Though tropical cyclone (TC) models have been routinely evaluated against track and intensity observations, little work has been performed to validate modeled TC wind fields over land. In this paper, we present a simple framework for evaluating simulated low-level inland winds with in-situ observations and existing TC structure theory. The Automated Surface Observing Systems, Florida Coastal Monitoring Program, and best track data are used to generate a theory-predicted wind profile that reasonably represents the observed radial distribution of TC wind speeds. We quantitatively and qualitatively evaluated the modeled inland TC wind fields, and described the model performance with a set of simple indicators. The framework was used to examine the performance of a high-resolution two-way nested Geophysical Fluid Dynamics Laboratory model on recent U.S. landfalling TCs. Results demonstrate the capacity of using this framework to assess the modeled TC low-level wind field in the absence of dense inland observations.
Elsberry, Russell L., Hsiao-Chung Tsai, Corie Capalbo, Wei-Chia Chin, and Timothy Marchok, March 2023: Critical pre-formation decision flowchart to apply tropical cyclone lifecycle predictions in eastern North Pacific. Atmosphere, 14(4), 616, DOI:10.3390/atmos14040616. Abstract
We have previously demonstrated that the ECMWF ensemble (ECEPS) provides early forecasts not only of the Time-to-Tropical Storm (T2TS) and of the Time-to-Hurricane (T2HU), but also of the Time-Ending-Hurricane (TEHU) and Time-Ending-Tropical Storm (TETS) times and positions along those 15-day ECEPS track forecasts, which then provides an opportunity for high-wind warnings along the path during the entire lifecycle of these Hurricanes. The focus in this study is the Decision Flowchart that has been developed to assist the forecasters to select the pre-formation disturbance that is most likely to become the next Tropical Storm with the potential to become a Hurricane. The most crucial decision is to detect and eliminate any disturbance that likely originated from a precursor Caribbean false alarm circulation. Summaries of other steps in the Decision Flowchart “To Watch”, or to reject, other storm options in the twice-daily ECEPS forecasts are provided for Hurricanes Enrique and Felicia, and for strong Tropical Storm Guillermo and weak Tropical Storm Jimena. The first detections in the ECEPS forecasts for the Tropical Storms during the 2021 season averaged 6 days, 18 h in advance with a range of only 2 days, 6 h in advance for TS Terry to 9 days, 18 h in advance for TS Sandra.
Elsberry, Russell L., Hsiao-Chung Tsai, Corie Capalbo, Wei-Chia Chin, and Timothy Marchok, June 2022: Opportunity for tropical cyclone lifecycle predictions from pre-formation to ending stage: Eastern North Pacific 2021 season. Atmosphere, 13(7), DOI:10.3390/atmos13071008. Abstract
Building on previous studies of western North Pacific formation and intensity predictions along the ECMWF ensemble medium-range track forecasts, the first objective of this transition to the eastern North Pacific was to provide earlier forecasts of the Time-to-Formation (T2F) and Time-to-Hurricane (T2H) than are available from the National Hurricane Center Advisories. For the first six hurricanes of the 2021 season, the first detections in the ECMWF ensemble were 8 days to 12 days in advance of the T2F times and 9 days to 13 days in advance of the T2H times. The major advance in this study has been to document that the ECMWF ensemble is also capable of predicting Ending-T2H and Ending-T2F timings and positions along those 15-day ECMWF ensemble track forecasts. This study for the first time documents the opportunity for high wind warnings during the entire lifecycle of the 2021 season hurricanes even days in advance of formation. Validations of the pre-hurricane and Ending-hurricane tracks and timings are provided for the lifecycles of seven hurricanes and the “Almost-Hurricane Guillermo”. Because the technique has been accepted for operational testing at the Joint Typhoon Warning Center, a companion article has been submitted that will describe the flowchart methodology for evaluating the twice-daily ECMWF ensemble forecasts to select the most likely pre-hurricane circulation as early as possible while non-selecting the likely false alarm circulations.
Hazelton, Andrew T., Kun Gao, Morris A Bender, Levi Cowan, Ghassan J Alaka Jr, Alex Kaltenbaugh, Lew Gramer, Xuejin Zhang, Lucas Harris, Timothy Marchok, Matthew J Morin, Avichal Mehra, Zhan Zhang, Bin Liu, and Frank D Marks, January 2022: Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD. Weather and Forecasting, 37(1), DOI:10.1175/WAF-D-21-0102.1143-161. Abstract
The global-nested Hurricane Analysis and Forecast System (HAFS-globalnest) is one piece of NOAA’s Unified Forecast System (UFS) application for hurricanes. In this study, results are analyzed from 2020 real-time forecasts by HAFS-globalnest and a similar global-nested model, the Tropical Atlantic version of GFDL’s System for High‐resolution prediction on Earth‐to‐Local Domains (T-SHiELD). HAFS-globalnest produced the highest track forecast skill compared to several operational and experimental models, while T-SHiELD showed promising track skills as well. The intensity forecasts from HAFS-globalnest generally had a positive bias at longer lead times primarily due to the lack of ocean coupling, while T-SHiELD had a much smaller intensity bias particularly at longer forecast lead times. With the introduction of a modified planetary boundary layer scheme and an increased number of vertical levels, particularly in the boundary layer, HAFS forecasts of storm size had a smaller positive bias than occurred in the 2019 version of HAFS-globalnest. Despite track forecasts that were comparable to the operational GFS and HWRF, both HAFS-globalnest and T-SHiELD suffered from a persistent right-of-track bias in several cases at the 4–5-day forecast lead times. The reasons for this bias were related to the strength of the subtropical ridge over the western North Atlantic and are continuing to be investigated and diagnosed. A few key case studies from this very active hurricane season, including Hurricanes Laura and Delta, were examined.
