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  • 1
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    Diagnosing Conditions Associated with Large Intensity Forecast Errors in the Hurricane Weather Research and Forecasting (HWRF) Model (2018)
    American Meteorological Society
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    Publication Date: 2018-01-31
    Description: Understanding and forecasting tropical cyclone (TC) intensity change continues to be a paramount challenge for the research and operational communities, partly because of inherent systematic biases contained in model guidance, which can be difficult to diagnose. The purpose of this paper is to present a method to identify such systematic biases by comparing forecasts characterized by large intensity errors with analog forecasts that exhibit small intensity errors. The methodology is applied to the 2015 version of the Hurricane Weather Research and Forecasting (HWRF) Model retrospective forecasts in the North Atlantic (NATL) and eastern North Pacific (EPAC) basins during 2011–14. Forecasts with large 24-h intensity errors are defined to be in the top 15% of all cases in the distribution that underforecast intensity. These forecasts are compared to analog forecasts taken from the bottom 50% of the error distribution. Analog forecasts are identified by finding the case that has 0–24-h intensity and wind shear magnitude time series that are similar to the large intensity error forecasts. Composite differences of the large and small intensity error forecasts reveal that the EPAC large error forecasts have weaker reflectivity and vertical motion near the TC inner core from 3 h onward. Results over the NATL are less clear, with the significant differences between the large and small error forecasts occurring radially outward from the TC core. Though applied to TCs, this analog methodology could be useful for diagnosing systematic model biases in other applications.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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  • 2
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    The Development and Evaluation of a Statistical–Dynamical Tropical Cyclone Genesis Guidance Tool (2016)
    American Meteorological Society
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    Publication Date: 2016-12-29
    Description: The National Hurricane Center (NHC) has stated that guidance on tropical cyclone (TC) genesis is an operational forecast improvement need, particularly since numerical weather prediction models produce TC-like features and operationally required forecast lead times recently have increased. Using previously defined criteria for TC genesis in global models, this study bias corrects TC genesis forecasts from global models using multiple logistic regression. The derived regression equations provide 48- and 120-h probabilistic genesis forecasts for each TC genesis event that occurs in the Environment Canada Global Environmental Multiscale Model (CMC), the NCEP Global Forecast System (GFS), and the Met Office's global model (UKMET). Results show select global model output variables are good discriminators between successful and unsuccessful TC genesis forecasts. Independent verification of the regression-based probabilistic genesis forecasts during 2014 and 2015 are presented. Brier scores and reliability diagrams indicate that the forecasts generally are well calibrated and can be used as guidance for NHC’s Tropical Weather Outlook product. The regression-based TC genesis forecasts are available in real time online.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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  • 3
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    Verification of Tropical Cyclone Genesis Forecasts from Global Numerical Models: Comparisons between the North Atlantic and Eastern North Pacific Basins (2016)
    American Meteorological Society
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    Publication Date: 2016-06-01
    Description: Accurately forecasting tropical cyclone (TC) genesis is an important operational need, especially since the National Hurricane Center’s Tropical Weather Outlook product has been extended from 2 to 5 days. A previous study by the coauthors verified North Atlantic TC genesis forecasts from five global models out to 4 days during 2004–11. This study expands on the previous research by 1) verifying TC genesis forecasts over both the Atlantic and eastern North Pacific basins, 2) extending the forecast window to 5 days, and 3) updating the analysis period through 2014. Verification statistics are presented and compared between the two basins. Probability of detection and critical success indices generally are greater over the eastern North Pacific basin compared to the North Atlantic. There is a trade-off between models that exhibit a greater probability of detection and a greater false alarm ratio, and models that exhibit a smaller false alarm ratio and a smaller probability of detection. Results also reveal that the models preferentially miss TCs over the North Atlantic (eastern North Pacific) that have a relatively small radius of the outer closed isobar (radius of maximum wind) at the forecast genesis time. Overall, global models have become a more reliable source of TC genesis guidance during the past few years compared to the early years in the dataset.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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  • 4
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    A Comparison of Tropical Cyclone Genesis Forecast Verification from Three Global Forecast System (GFS) Operational Configurations (2020)
