Abstract

We present a hurricane risk assessment model that simulates North Atlantic Ocean tropical cyclone (TC) tracks and intensity, conditioned on the early season large-scale climate state. The model, Cluster-Based Climate-Conditioned Hurricane Intensity and Track Simulator (C³-HITS), extends a previous version of HITS. HITS is a nonparametric, spatial semi-Markov, stochastic model that generates TC tracks by conditionally simulating segments of randomly varying lengths from the TC tracks contained in NOAA’s Best Track Data, version 2, dataset. The distance to neighboring tracks, track direction, TC wind speed, and age are used as conditioning variables. C³-HITS adds conditioning on two early season, large-scale climate covariates to condition the track simulation: the Niño-3.4 index, representing the eastern equatorial Pacific Ocean sea surface temperature (SST) departure from climatology, and main development region, representing tropical North Atlantic SST departure from climatology in the North Atlantic TC main development region. A track clustering procedure is used to identify track families, and a Poisson regression model is used to model the probabilistic number of storms formed in each cluster, conditional on the two climate covariates. The HITS algorithm is then applied to evolve these tracks forward in time. The output of this two-step, climate-conditioned simulator is compared with an unconditional HITS application to illustrate its prognostic efficacy in simulating tracks during the subsequent season. As in the HITS model, each track retains information on velocity and other attributes that can be used for predictive coastal risk modeling for the upcoming TC season.

Abstract

Many numerical model verification schemes are handicapped by their inability to separate non-systematic errors and systematic errors. In this study, for a specific synoptic event, a statistical method is described to determine a minimum number of cases which can be averaged to represent numerical forecast errors which are truly systematic and not smoothed fields of rapidly varying non-systematic errors.

Error patterns derived from forecasts and observations stored at Fleet Numerical Oceanography Center are used to compare a systematic error pattern, defined by the total number of available cases with subset error patterns to determine the minimum number of cases needed to filter out the unwanted non-systematic error components. The analysis indicates that a minimum of 8 cases must be averaged to adequately identify systematic errors in a 24 h forecast of a Shanghai Low. A minimum of 5 cases are needed for a 72 h forecast of the same event. Error patterns are identified by contours of the Student's t statistic calculated at each grid point. This contour pattern objectively determines the significance of the forecast errors and is shown to be a very useful method of portraying, systematic forecast errors.

Abstract

Extratropical transition (ET) in the western North Pacific is defined here in terms of two stages: transformation, in which the tropical cyclone evolves into a baroclinic storm; and reintensification, where the transformed storm then deepens as an extratropical cyclone. In this study, 30 ET cases occurring during 1 June–31 October 1994–98 are reviewed using Navy Operational Global Atmospheric Prediction System analyses; hourly geostationary visible, infrared, and water vapor imagery; and microwave imagery. A brief climatology based on these cases is presented for the transformation stage and the subsequent cyclone characteristics of the reintensification stage.

A three-dimensional conceptual model of the transformation stage of ET in the western North Pacific Ocean is proposed that describes how virtually all 30 cases evolved into an incipient, baroclinic low. The three-step evolution of the transformation of Typhoon (TY) David (September 1997) is described as a prototypical example. Four important physical processes examined in each of the three steps include (i) environmental inflow of colder, drier (warm, moist) air in the western (eastern) quadrant of David’s outer circulation that initiates an asymmetric distribution of clouds and precipitation, and a dipole of lower-tropospheric temperature advection; (ii) the interaction between TY David and a preexisting, midlatitude baroclinic zone to produce ascent over tilted isentropic surfaces; (iii) systematic decay and tilt of the warm core aloft in response to vertical shear; and (iv) an evolution of David’s outer circulation into an asymmetric pattern that implies lower-tropospheric frontogenesis.

The beginning and end of the transformation stage of ET in the western North Pacific is defined based on the interaction of the tropical cyclone circulation with a preexisting, midlatitude baroclinic zone. In particular, cases that complete the transformation stage of ET become embedded in the preexisting, midlatitude baroclinic zone, with the storm center in cold, descending air. Cases that begin transformation but do not become embedded in the baroclinic zone fail to complete transformation and simply dissipate over lower sea surface temperatures and in an environment of vertical wind shear. Use of the conceptual model, together with satellite imagery and high-resolution numerical analyses and forecasts, should assist forecasters in assessing the commencement, progress, and completion of the transformation stage of ET in the western North Pacific, and result in improved forecasts and dissemination of timely, effective advisories and warnings.