Elsberry, Russell L., Hsiao-Chung Tsai, Wei-Chia Chin, and Timothy Marchok, June 2021: Predicting rapid intensification events following tropical cyclone formation in the western North Pacific based on ECMWF ensemble warm core evolutions. Atmosphere, 12(7), DOI:10.3390/atmos12070847. Abstract
When the environmental conditions over the western North Pacific are favorable for tropical cyclone formation, a rapid intensification event will frequently follow formation. In this extension of our combined three-stage 7-day Weighted Analog Intensity Pacific prediction technique, the European Centre for Medium-range Weather Prediction ensemble predictions of the warm core magnitudes of pre-tropical cyclone circulations are utilized to define the Time-to-Formation (35 knots) and to estimate the Likely Storm Category. If that category is a Typhoon, the bifurcation version of our technique is modified to better predict the peak intensity by selecting only Cluster 1 analog storms with the largest peak intensities that are most likely to have under-gone rapid intensification. A second modification to improve the peak intensity magnitude and timing was to fit a cubic spline curve through the weighted-mean peak intensities of the Cluster 1 analogs. The performance of this modified technique has been evaluated for a sequence of western North Pacific tropical cyclones during 2019 in terms of: (i) Detection time in advance of formation; (ii) Accuracy of Time-to-Formation; (iii) Intensification stage prediction; and (iv) Peak intensity magnitude/timing. This modified technique would provide earlier guidance as to the threat of a Typhoon along the 15-day ensemble storm track forecast, which would be a benefit for risk management officials.
Hazelton, Andrew T., Zhan Zhang, Bin Liu, Jili Dong, Ghassan Alaka, Weiguo Wang, Timothy Marchok, Avichal Mehra, Sundararaman Gopalakrishnan, Xuejin Zhang, Morris A Bender, Vijay Tallapragada, and Frank D Marks, April 2021: 2019 Atlantic hurricane forecasts from the global-nested Hurricane Analysis and Forecast System: Composite statistics and key events. Weather and Forecasting, 36(2), DOI:10.1175/WAF-D-20-0044.1519-538. Abstract
NOAA’s Hurricane Analysis and Forecast System (HAFS) is an evolving FV3-based hurricane modeling system that is expected to replace the operational hurricane models at the National Weather Service. Supported by the Hurricane Forecast Improvement Program (HFIP), global-nested and regional versions of HAFS were run in real time in 2019 to create the first baseline for the HAFS advancement. In this study, forecasts from the global-nested configuration of HAFS (HAFS-globalnest) are evaluated and compared with other operational and experimental models. The forecasts by HAFS-globalnest covered the period from July through October during the 2019 hurricane season. Tropical cyclone (TC) track, intensity, and structure forecast verifications are examined. HAFS-globalnest showed track skill superior to several operational hurricane models and comparable intensity and structure skill, although the skill in predicting rapid intensification was slightly inferior to the operational model skill. HAFS-globalnest correctly predicted that Hurricane Dorian would slow and turn north in the Bahamas and also correctly predicted structural features in other TCs such as a sting jet in Hurricane Humberto during extratropical transition. Humberto was also a case where HAFS-globalnest had better track forecasts than a regional version of HAFS (HAFS-SAR) due to a better representation of the large-scale flow. These examples and others are examined through comparisons with airborne tail Doppler radar from the NOAA WP-3D to provide a more detailed evaluation of TC structure prediction. The results from this real-time experiment motivate several future model improvements, and highlight the promise of HAFS-globalnest for improved TC prediction.