    American Meteorological Society
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    Publication Date: 2020-08-05
    Description: Operational forecasting of tropical cyclone (TC) genesis has improved in recent years but still can be a challenge. Output from global numerical models continues to serve as a primary source of forecast guidance. Bulk verification statistics (e.g., critical success index) of TC genesis forecasts indicate that, overall, global models are increasingly able to predict TC genesis. However, as global model configurations are updated, TC genesis verification statistics will change. This study compares operational and retrospective forecasts from three configurations of NCEP’s Global Forecast System (GFS) to quantify the impact of model upgrades on TC genesis forecasts. First, bulk verification statistics from a homogeneous sample of model initialization cycles during the period 2013–14 are compared. Then, composites of select output fields are analyzed in an attempt to identify any key differences between hit and false alarm events. Bulk statistics indicate that TC genesis forecast performance decreased with the implementation of the 2015 version of the GFS, but then modestly recovered with the 2016 version of the model. In addition, the composite analysis suggests that false alarm forecasts in the 2015 version of the GFS may have been the result of inaccurately forecasting the location and/or strength of upper-level troughs poleward of the TC. There is also evidence of convective feedbacks occurring, such as ridging above the low-level circulation and upper-level convective outflow that were too strong, in this same set of false alarm forecasts. Overall, analyzing retrospective forecasts can assist forecasters in determining the strengths and weaknesses associated with a new configuration of a global model with respect to TC genesis.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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  • 5
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    Observed versus GCM-Generated Local Tropical Cyclone Frequency: Comparisons Using a Spatial Lattice (2013)
    American Meteorological Society
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    Publication Date: 2013-10-16
    Description: Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resembling actual TCs, but questions remain about their fidelity to observed TCs. Here the authors demonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using observed TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and GCM-generated TCs from the Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) and Florida State University (FSU) Center for Ocean–Atmospheric Prediction Studies (COAPS) model over the common period 1982–2008. Results show that the spatial distribution of TCs generated by the GFDL model compares well with observations globally, although there are areas of over- and underprediction, particularly in parts of the Pacific Ocean. Difference maps using the spatial lattice highlight these discrepancies. Additionally, comparisons focusing on the North Atlantic Ocean basin are made. Results confirm a large area of overprediction by the FSU COAPS model in the south-central portion of the basin. Relevant to projections of future U.S. hurricane activity is the fact that both models underpredict TC activity in the Gulf of Mexico.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 6
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    An Evaluation of Tropical Cyclone Genesis Forecasts from Global Numerical Models (2013)
    American Meteorological Society
    Details
    Publication Date: 2013-12-01
    Description: Tropical cyclone (TC) forecasts rely heavily on output from global numerical models. While considerable research has investigated the skill of various models with respect to track and intensity, few studies have considered how well global models forecast TC genesis in the North Atlantic basin. This paper analyzes TC genesis forecasts from five global models [Environment Canada's Global Environment Multiscale Model (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF) global model, the Global Forecast System (GFS), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Met Office global model (UKMET)] over several seasons in the North Atlantic basin. Identifying TCs in the model is based on a combination of methods used previously in the literature and newly defined objective criteria. All model-indicated TCs are classified as a hit, false alarm, early genesis, or late genesis event. Missed events also are considered. Results show that the models' ability to predict TC genesis varies in time and space. Conditional probabilities when a model predicts genesis and more traditional performance metrics (e.g., critical success index) are calculated. The models are ranked among each other, and results show that the best-performing model varies from year to year. A spatial analysis of each model identifies preferred regions for genesis, and a temporal analysis indicates that model performance expectedly decreases as forecast hour (lead time) increases. Consensus forecasts show that the probability of genesis noticeably increases when multiple models predict the same genesis event. Overall, this study provides a climatology of objectively identified TC genesis forecasts in global models. The resulting verification statistics can be used operationally to help refine deterministic and probabilistic TC genesis forecasts and potentially improve the models examined.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
    Published by American Meteorological Society
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