Abstract

The Quality Control (QC) Division of the U.S. Navy's Fleet Numerical Oceanography Center (FNOC) is responsible for the quality control of meteorological and oceanographic analyses and forecasts issued to operational users, and for the verification of FNOC numerical model products.

The FNOC QC Division ensures the quality and consistency of data to be included in the meteorological and oceanographic analyses, adding artificial data (“bogus technique”) when needed in sparse areas or in cases of significant discrepancies. Bogus data from various sources have a direct effect on the optimum interpolation analyses for the global forecast model and are used to modify the marine wind field, the spectral wave model, the upper-level winds for the Optimum Path Aircraft Routing System, and tropical cyclone warnings. Bogus sea surface temperature data are used to enhance the FNOC ocean thermal structure analysis.

The FNOC QC performs model verifications on a daily, monthly, and seasonal basis, providing a statistical summary of the performance of the meteorological and oceanographic models and identifying their strengths and weakness.

Abstract

A statistical postprocessing technique is developed and tested to reduce the U.S. Navy global model (NOGAPS) track forecast errors for a sample of western North Pacific tropical cyclones during 1992–96. The key piece of information is the offset of the initial NOGAPS position relative to an updated (here best-track) position that will be known by 6 h after the synoptic times, which is when the NOGAPS forecast is actually available for use by the forecaster. In addition to the basic storm characteristics, the set of 24 predictors includes various segments in the 0–36-h NOGAPS forecast track as well as a 0–36-h backward extrapolation that is compared with the known recent track positions. As statistically significant regressions are only found for 12–36 h, the original 36-h to 72-h NOGAPS track segment is simply translated to the adjusted 36-h position. For the development sample, the adjusted NOGAPS track errors are reduced by about 51 n mi (95 km) at 12 h, 35 n mi (65 km) at 36 h, and 28 n mi (52 km) at 72 h. Independent tests with a 1997 western North Pacific sample, 1995–97 Atlantic sample, and 1996–97 eastern and central North Pacific sample of NOGAPS forecasts have similar improvements from the postprocessing technique. Thus, the technique appears to have a more general applicability to Northern Hemisphere tropical cyclones.

Abstract

A unique dataset observing the life cycle of Typhoon Sinlaku was collected during The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) in 2008. In this study observations of the transformation stage of the extratropical transition of Sinlaku are analyzed. Research flights with the Naval Research Laboratory P-3 and the U.S. Air Force WC-130 aircraft were conducted in the core region of Sinlaku. Data from the Electra Doppler Radar (ELDORA), dropsondes, aircraft flight level, and satellite atmospheric motion vectors were analyzed with the recently developed Spline Analysis at Mesoscale Utilizing Radar and Aircraft Instrumentation (SAMURAI) software with a 1-km horizontal- and 0.5-km vertical-node spacing. The SAMURAI analysis shows marked asymmetries in the structure of the core region in the radar reflectivity and three-dimensional wind field. The highest radar reflectivities were found in the left of shear semicircle, and maximum ascent was found in the downshear left quadrant. Initial radar echos were found slightly upstream of the downshear direction and downdrafts were primarily located in the upshear semicircle, suggesting that individual cells in Sinlaku’s eyewall formed in the downshear region, matured as they traveled downstream, and decayed in the upshear region. The observed structure is consistent with previous studies of tropical cyclones in vertical wind shear, suggesting that the eyewall convection is primarily shaped by increased vertical wind shear during step 2 of the transformation stage, as was hypothesized by Klein et al. A transition from active convection upwind to stratiform precipitation downwind is similar to that found in the principal rainband of more intense tropical cyclones.

Abstract

The structure and the environment of Typhoon Sinlaku (2008) were investigated during its life cycle in The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC). On 20 September 2008, during the transformation stage of Sinlaku’s extratropical transition (ET), research aircraft equipped with dual-Doppler radar and dropsondes documented the structure of the convection surrounding Sinlaku and low-level frontogenetical processes. The observational data obtained were assimilated with the recently developed Spline Analysis at Mesoscale Utilizing Radar and Aircraft Instrumentation (SAMURAI) software tool. The resulting analysis provides detailed insight into the ET system and allows specific features of the system to be identified, including deep convection, a stratiform precipitation region, warm- and cold-frontal structures, and a dry intrusion. The analysis offers valuable information about the interaction of the features identified within the transitioning tropical cyclone. The existence of dry midlatitude air above warm-moist tropical air led to strong potential instability. Quasigeostrophic diagnostics suggest that forced ascent during warm frontogenesis triggered the deep convective development in this potentially unstable environment. The deep convection itself produced a positive potential vorticity anomaly at midlevels that modified the environmental flow. A comparison of the operational ECMWF analysis and the observation-based SAMURAI analysis exhibits important differences. In particular, the ECMWF analysis does not capture the deep convection adequately. The nonexistence of the deep convection has considerable implications on the potential vorticity structure of the remnants of the typhoon at midlevels. An inaccurate representation of the thermodynamic structure of the dry intrusion has considerable implications on the frontogenesis and the quasigeostrophic forcing.