Marchok, Timothy, September 2021: Important factors in the tracking of tropical cyclones in operational models. Journal of Applied Meteorology and Climatology, 60(9), DOI:10.1175/JAMC-D-20-0175.11265-1284. Abstract
Multiple configurations of the Geophysical Fluid Dynamics Laboratory vortex tracker are tested to determine a setup that produces the best representation of a model forecast tropical cyclone center fix for the purpose of providing track guidance with the highest degree of accuracy and availability. Details of the tracking algorithms are provided, including descriptions of both the Barnes analysis used for center fixing most variables and a separate scheme used for center fixing wind circulation. The tracker is tested by running multiple configurations on all storms from the 2015–17 hurricane seasons in the Atlantic and eastern Pacific basins using forecasts from two operational National Weather Service models, the Global Forecast System (GFS) and the Hurricane Weather Research and Forecasting Model (HWRF). A configuration that tracks only 850-mb geopotential height has the smallest forecast track errors of any configuration based on an individual parameter. However, a configuration composed of the mean of 11 parameters outperforms any of the configurations that are based on individual parameters. Configurations composed of subsets of the 11 parameters and including both mass and momentum variables provide results comparable to or better than the full 11-parameter configuration. In particular, a subset configuration with thickness variables excluded generally outperforms the 11-parameter mean, while one composed of variables from only the 850-mb and near-surface layers performs nearly as well as the 11-parameter mean. Tracker configurations composed of multiple variables are more reliable in providing guidance through the end of a forecast period than are tracker configurations based on individual parameters.
Elsberry, Russell L., Hsiao-Chung Tsai, Wei-Chia Chin, and Timothy Marchok, September 2020: Advanced global model ensemble forecasts of tropical cyclone formation, and intensity predictions along medium-range tracks. Atmosphere, 11(9), DOI:10.3390/atmos11091002. Abstract
Marchok vortex tracker outputs from the European Centre for Medium-Range Weather Forecasts ensemble (ECEPS) and National Centers for Environmental Prediction ensemble (GEFS) are utilized to provide the Time-to-Formation (T2F of 25 kt or 35 kt) timing and positions along the weighted-mean vector motion (WMVM) track forecasts, and our weighted analog intensity Pacific (WAIP) technique provides 7-day intensity forecasts after the T2F. Example T2F(35) forecasts up to 5 days in advance of two typhoons and one non-developer in the western North Pacific are described in detail. An example T2F forecast of pre-Hurricane Kiko in the eastern North Pacific indicated that Hawaii would be under threat by the end of the 15-day ECEPS WMVM track forecast. An example T2F forecast of pre-Hurricane Lorenzo in the eastern Atlantic demonstrates that both the ECEPS and GEFS predict up to 5 days in advance that the precursor African wave will become a Tropical Storm off the west coast and will likely become a hurricane. Validations of the T2F(25) and T2F(35) timing and position errors are provided for all ECEPS and GEFS forecasts of the two typhoons and Hurricanes Kiko and Lorenzo. If the T2F timing errors are small (<1 day), the T2F position errors along the WMVM track forecasts will be small (<300 km). Although the primary focus is on the western North Pacific, the examples from the Atlantic and eastern/central North Pacific indicate the potential for future application in other basins.
We present the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic FV3 Dynamical Core to a physics suite originally taken from the Global Forecast System. SHiELD is designed to demonstrate new capabilities within its components, explore new model applications, and to answer scientific questions through these new functionalities. A variety of configurations are presented, including short‐to‐medium‐range and subseasonal‐to‐seasonal prediction, global‐to‐regional convective‐scale hurricane and contiguous U.S. precipitation forecasts, and global cloud‐resolving modeling. Advances within SHiELD can be seamlessly transitioned into other Unified Forecast System or FV3‐based models, including operational implementations of the Unified Forecast System. Continued development of SHiELD has shown improvement upon existing models. The flagship 13‐km SHiELD demonstrates steadily improved large‐scale prediction skill and precipitation prediction skill. SHiELD and the coarser‐resolution S‐SHiELD demonstrate a superior diurnal cycle compared to existing climate models; the latter also demonstrates 28 days of useful prediction skill for the Madden‐Julian Oscillation. The global‐to‐regional nested configurations T‐SHiELD (tropical Atlantic) and C‐SHiELD (contiguous United States) show significant improvement in hurricane structure from a new tracer advection scheme and promise for medium‐range prediction of convective storms.
Tsai, Hsiao-Chung, Russell L Elsberry, Wei-Chia Chin, and Timothy Marchok, October 2020: Opportunity for early warnings of Typhoon Lekima from two global ensemble model forecasts of formation with 7-day intensities along medium-range tracks. Atmosphere, 11(11), DOI:10.3390/atmos11111162. Abstract
Typhoon Lekima (2019) with its heavy rains and floods is an excellent example of the need to provide the earliest possible warnings of the formation, intensification, and subsequent track before a typhoon makes landfall along a densely populated coast. To demonstrate an opportunity to provide early (10 days in advance) warnings of the threat of Typhoon Lekima, the ensemble models from the European Centre for Medium-Range Weather Forecasts and the National Centers for Environmental Predictions have been used to provide time-to-formation timing and positions along the weighted-mean vector motion track forecasts. In addition, the seven-day intensity forecasts after the formation using a weighted analog intensity prediction technique are provided. A detailed description of one European Center ensemble forecast is provided to describe the methodology for estimating the formation time and generating the intensity forecasts. Validation summary tables of the formation timing and position errors, and the intensity errors versus the Joint Typhoon Warning Center intensities, are presented. The availability of these ensemble forecasts would have been an opportunity to issue alerts/watches/warnings of Lekima even seven days in advance of when Lekima became a Tropical Storm. These ensemble forecasts also represent an opportunity to extend support on the 5–15 day timescale for the decision-making processes of water resource management and hydrological operations
Successful collaborations played a pivotal role in transitioning the GFDL hurricane research model into a long-standing state-of-the-art operational system that provided critical guidance for over 20 years.
