perform better than VarEPS postgenesis forecasts through 120 h and feature a total track error growth of 41 n mi day−1. VarEPS provides superior postgenesis track forecasts for lead times greater than 12 h compared to other models, including the Met Office global model (UKMET), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Global Forecasting System (GFS), and slightly lower track errors than the Joint Typhoon Warning Center. This paper concludes with a discussion of how VarEPS can provide much of this extended predictability within a probabilistic framework for the region.

scholarly journals Verification of Ensemble-Based Uncertainty Circles around Tropical Cyclone Track Forecasts

2011 ◽  
Vol 26 (5) ◽  
pp. 664-676 ◽  
Author(s):  
Thierry Dupont ◽  
Matthieu Plu ◽  
Philippe Caroff ◽  
Ghislain Faure
Keyword(s):  
Tropical Cyclone ◽  
Large Error ◽  
Ensemble Prediction ◽  
Probabilistic Forecasting ◽  
Cyclone Track ◽  
Ensemble Prediction System ◽  
Weather Forecasts ◽  
Probabilistic Forecasts ◽  
Medium Range ◽  
Uncertainty Information

Abstract Several tropical cyclone forecasting centers issue uncertainty information with regard to their official track forecasts, generally using the climatological distribution of position error. However, such methods are not able to convey information that depends on the situation. The purpose of the present study is to assess the skill of the Ensemble Prediction System (EPS) from the European Centre for Medium-Range Weather Forecasts (ECMWF) at measuring the uncertainty of up to 3-day track forecasts issued by the Regional Specialized Meteorological Centre (RSMC) La Réunion in the southwestern Indian Ocean. The dispersion of cyclone positions in the EPS is extracted and translated at the RSMC forecast position. The verification relies on existing methods for probabilistic forecasts that are presently adapted to a cyclone-position metric. First, the probability distribution of forecast positions is compared to the climatological distribution using Brier scores. The probabilistic forecasts have better scores than the climatology, particularly after applying a simple calibration scheme. Second, uncertainty circles are built by fixing the probability at 75%. Their skill at detecting small and large error values is assessed. The circles have some skill for large errors up to the 3-day forecast (and maybe after); but the detection of small radii is skillful only up to 2-day forecasts. The applied methodology may be used to assess and to compare the skill of different probabilistic forecasting systems of cyclone position.

scholarly journals Track Uncertainty in High-Resolution HWRF Ensemble Forecasts of Hurricane Joaquin

2019 ◽  
Vol 34 (6) ◽  
pp. 1889-1908 ◽  
Author(s):  
Ghassan J. Alaka ◽  
Xuejin Zhang ◽  
Sundararaman G. Gopalakrishnan ◽  
Zhan Zhang ◽  
Frank D. Marks ◽  
...  
Keyword(s):  
High Resolution ◽  
Vortex Structure ◽  
The United States ◽  
Ensemble Prediction ◽  
Track Forecast ◽  
Synoptic Scale ◽  
Forecast Uncertainty ◽  
The Bahamas ◽  
Ensemble Prediction System ◽  
Steering Flow

Abstract Hurricane Joaquin (2015) was characterized by high track forecast uncertainty when it approached the Bahamas from 29 September 2015 to 1 October 2015, with 5-day track predictions ranging from landfall in the United States to east of Bermuda. The source of large track spread in Joaquin forecasts is investigated using an ensemble prediction system (EPS) based on the Hurricane Weather Research and Forecasting (HWRF) Model. For the first time, a high-resolution analysis of an HWRF-based EPS is performed to isolate the factors that control tropical cyclone (TC) track uncertainty. Differences in the synoptic-scale environment, the TC vortex structure, and the TC location are evaluated to understand the source of track forecast uncertainty associated with Joaquin, especially at later lead times when U.S. landfall was possible. EPS members that correctly propagated Joaquin into the central North Atlantic are compared with members that incorrectly predicted U.S. landfall. Joaquin track forecasts were highly dependent on the evolution of the environment, including weak atmospheric steering flow near the Bahamas and three synoptic-scale systems: a trough over North America, a ridge to the northeast of Joaquin, and an upper-tropospheric trough to the east of Joaquin. Differences in the steering flow were associated with perturbations of the synoptic-scale environment at the model initialization time. Ultimately, members that produced a more progressive midlatitude synoptic-scale pattern had reduced track errors. Joaquin track forecast uncertainty was not sensitive to the TC vortex structure or the initial TC position.

