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John A. Knaff

Abstract

A method to predict the June–September (JJAS) Caribbean sea level pressure anomalies (SLPAs) using data available the previous April is described. The method involves the creation of a multiple linear regression equation that uses three predictors. These predictors are the January–March (JFM) North Atlantic (50°–60°N, 10°–50°W) sea surface temperature anomalies (SSTAs), JFM Niño 3.4 (5°N–5°S, 120°–170°W) SSTAs, and the strength of the eastern Atlantic subtropical pressure ridge measured in March between 20° and 30°W. The physical role of each of the predictors in determining the variations of Caribbean SLPAs is discussed. The forecast equation is developed using a training dataset covering the period 1950–95 (46 yr) and is tested upon independent data covering the period 1903–49 where the data availability permits (42 yr). Results suggest that skillful forecasts are possible. The method reduced the interannual variance of the JJAS Caribbean SLPAs by 50% in the developmental dataset and by 40% in the independent dataset. Separate forecasts for the June–July and August–September SLPAs are also developed, tested, and discussed.

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John A. Knaff

Abstract

This study explores the inverse relationship between sea level pressure and tropical cyclones in the tropical Atlantic (TA). Upper-air observations, the National Centers for Environmental Prediction (formerly the National Meteorological Center)/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, and regional SSTs provide clues as to the physics of this relationship using composite and regression methods. Stratification of upper-air data by sea level pressure anomalies in the TA yields several interesting results, including anomalously high (low) pressure association with relatively dry (moist) middle levels, cooler (warmer) midlevel temperatures, and stronger (weaker) 200–850-mb vertical wind shears. The configuration of these composite wind differences suggests that higher summertime pressure in the TA is associated with an anomalously strong tropical upper tropospheric trough (TUTT) circulation. The observations show systematic association between the composite moisture, temperature, and wind differences. Studies of longwave sensitivity using a two stream model show that the moisture field dominates the longwave radiative cooling; hence, dry midlevels enhance cooling of the atmosphere. The effects of SST variations and tropical cyclones on TA pressure anomalies suggest that summertime pressure in this region is strongly influenced by additional (unresolved) climate forcings. These findings lead to a hypothesis that explains both the persistent nature of the summertime pressure (in the TA) as well as how variations of this pressure modulate the TUTT circulation strength. The hypothesis states that positive feedbacks operate between pressure/subsidence variations, midlevel moisture, and differential longwave radiative cooling that affects local baroclinicity (i.e., TUTT). When pressures are anomalously high, subsidence is greater and middle levels are dryer, resulting in increased atmospheric cooling to space and increased baroclinicity. Hence, pressure-related variations of both the midlevel moisture field and the TUTT circulation result in modulations of the upper-level winds and vertical wind shears in the TA. These, in turn, are found to be the primary cause of the observed pressure–tropical cyclone relationship; higher tropical Atlantic pressure results in an environment that is dryer and more sheared and, thus, less favorable for tropical cyclone formation and development.

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Mark DeMaria, John A. Knaff, and John Kaplan

Abstract

A method is developed to adjust the Kaplan and DeMaria tropical cyclone inland wind decay model for storms that move over narrow landmasses. The basic assumption that the wind speed decay rate after landfall is proportional to the wind speed is modified to include a factor equal to the fraction of the storm circulation that is over land. The storm circulation is defined as a circular area with a fixed radius. Application of the modified model to Atlantic Ocean cases from 1967 to 2003 showed that a circulation radius of 110 km minimizes the bias in the total sample of landfalling cases and reduces the mean absolute error of the predicted maximum winds by about 12%. This radius is about 2 times the radius of maximum wind of a typical Atlantic tropical cyclone. The modified decay model was applied to the Statistical Hurricane Intensity Prediction Scheme (SHIPS), which uses the Kaplan and DeMaria decay model to adjust the intensity for the portion of the predicted track that is over land. The modified decay model reduced the intensity forecast errors by up to 8% relative to the original decay model for cases from 2001 to 2004 in which the storm was within 500 km from land.