The hurricane project at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL) was established in 1970. By the mid 1970s pioneering research had led to the development of a new hurricane model. As the reputation of the model grew, GFDL was approached in 1986 by the director of the National Meteorological Center about establishing collaboration between the two Federal organizations to transition the model into an operational modeling system. After a multi-year effort by GFDL scientists to develop a system that could support rigorous requirements of operations, and multi-year testing had demonstrated its superior performance compared to existing guidance products, operational implementation was made in 1995. Through collaboration between GFDL and the US Navy, the model was also made operational at Fleet Numerical Meteorology and Oceanography Center in 1996. GFDL scientists continued to support and improve the model during the next two decades by collaborating with other scientists at GFDL, the NCEP Environmental Modeling Center (EMC), the National Hurricane Center, the US Navy, the University of Rhode Island (URI), Old Dominion University, and the NOAA Hurricane Research Division. Scientists at GFDL, URI, and EMC collaborated to transfer key components of the GFDL model to the NWS new Hurricane Weather and Research Forecast (HWRF) model that became operational in 2007. The purpose of the article is to highlight the critical role of these collaborations. It is hoped that the experiences of the authors will serve as an example of how such collaboration can benefit the nation with improved weather guidance products.
The impact of storm size on the forecast of tropical cyclone storm track and intensity is investigated using the 2016 version of the operational GFDL hurricane model. Evaluation was made for 1,529 forecasts in the Atlantic, eastern Pacific, and western North Pacific basins, during the 2014 and 2015 seasons. The track and intensity errors were computed from forecasts in which the 34-knot wind radii obtained from the operational TC-Vitals that are used to initialize TCs in the GFDL model were replaced with wind radii estimates derived using an equally-weighted average of six objective estimates. It was found that modifying the radius of 34-knot winds had a significant positive impact on the intensity forecasts in the 1-2 day lead times. For example, at 48h, the intensity error was reduced 10%, 5% and 4% in the Atlantic, eastern Pacific, and western North Pacific, respectively. The largest improvements in intensity forecasts were for those tropical cyclones undergoing rapid intensification, with a maximum error reduction in the 1-2 day forecast lead time of 14 and 17% in the eastern and western North Pacific, respectively. The large negative intensity biases in the eastern and western North Pacific were also reduced 25% and 75% in the 12 to 72h forecast lead times. Although the overall impact on the average track error was neutral, forecasts of recurving storms were improved and tracks of non-recurving storms degraded. Results also suggest that objective specification of storm size may impact intensity forecasts in other high resolution numerical models, particularly for tropical cyclones entering a rapid intensification phase.
Sampson, C R., E M Fukada, J A Knaff, B R Strahl, M J Brennan, and Timothy Marchok, June 2017: Tropical cyclone gale wind radii estimates for the western North Pacific. Weather and Forecasting, 32(3), DOI:10.1175/WAF-D-16-0196.1. Abstract
The Joint Typhoon Warning Center’s (JTWC) forecast improvement goals include reducing 34-kt wind radii forecast errors, so accurate real-time estimates and post-season analysis of the 34-kt wind radii are critical to reaching this goal. Accurate real-time 34-kt wind radii estimates are also critical for decisions regarding base preparedness and asset protection, but still represent a significant operational challenge at JTWC for several reasons. These reasons include: a paucity of observations, the timeliness and availability of guidance, a lack of analysis tools, and a perceived shortage of personnel to perform the analysis; however, the number of available objective wind radii estimates is expanding and the topic of estimating 34-kt wind radii warrants revisiting.
In this work we describe an equally-weighted mean of real-time 34-kt wind radii objective estimates that provides real-time, routine operational guidance. This objective method is also used to retrospectively produce a two-year (2014-2015) 34-kt wind radii objective analysis, the results of which compare favorably to the post-season National Hurricane Center data (i.e., the best tracks), and a newly created best track data set for the western North Pacific seasons. This equally-weighted mean, when compared to the individual 34-kt wind radii estimate methods, is shown to have among the lowest mean absolute errors and smallest biases. In an ancillary finding, the western North Pacific basin average 34-kt wind radii calculated from the 2014-2015 seasons are estimated to be 134 n mi, which is larger than the estimates for storms in either the Atlantic (95 n mi) or eastern North Pacific (82 n mi) basins for the same years.