scholarly journals Hydrometeorological Ensemble Forecast of a Highly Localized Convective Event in the Mediterranean

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1545
Author(s):  
Luca Furnari ◽  
Giuseppe Mendicino ◽  
Alfonso Senatore
Keyword(s):  
Ensemble Prediction ◽  
Lead Times ◽  
Forecast Uncertainty ◽  
Ensemble Prediction System ◽  
Distributed Information ◽  
Convective Event ◽  
Spatially Distributed ◽  
Accumulated Rainfall ◽  
Clear Information

The uncertainties that affect hydrometeorological modelling chains can be addressed through ensemble approaches. In this paper, a convection-permitting ensemble system was assessed based on the downscaling of all members of the ECMWF ensemble prediction system through the coupled atmospheric-hydrological WRF-Hydro modelling system. An exemplary highly localized convective event that occurred in a morphologically complex area of the southern Italian coast was selected as a case study, evaluating the performance of the system for two consecutive lead times up to the hydrological forecast on a very small (11.4 km2) catchment. The proposed approach accurately downscales the signal provided by the global model, improving up to almost 200% the quantitative forecast of the accumulated rainfall peak in the area affected by the event and supplying clear information about the forecast uncertainty. Some members of the ensemble simulations provide accurate results up to the hydrological scale over the catchment, with unit peak discharge forecasts up to 3 m3∙s−1∙km−2. Overall, the study highlights that for highly localized convective events in coastal Mediterranean catchments, ensemble approaches should be preferred to a classic single-based simulation approach, because they improve the forecast skills and provide spatially distributed information about the forecast uncertainty, which can be particularly useful for operational purposes.

Track Dependence of Tropical Cyclone Intensity Forecast Errors in the COAMPS-TC Model

2021 ◽  
Author(s):  
Chanh Kieu ◽  
Cole Evans ◽  
Yi Jin ◽  
James D. Doyle ◽  
Hao Jin ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Numerical Models ◽  
Intensity Variation ◽  
Absolute Intensity ◽  
Mature Stage ◽  
Lead Times ◽  
Track Forecast ◽  
Forecast Errors ◽  
Intensity Forecast ◽  
Tc Model

AbstractThis study examines the dependence of tropical cyclone (TC) intensity forecast errors on track forecast errors in the Coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) model. Using real-time forecasts and retrospective experiments during 2015-2018, verification of TC intensity errors conditioned on different 5-day track error thresholds shows that reducing the 5-day track errors by 50-70% can help reduce the absolute intensity errors by 18-20% in the 2018 version of the COAMPS-TC model. Such impacts of track errors on the TC intensity errors are most persistent at 4-5 day lead times in all three major ocean basins, indicating a significant control of global models on the forecast skill of the COAMPS-TC model. It is of interest to find, however, that lowering the 5-day track errors below 80 nm does not reduce TC absolute intensity errors further. Instead, the 4-5 day intensity errors appear to be saturated at around 10-12 kt for cases with small track errors, thus suggesting the existence of some inherent intensity errors in regional models.Additional idealized simulations under a perfect model scenario reveal that the COAMPS-TC model possesses an intrinsic intensity variation at the TC mature stage in the range of 4-5 kt, regardless of the large-scale environment. Such intrinsic intensity variability in the COAMPS-TC model highlights the importance of potential chaotic TC dynamics, rather than model deficiencies, in determining TC intensity errors at 4-5 day lead times. These results indicate a fundamental limit in the improvement of TC intensity forecasts by numerical models that one should consider in future model development and evaluation.

scholarly journals A comparison of predictors of the error of weather forecasts

2005 ◽  
Vol 12 (6) ◽  
pp. 1021-1032 ◽  
Author(s):  
M. S. Roulston
Keyword(s):  
Forecast Error ◽  
Absolute Error ◽  
Ensemble Prediction ◽  
Lead Times ◽  
Ensemble Spread ◽  
Spatial Error ◽  
Ensemble Prediction System ◽  
Error Covariance ◽  
The Mean ◽  
Local Gradient

