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 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.

Have We Reached the Limits of Predictability for Tropical Cyclone Track Forecasting?

2018 ◽  
Vol 99 (11) ◽  
pp. 2237-2243 ◽  
Author(s):  
Christopher W. Landsea ◽  
John P. Cangialosi
Keyword(s):  
Tropical Cyclone ◽  
Initial Conditions ◽  
Forecast Accuracy ◽  
The United States ◽  
Track Forecast ◽  
Synoptic Scale ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Atmospheric Sciences ◽  
Steering Flow

AbstractThe tropical cyclone is the largest single-day-impact meteorological event in the United States and worldwide through its effects from storm surge, extreme winds, freshwater flooding, and embedded tornadoes. Fortunately, over the last three decades there have been incredible advances in forecast accuracy, especially for the track of the tropical cyclone’s center. Errors have been cut by two-thirds in just 25 years due to global modeling advances, data assimilation improvements, dramatic increases in observations primarily derived from satellite platforms, and use of ensemble forecast techniques. These four factors have allowed for highly accurate synoptic-scale atmospheric initial conditions and forecasts of the steering flow out through several days into the future. However, such improvements cannot continue indefinitely. It is well known in the atmospheric sciences that there exists an inherent “limit of predictability” because of errors at the smallest scales (microscale—meters and seconds) that eventually cascade up to the largest scales (synoptic scale—thousands of kilometers and several days). While there have been estimates of the limits of predictability for tropical cyclone track prediction in the past, our current capabilities have exceeded those somewhat pessimistic earlier outlooks. This essay discusses the current state of the art for tropical cyclone track prediction and reassesses whether reaching the “limit of predictability” is imminent. The ramifications of this eventual conclusion—whether in the short-term or still decades away—could be critical for all users of tropical cyclone track forecast information, including the emergency management community/governments, the media, the private sector, and the general public.

Case Dependence of Multiscale Interactions between Multisource Perturbations for Convection-Permitting Ensemble Forecasting during SCMREX

2021 ◽  
Author(s):  
Xubin Zhang
Keyword(s):  
Perturbation Methods ◽  
Monsoon Rainfall ◽  
Southern China ◽  
Ensemble Forecasting ◽  
Ensemble Prediction ◽  
Synoptic Scale ◽  
Ensemble Prediction System ◽  
Control Member ◽  
Probabilistic Forecasts ◽  
Perturbation Energy

AbstractThis study examines the case dependence of the multiscale characteristics of initial condition (IC) and model physics (MO) perturbations and their interactions in a convection-permitting ensemble prediction system (CPEPS), focusing on the 12-h forecasts of precipitation perturbation energy. The case dependence of forecast performances of various ensemble configurations is also examined to gain guidance for CPEPS design. Heavy-rainfall cases over Southern China during the Southern China Monsoon Rainfall Experiment (SCMREX) in May 2014 were discriminated between the strongly and weakly forced events in terms of synoptic-scale forcing, each of which included 10 cases. In the cases with weaker forcing, MO perturbations showed larger influences while the enhancements of convective activities relative to the control member due to IC perturbations were less evident, leading to smaller dispersion reduction due to adding MO perturbations to IC perturbations. Such dispersion reduction was more sensitive to IC and MO perturbation methods in the weakly and strongly forced cases, respectively. The dispersion reduction improved the probabilistic forecasts of precipitation, with more evident improvements in the cases with weaker forcing. To improve the benefits of dispersion reduction in forecasts, it is instructive to elaborately consider the case dependence of dispersion reduction, especially the various sensitivities of dispersion reduction to different-source perturbation methods in various cases, in CPEPS design.

Impacts of Assimilating High-Resolution Atmospheric Motion Vectors Derived from Himawari-8 on Tropical Cyclone Forecast in HWRF

2019 ◽  
Vol 147 (10) ◽  
pp. 3721-3740 ◽  
Author(s):  
Masahiro Sawada ◽  
Zaizhong Ma ◽  
Avichal Mehra ◽  
Vijay Tallapragada ◽  
Ryo Oyama ◽  
...  
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Ensemble Forecast ◽  
Lead Times ◽  
Track Forecast ◽  
Background Error ◽  
Steering Flow ◽  
Error Covariance ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors

Abstract The impact of the assimilation of high spatial and temporal resolution atmospheric motion vectors (AMVs) on tropical cyclone (TC) forecasts has been investigated. The high-resolution AMVs are derived from the full disk scan of the new generation geostationary satellite Himawari-8. Forecast experiments for three TCs in 2016 in a western North Pacific basin are performed using the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecasting Model (HWRF). Two different ensemble–variational hybrid data assimilation configurations (using background error covariance created by global ensemble forecast and HWRF ensemble forecast), based on the Gridpoint Statistical Interpolation (GSI), are used for the sensitivity experiments. The results show that the inclusion of high-resolution Himawari-8 AMVs (H8AMV) can benefit the track forecast skill, especially for long-range lead times. The diagnosis of optimal steering flow indicates that the improved track forecast seems to be attributed to the improvement of initial steering flow surrounding the TC. However, the assimilation of H8AMV increases the negative intensity bias and error, especially for short-range forecast lead times. The investigation of the structural change from the assimilation of H8AMV revealed that the following two factors are likely related to this degradation: 1) an increase of inertial stability outside the radius of maximum wind (RMW), which weakens the boundary layer inflow; and 2) a drying around and outside the RMW. Assimilating H8AMV using background error covariance created from HWRF ensemble forecast contributes to a significant reduction in negative intensity bias and error, and there is a significant benefit to TC size forecast.