Bernardet, L, Vijay Tallapragada, S Bao, S Trahan, Y Kwon, Q Liu, Mingjing Tong, M Biswas, T Brown, D Stark, L Carson, R Yablonsky, E Uhlhorn, Sundararaman Gopalakrishnan, X Zhang, and Timothy Marchok, et al., June 2015: Community Support and Transition of Research to Operations for the Hurricane Weather Research and Forecast (HWRF) Model. Bulletin of the American Meteorological Society, 96(6), DOI:10.1175/BAMS-D-13-00093.1. Abstract
The Hurricane Weather Research and Forecasting (HWRF) model is an operational model used to provide numerical guidance in support of tropical cyclone forecasting at the National Hurricane Center. HWRF is a complex multi-component system, consisting of the Weather Research and Forecasting (WRF) atmospheric model coupled to the Princeton Ocean Model for Tropical Cyclones (POM-TC), a sophisticated initialization package including a data assimilation system, and a set of postprocessing and vortex tracking tools. HWRF's development is centralized at the Environmental Modeling Center of NOAA's National Weather Service, but it incorporates contributions from a variety of scientists spread out over several governmental laboratories and academic institutions. This distributed development scenario poses significant challenges: a large number of scientists need to learn how to use the model, operational and research codes need to stay synchronized to avoid divergence, and promising new capabilities need to be tested for operational consideration. This article describes how the Developmental Testbed Center has engaged in the HWRF developmental cycle in the last three years and the services it provides to the community in using and developing HWRF.
Sampson, C R., P A Wittmann, H L Tolman, E A Serra, J Schauer, and Timothy Marchok, February 2013: Evaluation of Wave Forecasts Consistent with Tropical Cyclone Warning Center Wind Forecasts. Weather and Forecasting, 28(1), DOI:10.1175/WAF-D-12-00060.1. Abstract
An algorithm to generate wave fields consistent with forecasts from the official U. S. tropical cyclone forecast centers has been made available in near real-time to forecasters since summer 2007. The algorithm removes the tropical cyclone from numerical weather prediction model surface wind field forecasts, replaces the removed winds with interpolated values from surrounding grid points, and then adds a surface wind field generated from the official forecast into the background. The modified wind fields are then used as input into the WAVEWATCH III model to provide seas consistent with the official tropical cyclone forecasts. Although this product is appealing to forecasters because of its consistency and its superior tropical cyclone track forecast, there has been only anecdotal evaluation of resulting wave fields to date. This study evaluates this new algorithm for two years of Atlantic tropical cyclones and compares results with those of WAVEWATCH III run with U.S. Navy Global Atmospheric Prediction System (NOGAPS) surface winds alone. Results show that the new algorithm has generally improved forecasts of maximum significant wave heights and 12-ft seas radii in proximity to tropical cyclones when compared with forecasts produced using only the NOGAPS surface winds.
This paper describes a forecasting configuration of the Geophysical Fluid Dynamics Laboratory (GFDL) High-resolution Atmospheric model (HiRAM). HiRAM represents an early attempt in unifying, within a global modeling framework, the capabilities of GFDL's low-resolution climate models for IPCC-type climate change assessments and high-resolution limited-area models for hurricane predictions.
In this study, the potential of HiRAM as a forecasting tool is investigated by applying the model to near-term and intraseasonal hindcasting of tropical cyclones (TCs) in the Atlantic basin from 2006 – 2009. Results demonstrate that HiRAM provides skillful near-term forecasts of TC track and intensity relative to their respective benchmarks from t = 48 hr through t = 144 hr. At the intraseasonal timescale, a simple HiRAM ensemble provides skillful forecasts of 21-day Atlantic basin TC activity at a 2-day lead time. It should be noted that the methodology used to produce these hindcasts is applicable in a real-time forecasting scenario.
While the initial experimental results appear promising, the HiRAM forecasting system requires various improvements in order to be useful in an operational setting. These modifications currently under development include a data assimilation system for forecast initialization, increased horizontal resolution to better resolve the vortex structure, 3-D ocean model coupling, and wave model coupling. An overview of these ongoing developments are provided, and the specifics of each will be described in subsequent papers.
Lloyd, I D., Timothy Marchok, and Gabriel A Vecchi, November 2011: Diagnostics comparing sea surface temperature feedbacks from operational hurricane forecasts to observations. Journal of Advances in Modeling Earth Systems, 3, M11002, DOI:10.1029/2011MS000075. Abstract
This paper examines the ability of recent versions of the Geophysical Fluid Dynamics Laboratory
Operational Hurricane Forecast Model (GHM) to reproduce the observed relationship between hurricane
intensity and hurricane-induced Sea Surface Temperature (SST) cooling. The analysis was performed by
taking a Lagrangian composite of all hurricanes in the North Atlantic from 1998–2009 in observations and
2005–2009 for the GHM. A marked improvement in the intensity-SST relationship for the GHM compared
to observations was found between the years 2005 and 2006–2009 due to the introduction of warm-core
eddies, a representation of the loop current, and changes to the drag coefficient parameterization for bulk
turbulent flux computation. A Conceptual Hurricane Intensity Model illustrates the essential steady-state
characteristics of the intensity-SST relationship and is explained by two coupled equations for the
atmosphere and ocean. The conceptual model qualitatively matches observations and the 2006–2009 period
in the GHM, and presents supporting evidence for the conclusion that weaker upper oceanic thermal
stratification in the Gulf of Mexico, caused by the introduction of the loop current and warm core eddies, is
crucial to explaining the observed SST-intensity pattern. The diagnostics proposed by the conceptual model
offer an independent set of metrics for comparing operational hurricane forecast models to observations.