Abstract. Three different potential predictors of forecast error - ensemble spread, mean errors of recent forecasts and the local gradient of the predicted field - were compared. The comparison was performed using the forecasts of 500hPa geopotential and 2-m temperature of the ECMWF ensemble prediction system at lead times of 96, 168 and 240h, over North America for each day in 2004. Ensemble spread was found to be the best overall predictor of absolute forecast error. The mean absolute error of recent forecasts (past 30 days) was found to contain some information, however, and the local gradient of the geopotential also provided some information about the error in the prediction of this variable. Ensemble spatial error covariance and the mean spatial error covariance of recent forecasts (past 30 days) were also compared as predictors of actual spatial error covariance. Both were found to provide some predictive information, although the ensemble error covariance was found to provide substantially more information for both variables tested at all three lead times. The results of the study suggest that past errors and local field gradients should not be ignored as predictors of forecast error as they can be computed cheaply from single forecasts when an ensemble is not available. Alternatively, in some cases, they could be used to supplement the information about forecast error provided by an ensemble to provide a better prediction of forecast skill.

A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction Systems

2005 ◽  
Vol 133 (5) ◽  
pp. 1076-1097 ◽  
Author(s):  
Roberto Buizza ◽  
P. L. Houtekamer ◽  
Gerald Pellerin ◽  
Zoltan Toth ◽  
Yuejian Zhu ◽  
...  
Keyword(s):  
Ensemble Forecasting ◽  
Ensemble Prediction ◽  
Forecast Errors ◽  
Ensemble Forecasts ◽  
Ensemble Prediction System ◽  
Weather Forecasts ◽  
Prediction Systems ◽  
Environmental Prediction ◽  
Global Systems

Abstract The present paper summarizes the methodologies used at the European Centre for Medium-Range Weather Forecasts (ECMWF), the Meteorological Service of Canada (MSC), and the National Centers for Environmental Prediction (NCEP) to simulate the effect of initial and model uncertainties in ensemble forecasting. The characteristics of the three systems are compared for a 3-month period between May and July 2002. The main conclusions of the study are the following:the performance of ensemble prediction systems strongly depends on the quality of the data assimilation system used to create the unperturbed (best) initial condition and the numerical model used to generate the forecasts;a successful ensemble prediction system should simulate the effect of both initial and model-related uncertainties on forecast errors; andfor all three global systems, the spread of ensemble forecasts is insufficient to systematically capture reality, suggesting that none of them is able to simulate all sources of forecast uncertainty.The relative strengths and weaknesses of the three systems identified in this study can offer guidelines for the future development of ensemble forecasting techniques.

scholarly journals An analysis of uncertainties and skill in forecasts of winter storm losses

2016 ◽  
Vol 16 (11) ◽  
pp. 2391-2402 ◽  
Author(s):  
Tobias Pardowitz ◽  
Robert Osinski ◽  
Tim Kruschke ◽  
Uwe Ulbrich
Keyword(s):  
Model Uncertainty ◽  
Damage Model ◽  
Calibration Method ◽  
Ensemble Prediction ◽  
Brier Score ◽  
Lead Times ◽  
Storm Damage ◽  
Winter Storm ◽  
Forecast Uncertainty ◽  
Ensemble Prediction System

Abstract. This paper describes an approach to derive probabilistic predictions of local winter storm damage occurrences from a global medium-range ensemble prediction system (EPS). Predictions of storm damage occurrences are subject to large uncertainty due to meteorological forecast uncertainty (typically addressed by means of ensemble predictions) and uncertainties in modelling weather impacts. The latter uncertainty arises from the fact that local vulnerabilities are not known in sufficient detail to allow for a deterministic prediction of damages, even if the forecasted gust wind speed contains no uncertainty. Thus, to estimate the damage model uncertainty, a statistical model based on logistic regression analysis is employed, relating meteorological analyses to historical damage records. A quantification of the two individual contributions (meteorological and damage model uncertainty) to the total forecast uncertainty is achieved by neglecting individual uncertainty sources and analysing resulting predictions. Results show an increase in forecast skill measured by means of a reduced Brier score if both meteorological and damage model uncertainties are taken into account. It is demonstrated that skilful predictions on district level (dividing the area of Germany into 439 administrative districts) are possible on lead times of several days. Skill is increased through the application of a proper ensemble calibration method, extending the range of lead times for which skilful damage predictions can be made.

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