scholarly journals Verification of 24-h Quantitative Precipitation Forecasts over the Pacific Northwest from a High-Resolution Ensemble Kalman Filter System

2017 ◽  
Vol 32 (3) ◽  
pp. 1185-1208 ◽  
Author(s):  
Phillipa Cookson-Hills ◽  
Daniel J. Kirshbaum ◽  
Madalina Surcel ◽  
Jonathan G. Doyle ◽  
Luc Fillion ◽  
...  
Keyword(s):  
Kalman Filter ◽  
High Resolution ◽  
Data Assimilation ◽  
Pacific Northwest ◽  
Ensemble Kalman Filter ◽  
Ensemble Prediction ◽  
Forecast Errors ◽  
Ensemble Prediction System ◽  
The Pacific ◽  
Quantitative Precipitation Forecasts

Abstract Environment and Climate Change Canada (ECCC) has recently developed an experimental high-resolution EnKF (HREnKF) regional ensemble prediction system, which it tested over the Pacific Northwest of North America for the first half of February 2011. The HREnKF has 2.5-km horizontal grid spacing and assimilates surface and upper-air observations every hour. To determine the benefits of the HREnKF over less expensive alternatives, its 24-h quantitative precipitation forecasts are compared with those from a lower-resolution (15 km) regional ensemble Kalman filter (REnKF) system and to ensembles directly downscaled from the REnKF using the same grid as the HREnKF but with no additional data assimilation (DS). The forecasts are verified against rain gauge observations and gridded precipitation analyses, the latter of which are characterized by uncertainties of comparable magnitude to the model forecast errors. Nonetheless, both deterministic and probabilistic verification indicates robust improvements in forecast skill owing to the finer grids of the HREnKF and DS. The HREnKF exhibits a further improvement in performance over the DS in the first few forecast hours, suggesting a modest positive impact of data assimilation. However, this improvement is not statistically significant and may be attributable to other factors.

scholarly journals The Soverato flood in Southern Italy: performance of global and limited-area ensemble forecasts

2003 ◽  
Vol 10 (3) ◽  
pp. 261-274 ◽  
Author(s):  
A. Montani ◽  
C. Marsigli ◽  
F. Nerozzi ◽  
T. Paccagnella ◽  
S. Tibaldi ◽  
...  
Keyword(s):  
High Resolution ◽  
Southern Italy ◽  
Ensemble Prediction ◽  
Limited Area ◽  
Prediction System ◽  
Probabilistic Prediction ◽  
Ensemble Forecasts ◽  
Ensemble Prediction System ◽  
Limited Area Model ◽  
Area Model

Abstract. The predictability of the flood event affecting Soverato (Southern Italy) in September 2000 is investigated by considering three different configurations of ECMWF ensemble: the operational Ensemble Prediction System (EPS), the targeted EPS and a high-resolution version of EPS. For each configuration, three successive runs of ECMWF ensemble with the same verification time are grouped together so as to generate a highly-populated "super-ensemble". Then, five members are selected from the super-ensemble and used to provide initial and boundary conditions for the integrations with a limited-area model, whose runs generate a Limited-area Ensemble Prediction System (LEPS). The relative impact of targeting the initial perturbations against increasing the horizontal resolution is assessed for the global ensembles as well as for the properties transferred to LEPS integrations, the attention being focussed on the probabilistic prediction of rainfall over a localised area. At the 108, 84 and 60- hour forecast ranges, the overall performance of the global ensembles is not particularly accurate and the best results are obtained by the high-resolution version of EPS. The LEPS performance is very satisfactory in all configurations and the rainfall maps show probability peaks in the correct regions. LEPS products would have been of great assistance to issue flood risk alerts on the basis of limited-area ensemble forecasts. For the 60-hour forecast range, the sensitivity of the results to the LEPS ensemble size is discussed by comparing a 5-member against a 51-member LEPS, where the limited-area model is nested on all EPS members. Little sensitivity is found as concerns the detection of the regions most likely affected by heavy precipitation, the probability peaks being approximately the same in both configurations.

scholarly journals Hydrometeorological Short-Range Ensemble Forecasts in Complex Terrain. Part II: Economic Evaluation

2008 ◽  
Vol 23 (4) ◽  
pp. 557-574 ◽  
Author(s):  
Doug McCollor ◽  
Roland Stull
Keyword(s):  
High Resolution ◽  
Utility Function ◽  
Short Range ◽  
Deterministic Model ◽  
Ensemble Average ◽  
Ensemble Prediction ◽  
Value Assessment ◽  
Ensemble Forecasts ◽  
Ensemble Prediction System ◽  
Hydroelectric Reservoir