Villarini, Gabriele, James A Smith, Mary Lynn Baeck, Timothy Marchok, and Gabriel A Vecchi, December 2011: Characterization of rainfall distribution and flooding associated with U.S. landfalling tropical cyclones: Analyses of hurricanes Frances, Ivan, and Jeanne (2004). Journal of Geophysical Research: Atmospheres, 116, D23116, DOI:10.1029/2011JD016175. Abstract
Rainfall and flooding associated with landfalling tropical cyclones are examined through empirical analyses of three hurricanes (Frances, Ivan, and Jeanne) that affected large portions of the eastern U.S. during September 2004. Three rainfall products are considered for the analyses: NLDAS, Stage IV, and TMPA. Each of these products has strengths and weaknesses related to their spatio-temporal resolution and accuracy in estimating rainfall. Based on our analyses, we recommend using the Stage IV product when studying rainfall distribution in landfalling tropical cyclones due to its fine spatial and temporal resolutions (about 4-km and hourly) and accuracy, and the capability of estimating rainfall up to 150 km from the coast. Lagrangian analyses of rainfall distribution relative to the track of the storm are developed to represent evolution of the temporal and spatial structure of rainfall. Analyses highlight the profound changes in rainfall distribution near landfall, the changing contributions to the rainfall field from eyewall convection, inner rain bands and outer rain bands, and the key role of orographic amplification of rainfall. We also present new methods for examining spatial extreme of flooding from tropical cyclones and illustrate the links between evolving rainfall structure and spatial extent of flooding.
Buckingham, Christian E., Timothy Marchok, Isaac Ginis, L Rothstein, and D Rowe, December 2010: Short and medium-range prediction of tropical and transitioning cyclone tracks within the NCEP Global Ensemble Forecasting System. Weather and Forecasting, 25(6), DOI:10.1175/2010WAF2222398.1. Abstract
The NCEP Global Ensemble Forecasting System (GEFS) is examined in its ability to predict tropical cyclone and extratropical transition (ET) position. Forecast and observed tracks are compared in Atlantic and western North Pacific basins for 2006–2008, and accuracy and consistency of the ensemble is examined out to 8 days. Accuracy is quantified by average absolute, along and cross track error of the ensemble mean. Consistency is evaluated through use of dispersion diagrams, missing rate error and probability within spread. Homogeneous comparisons are made with the NCEP Global Forecasting System (GFS).
Average absolute track error of the GEFS mean increases linearly at a rate of 50 n mi d−1 at early lead times in the Atlantic, increasing to 150 n mi d−1 at 144 h (100 n mi d−1 when excluding ET tracks). This trend is 60 n mi d−1 at early lead times in the western North Pacific, increasing to 150 n mi d−1 at longer lead times (130 n mi d−1 when excluding ET tracks). At long lead times, forecasts illustrate left- and right-of-track bias in Atlantic and western North Pacific basins, respectively; bias is reduced (increased) in the Atlantic (western North Pacific) when excluding ET tracks. All forecasts were found to lag behind observed cyclones, on average. The GEFS has good dispersion characteristics in the Atlantic and is under-dispersive in the western North Pacific. Homogeneous comparisons suggest that the ensemble mean has value relative to the GFS beyond 96 h in the Atlantic and less value in the western North Pacific; a larger sample size is needed before conclusions can be made.
Lin, Ning, James A Smith, Timothy Marchok, Gabriele Villarini, and Mary Lynn Baeck, October 2010: Modeling extreme rainfall, winds, and surge from Hurricane Isabel (2003). Weather and Forecasting, 25(5), DOI:10.1175/2010WAF2222349.1. Abstract
Landfalling tropical cyclones present major hazards for the eastern United States. Hurricane Isabel (September 2003) produced more than $3.3 billion in damages from wind, inland riverine flooding and storm surge flooding and resulted in 17 fatalities. Case study analyses of Hurricane Isabel are carried out to investigate multiple hazards from landfalling tropical cyclones. The analyses focus on storm evolution following landfall and center on simulations using the Weather Research and Forecasting (WRF) model. WRF simulations are coupled with the 2-D, depth-averaged hydrodynamic model, ADCIRC (Advanced Circulation Model), to examine storm surge in the Chesapeake Bay. Analyses of heavy rainfall and flooding include examination of the structure and evolution of extreme rainfall over land. Intercomparisons of simulated rainfall from WRF with Hydro-NEXRAD radar rainfall fields and observations from rain gage networks are presented. A particular focus of these analyses is the evolving distribution of rainfall, relative to the center of circulation, as the storm moves over land. Similar analyses are carried out for the wind field of Hurricane Isabel as it moves over the mid-Atlantic region. Outer rainbands, which are not well captured in WRF simulations, played a major role in urban flooding and wind damage, especially for the Baltimore metropolitan region. Wind maxima in outer rainbands may also have played a role in storm surge flooding in the upper Chesapeake Bay.