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John A. Knaff and John F. Weaver

Abstract

A large, low-level thunderstorm outflow boundary was observed as it exited from beneath the cirrus canopy of Hurricane Luis following a period of intense convection in the storm’s eyewall. A description of the feature and a short summary of its behavior are presented.

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John Kaplan, Mark DeMaria, and John A. Knaff

Abstract

A revised rapid intensity index (RII) is developed for the Atlantic and eastern North Pacific basins. The RII uses large-scale predictors from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) to estimate the probability of rapid intensification (RI) over the succeeding 24 h utilizing linear discriminant analysis. Separate versions of the RII are developed for the 25-, 30-, and 35-kt RI thresholds, which represent the 90th (88th), 94th (92nd), and 97th (94th) percentiles of 24-h overwater intensity changes of tropical and subtropical cyclones in the Atlantic (eastern North Pacific) basins from 1989 to 2006, respectively. The revised RII became operational at the NHC prior to the 2008 hurricane season.

The relative importance of the individual RI predictors is shown to differ between the two basins. Specifically, the previous 12-h intensity change, upper-level divergence, and vertical shear have the highest weights for the Atlantic basin, while the previous 12-h intensity change, symmetry of inner-core convection, and the difference in a system’s current and maximum potential intensity are weighted highest in the eastern North Pacific basin.

A verification of independent forecasts from the 2006 and 2007 hurricane seasons shows that the probabilistic RII forecasts are generally skillful in both basins when compared to climatology. Moreover, when employed in a deterministic manner, the RII forecasts were superior to all other available operational intensity guidance in terms of the probability of detection (POD) and false alarm ratio (FAR). Specifically, the POD for the RII ranged from 15% to 59% (53% to 73%) while the FAR ranged from 71% to 85% (53% to 79%) in the Atlantic (eastern North Pacific) basins, respectively, for the three RI thresholds studied. Nevertheless, the modest POD and relatively high FAR of the RII and other intensity guidance demonstrate the difficulty of predicting RI, particularly in the Atlantic basin.

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John A. Knaff and Raymond M. Zehr

Abstract

Tropical cyclone wind–pressure relationships are reexamined using 15 yr of minimum sea level pressure estimates, numerical analysis fields, and best-track intensities. Minimum sea level pressure is estimated from aircraft reconnaissance or measured from dropwindsondes, and maximum wind speeds are interpolated from best-track maximum 1-min wind speed estimates. The aircraft data were collected primarily in the Atlantic but also include eastern and central North Pacific cases. Global numerical analyses were used to estimate tropical cyclone size and environmental pressure associated with each observation. Using this dataset (3801 points), the influences of latitude, tropical cyclone size, environmental pressure, and intensification trend on the tropical cyclone wind–pressure relationships were examined. Findings suggest that latitude, size, and environmental pressure, which all can be quantified in an operational and postanalysis setting, are related to predictable changes in the wind–pressure relationships. These factors can be combined into equations that estimate winds given pressure and estimate pressure given winds with greater accuracy than current methodologies. In independent testing during the 2005 hurricane season (524 cases), these new wind–pressure relationships resulted in mean absolute errors of 5.3 hPa and 6.2 kt compared with the 7.7 hPa and 9.0 kt that resulted from using the standard Atlantic Dvorak wind–pressure relationship. These new wind–pressure relationships are then used to evaluate several operational wind–pressure relationships. These intercomparisons have led to several recommendations for operational tropical cyclone centers and those interested in reanalyzing past tropical cyclone events.