Abstract Two economic models are employed to perform a value assessment of short-range ensemble forecasts of 24-h precipitation probabilities for hydroelectric reservoir operation. Using a static cost–loss model, the value of the probability information is compared to the values of a deterministic control high-resolution forecast and of an ensemble-average forecast for forecast days 1 and 2. It is found that the probabilistic ensemble forecast provides value to a much wider range of hydroelectric operators than either the deterministic high-resolution forecast or the ensemble-average forecast, although for a small subset of operators the value of the three forecasts is the same. Forecasts for day-1 precipitation provide measurably higher value than forecasts for day-2 precipitation because of the loss of skill in the longer-range forecasts. A decision theory model provides a continuous-variable weighting of a user-specific utility function. The utility function weights are supplied by the ensemble prediction system, and the outcome is compared with weights calculated from a deterministic model, from the ensemble average, and from climatology. It is found that the methods employing the full ensemble and the ensemble average outperform the single deterministic model and climatology for the hydroelectric reservoir scenario studied.

scholarly journals Atlantic Hurricane Season of 2011*

2013 ◽  
Vol 141 (8) ◽  
pp. 2577-2596 ◽  
Author(s):  
Lixion A. Avila ◽  
Stacy R. Stewart
Keyword(s):  
United States ◽  
The United States ◽  
Tropical Storms ◽  
Track Forecast ◽  
Forecast Errors ◽  
Eastern Canada ◽  
The Bahamas ◽  
Hurricane Wind ◽  
Level Of Activity ◽  
High Level

Abstract The 2011 Atlantic season was marked by above-average tropical cyclone activity with the formation of 19 tropical storms. Seven of the storms became hurricanes and four became major hurricanes (category 3 or higher on the Saffir–Simpson hurricane wind scale). The numbers of tropical storms and hurricanes were above the long-term averages of 12 named storms, 6 hurricanes, and 3 major hurricanes. Despite the high level of activity, Irene was the only hurricane to hit land in 2011, striking both the Bahamas and the United States. Other storms, however, affected the United States, eastern Canada, Central America, eastern Mexico, and the northeastern Caribbean Sea islands. The death toll from the 2011 Atlantic tropical cyclones is 80. National Hurricane Center mean official track forecast errors in 2011 were smaller than the previous 5-yr means at all forecast times except 120 h. In addition, the official track forecast errors set records for accuracy at the 24-, 36-, 48-, and 72-h forecast times. The mean intensity forecast errors in 2011 ranged from about 6 kt (~3 m s−1) at 12 h to about 17 kt (~9 m s−1) at 72 and 120 h. These errors were below the 5-yr means at all forecast times.

scholarly journals Ensemble-Based Forecast Uncertainty Analysis of Diverse Heavy Rainfall Events

2010 ◽  
Vol 25 (4) ◽  
pp. 1103-1122 ◽  
Author(s):  
Russ S. Schumacher ◽  
Christopher A. Davis
Keyword(s):  
United States ◽  
Tropical Cyclones ◽  
Heavy Rainfall ◽  
Warm Season ◽  
The United States ◽  
Forecast Skill ◽  
Ensemble Prediction ◽  
Lead Times ◽  
Cool Season ◽  
Ensemble Prediction System

Abstract This study examines widespread heavy rainfall over 5-day periods in the central and eastern United States. First, a climatology is presented that identifies events in which more than 100 mm of precipitation fell over more than 800 000 km2 in 5 days. This climatology shows that such events are most common in the cool season near the Gulf of Mexico coast and are rare in the warm season. Then, the focus turns to the years 2007 and 2008, when nine such events occurred in the United States, all of them leading to flooding. Three of these were associated with warm-season convection, three took place in the cool season, and three were caused by landfalling tropical cyclones. Global ensemble forecasts from the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System are used to assess forecast skill and uncertainty for these nine events, and to identify the types of weather systems associated with their relative levels of skill and uncertainty. Objective verification metrics and subjective examination are used to determine how far in advance the ensemble identified the threat of widespread heavy rains. Specific conclusions depend on the rainfall threshold and the metric chosen, but, in general, predictive skill was highest for rainfall associated with tropical cyclones and lowest for the warm-season cases. In almost all cases, the ensemble provides very skillful 5-day forecasts when initialized at the beginning of the event. In some of the events—particularly the tropical cyclones and strong baroclinic cyclones—the ensemble still shows considerable skill in 96–216-h precipitation forecasts. In other cases, however, the skill drops off much more rapidly as lead time increases. In particular, forecast skill at long lead times was the lowest and spread was the largest in the two cases associated with meso-α-scale to synoptic-scale vortices that were cut off from the primary upper-level jet. In these cases, it appears that when the vortex is present in the initial conditions, the resulting precipitation forecasts are quite accurate and certain, but at longer lead times when the model is required to both develop and correctly evolve the vortex, forecast quality is low and uncertainty is large. These results motivate further investigation of the events that were poorly predicted.

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