Rogers, Robert, Frank D Marks, and Timothy Marchok, 2009: Tropical Cyclone Rainfall In Encyclopedia of Hydrological Sciences [M.G. Anderson and J.J. McDonnell (eds.)], DOI:10.1002/0470848944.hsa030. Abstract
A brief survey of the relevant research of tropical cyclone (TC) rainfall is presented here. The importance of TC rainfall in global and regional rainfall budgets is discussed, as is its mean characteristics as derived from airborne and satellite observational studies. Discussion is also presented on the physical processes that can modulate TC rainfall distributions, including topography, storm motion, vertical shear, and extratropical transition. Some tools that have been developed to predict and evaluate forecasts of TC rainfall are discussed. Finally, a summary and outlook for the future is presented, including a discussion of opportunities for improving TC rainfall forecasts and conducting research into the role of TC rainfall in intensity and structure changes in TCs.
The past decade has been marked by significant advancements in numerical weather prediction of hurricanes, which have greatly contributed to the steady decline in forecast track error. Since its operational implementation by the U.S. National Weather Service (NWS) in 1995, the best-track model performer has been NOAA’s regional hurricane model developed at the Geophysical Fluid Dynamics Laboratory (GFDL). The purpose of this paper is to summarize the major upgrades to the GFDL hurricane forecast system since 1998. These include coupling the atmospheric component with the Princeton Ocean Model, which became operational in 2001, major physics upgrades implemented in 2003 and 2006, and increases in both the vertical resolution in 2003 and the horizontal resolution in 2002 and 2005. The paper will also report on the GFDL model performance for both track and intensity, focusing particularly on the 2003 through 2006 hurricane seasons. During this period, the GFDL track errors were the lowest of all the dynamical model guidance available to the NWS Tropical Prediction Center in both the Atlantic and eastern Pacific basins. It will also be shown that the GFDL model has exhibited a steady reduction in its intensity errors during the past 5 yr, and can now provide skillful intensity forecasts. Tests of 153 forecasts from the 2004 and 2005 Atlantic hurricane seasons and 75 forecasts from the 2005 eastern Pacific season have demonstrated a positive impact on both track and intensity prediction in the 2006 GFDL model upgrade, through introduction of a cloud microphysics package and an improved air–sea momentum flux parameterization. In addition, the large positive intensity bias in sheared environments observed in previous versions of the model is significantly reduced. This led to the significant improvement in the model’s reliability and skill for forecasting intensity that occurred in 2006.
Knaff, J A., C R Sampson, M DeMaria, Timothy Marchok, J M Gross, and C J McAdie, 2007: Statistical Tropical Cyclone Wind Radii Prediction Using Climatology and Persistence. Weather and Forecasting, 22(4), DOI:10.1175/WAF1026.1. Abstract
An
operational model used to predict tropical cyclone wind structure in terms
of significant wind radii (i.e., 34-, 50-, and 64-kt wind radii, where 1 kt
= 0.52 m s-1) at the National Oceanic and Atmospheric
Administration/National Hurricane Center (NHC) and the Department of
Defense/Joint Typhoon Warning Center (JTWC) is described. The statistical-parametric
model employs aspects of climatology and persistence to forecast tropical
cyclone wind radii through 5 days. Separate versions of the model are
created for the Atlantic, east Pacific, and western North Pacific by
statistically fitting a modified Rankine vortex, which is generalized to
allow wavenumber-1 asymmetries, to observed values of tropical cyclone wind
radii as reported by NHC and JTWC. Descriptions of the developmental data
and methods used to formulate the model are given. A 2-yr verification and
comparison with operational forecasts and an independently developed wind
radii forecast method that also employs climatology and persistence suggests
that the statistical-parametric model does a good job of forecasting wind
radii. The statistical-parametric model also provides reliable operational
forecasts that serve as a baseline for evaluating the skill of operational
forecasts and other wind radii forecast methods in these tropical cyclone
basins.
Lonfat, M, Robert Rogers, Timothy Marchok, and Frank D Marks, 2007: A Parametric Model for Predicting Hurricane Rainfall. Monthly Weather Review, 135(9), DOI:10.1175/MWR3433.1. Abstract
This study documents a new parametric hurricane rainfall prediction scheme, based on the rainfall climatology and persistence model (R-CLIPER) used operationally in the Atlantic Ocean basin to forecast rainfall accumulations. Although R-CLIPER has shown skill at estimating the mean amplitude of rainfall across the storm track, one underlying limitation is that it assumes that hurricanes produce rain fields that are azimuthally symmetric. The new implementations described here take into account the effect of shear and topography on the rainfall distribution through the use of parametric representations of these processes. Shear affects the hurricane rainfall by introducing spatial asymmetries, which can be reasonably well modeled to first order using a Fourier decomposition. The effect of topography is modeled by evaluating changes in elevation of flow parcels within the storm circulation between time steps and correcting the rainfall field in proportion to those changes. Effects modeled in R-CLIPER and those from shear and topography are combined in a new model called the Parametric Hurricane Rainfall Model (PHRaM). Comparisons of rainfall accumulations predicted from the operational R-CLIPER model, PHRaM, and radar-derived observations show some improvement in the spatial distribution and amplitude of rainfall when shear is accounted for and significant improvements when both shear and topography are modeled.