Abstract

An empirical orthogonal function (EOF) representation of relative vorticity is used to forecast recurvature (change in storm heading from west through north to cast of 360°) of western North Pacific tropical cyclones. A pattern recognition approach is adapted in which the synoptic conditions at recurvature time and each 12-h interval up to 96 h prior to recurvature are to be distinguished from the synoptic pattern for straight-mover storms. Synoptic descriptors are defined in terms of the time-dependent principal components of the vorticity fields for the individual maps. A standard discriminant analysis approach using 250-mb vorticity fields correctly identifies recurvers and straight movers in 80% and 66%, respectively, of the 782 cases. For a specific discriminant analysis that is derived to separate recurvers (74% correct) from straight movers (81% correct), the accuracy is higher than for the operational track prediction techniques and the official forecasts considered in Part I of this study. Although the accuracy of the discriminant analysis in identifying the lime to recurvature in 12-h intervals is less than desired for operational use, this new technique has higher accuracy than the techniques evaluated in Part I. Better accuracy can be achieved if the time resolution requirements are relaxed, for example, into three groups (0–24 h, 36–72 h, and greater than 72 h until recurvature).

Abstract

Seventy-two-hour forecasts of sea level cyclones from the Navy Operational Global Atmospheric Prediction System are examined. Cyclones that formed over the North Pacific region of maximum cyclogenesis frequency are included for study. The analysis is oriented to assist the forecaster in evaluating the numerical model guidance by emphasizing verification of operationally oriented factors (i.e., cyclogenesis, explosive deepening).

Initially, systematic errors in forecast intensities and positions are identified. Maximum underforecasting errors (forecast central pressure higher than actual central pressure) occur over the central North Pacific region of climatological maximum cyclone deepening. Maximum overforecasting errors (forecast central pressure lower than the actual central pressure) occur over the region of climatological cyclone dissipation. Maximum position errors also occur over the central North Pacific region of climatological maximum deepening. These systematic error distributions indicate that there are diagnostic relationships between forecast performance, the cyclone track type, and whether the cyclone is deepening or filling at the forecast verification time.

The forecast intensity and position errors are stratified based on the 72-h forecast intensity change, which is one possible measure of forecast accuracy that uses information known at the initial time of the forecast rather than the verifying time. Three classes of intensity change are identified as deepening, filling, and mixed deepening and filling. The systematic intensity errors mainly comprise instances when a 72-h deepening profile was not forecast and a deepening or mixed deepening-filling profile actually occurred. When the category of intensity change is correctly forecast, cyclones forecast to follow a western Pacific track tend to be overforecast, while those forecast to follow a central Pacific track tend to be underforecast. It is hypothesized that one reason for these differences may be due to the relative importance of adiabatic versus diabatic processes involved in the development of cyclones following each track type. Furthermore, central Pacific cyclones become more removed from available initializing data on the Asian continent. Position errors are more sensitive to the forecast track type rather than the forecast central-pressure profile.

Model tendencies based on the forecast intensity change and track type are presented to aid the users of the numerical guidance recognize instances when the forecast performance may be exceptionally high or low.

Abstract

The United States has had three operational numerical weather prediction centers since the Joint Numerical Weather Prediction Unit was closed in 1958. This led to separate paths for U.S. numerical weather prediction, research, technology, and operations, resulting in multiple community calls for better coordination. Since 2006, the three operational organizations—the U.S. Air Force, the U.S. Navy, and the National Weather Service—and, more recently, the Department of Energy, the National Aeronautics and Space Administration, the National Science Foundation, and the National Oceanic and Atmospheric Administration/Office of Oceanic and Atmospheric Research, have been working to increase coordination. This increasingly successful effort has resulted in the establishment of a National Earth System Prediction Capability (National ESPC) office with responsibility to further interagency coordination and collaboration. It has also resulted in sharing of data through an operational global ensemble, common software standards, and model components among the agencies. This article discusses the drivers, the progress, and the future of interagency collaboration.