Marchok, Timothy, Robert Rogers, and Robert E Tuleya, 2007: Validation Schemes for Tropical Cyclone Quantitative Precipitation Forecasts: Evaluation of Operational Models for U.S. Landfalling Cases. Weather and Forecasting, 22(4), DOI:10.1175/WAF1024.1. Abstract
A scheme for validating quantitative precipitation forecasts (QPFs) for landfalling tropical cyclones is developed and presented here. This scheme takes advantage of the unique characteristics of tropical cyclone rainfall by evaluating the skill of rainfall forecasts in three attributes: the ability to match observed rainfall patterns, the ability to match the mean value and volume of observed rainfall, and the ability to produce the extreme amounts often observed in tropical cyclones. For some of these characteristics, track-relative analyses are employed that help to reduce the impact of model track forecast error on QPF skill. These characteristics are evaluated for storm-total rainfall forecasts of all U.S. landfalling tropical cyclones from 1998 to 2004 by the NCEP operational models, that is, the Global Forecast System (GFS), the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model, and the North American Mesoscale (NAM) model, as well as the benchmark Rainfall Climatology and Persistence (R-CLIPER) model. Compared to R-CLIPER, all of the numerical models showed comparable or greater skill for all of the attributes. The GFS performed the best of all of the models for each of the categories. The GFDL had a bias of predicting too much heavy rain, especially in the core of the tropical cyclones, while the NAM predicted too little of the heavy rain. The R-CLIPER performed well near the track of the core, but it predicted much too little rain at large distances from the track. Whereas a primary determinant of tropical cyclone QPF errors is track forecast error, possible physical causes of track-relative differences lie with the physical parameterizations and initialization schemes for each of the models. This validation scheme can be used to identify model limitations and biases and guide future efforts toward model development and improvement.
Toth, Z, Y Zhu, and Timothy Marchok, 2001: The use of ensembles to identify forecasts with small and large uncertainty. Weather and Forecasting, 16(4), 463-477. Abstract
In the past decade ensemble forecasting has developed into an integral part of numerical weather prediction. Flow-dependent forecast probability distributions can be readily generated from an ensemble, allowing for the identification of forecast cases with high and low uncertainty. The ability of the NCEP ensemble to distinguish between high and low uncertainty forecast cases is studied here quantitatively. Ensemble mode forecasts, along with traditional higher-resolution control forecasts, are verified in terms of predicting the probability of the true state being in 1 of 10 climatologically equally likely 500-hPa height intervals. A stratification of the forecast cases by the degree of overall agreement among the ensemble members reveals great differences in forecast performance between the cases identified by the ensemble as the least and most uncertain. A new ensemble-based forecast product, the "relative measure of predictability," is introduced to identify forecasts with below and above average uncertainty. This measure is standardized according to geographical location, the phase of the annual cycle, lead time, and also the position of the forecast value in terms of the climatological frequency distribution. The potential benefits of using this and other ensemble-based measures of predictability is demonstrated through synoptic examples.
Szunyogh, I, Z Toth, Kerry A Emanuel, C H Bishop, C Snyder, R E Morse, J Woolen, and Timothy Marchok, 1999: Ensemble-based targeting experiments during FASTEX: The effect of dropsonde data from the Lear jet. Quarterly Journal of the Royal Meteorological Society, 125(561), 3189-3217. Abstract PDF
In this study we evaluate the performance of the Ensemble Transform (ET) technique, which is one of several targeting methods used in real time during the Fronts and Atlantic Storm-Track EXperiment (FASTEX). 'Targeted' observations were taken adaptively in those upstream areas identified in real time as most relevant for improving the initial conditions for forecasts of synoptic-scale storms developing downstream. The upstream areas were identified as regions where the effect of extra observations at a future analysis time could produce the largest decrease in the largest likely forecast error at a preselected later verification time at a given downstream location. The ET technique selects these obervational areas out of a large number of possible deployment locations of observational resources via a linear transformation of an ensemble of forecasts.
The analysis and forecast effects of special targeted observations associated with seven Intensive Observing Periods (IOPS) during FASTEX were investigated. The most important result of the present study is that the ET technique, based on the National Centers for Environmental Prediction (NCEP) operational global ensemble, was able to identify upstream areas that had significant contribution to the quality of selected future downstream forecast features. Moreover, the technique could reliably distinguish between areas of greatest contribution.
Though the overall impact of the targeted data on forecast quality is positive, there were cases when the extra data degraded the forecasts. Our analysis indicates that large amplification of ensemble perturbations from the targeted area into the verification area is a good indicator of potential forecast improvement.