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John A. Knaff and Christopher W. Landsea

Abstract

A statistical prediction method, which is based entirely on the optimal combination of persistence, month-to-month trend of initial conditions, and climatology, is developed for the El Niño–Southern Oscillation (ENSO) phenomena. The selection of predictors is by design intended to avoid any pretense of predictive ability based on “model physics” and the like, but rather is to specify the optimal “no-skill” forecast as a baseline comparison for more sophisticated forecast methods. Multiple least squares regression using the method of leaps and bounds is employed to test a total of 14 possible predictors for the selection of the best predictors, based upon 1950–94 developmental data. A range of zero to four predictors were chosen in developing 12 separate regression models, developed separately for each initial calendar month. The predictands to be forecast include the Southern Oscillation (pressure) index (SOI) and the Niño 1+2, Niño 3, Niño 4, and Niño 3.4 SST indices for the equatorial eastern and central Pacific at lead times ranging from zero seasons (0–2 months) through seven seasons (21–23 months). Though hindcast ability is strongly seasonally dependent, substantial improvement is achieved over simple persistence wherein largest gains occur for two–seven-season (6–23 months) lead times. For example, expected maximum forecast ability for the Niño 3.4 SST region, depending on the initial date, reaches 92%, 85%, 64%, 41%, 36%, 24%, 24%, and 28% of variance for leads of zero to seven seasons. Comparable maxima of persistence only forecasts explain 92%, 77%, 50%, 17%, 6%, 14%, 21%, and 17%, respectively. More sophisticated statistical and dynamic forecasting models are encouraged to utilize this ENSO-CLIPER model in place of persistence when assessing whether they have achieved forecasting skill; to this end, real-time results for this model are made available via a Web site.

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John A. Knaff and Robert T. DeMaria

Abstract

The development of an infrared (IR; specifically near 11 μm) eye probability forecast scheme for tropical cyclones is described. The scheme was developed from an eye detection algorithm that used a linear discriminant analysis technique to determine the probability of an eye existing in any given IR image given information about the storm center, motion, and latitude. Logistic regression is used for the model development and predictors were selected from routine information about the current storm (e.g., current intensity), forecast environmental factors (e.g., wind shear, oceanic heat content), and patterns/information (e.g., convective organization, tropical cyclone size) extracted from the current IR image. Forecasts were created for 6-, 12-, 18-, 24-, and 36-h forecast leads. Forecasts were developed using eye existence probabilities from North Atlantic tropical cyclone cases (1996–2014) and a combined North Atlantic and North Pacific (i.e., Northern Hemisphere) sample. The performance of North Atlantic–based forecasts, tested using independent eastern Pacific tropical cyclone cases (1996–2014), shows that the forecasts are skillful versus persistence at 12–36 h, and skillful versus climatology at 6–36 h. Examining the reliability and calibration of those forecasts shows that calibration and reliability of the forecasts is good for 6–18 h, but forecasts become a little overconfident at longer lead times. The forecasts also appear unbiased. The small differences between the Atlantic and Northern Hemisphere formulations are discussed. Finally, and remarkably, there are indications that smaller TCs are more prone to form eye features in all of the TC areas examined.

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Kotaro Bessho, Mark DeMaria, and John A. Knaff

Abstract

Horizontal winds at 850 hPa from tropical cyclones retrieved using the nonlinear balance equation, where the mass field was determined from Advanced Microwave Sounding Unit (AMSU) temperature soundings, are compared with the surface wind fields derived from NASA's Quick Scatterometer (QuikSCAT) and Hurricane Research Division H*Wind analyses. It was found that the AMSU-derived wind speeds at 850 hPa have linear relations with the surface wind speeds from QuikSCAT or H*Wind. There are also characteristic biases of wind direction between AMSU and QuikSCAT or H*Wind. Using this information to adjust the speed and correct for the directional bias, a new algorithm was developed for estimation of the tropical cyclone surface wind field from the AMSU-derived 850-hPa winds. The algorithm was evaluated in two independent cases from Hurricanes Floyd (1999) and Michelle (2001), which were observed simultaneously by AMSU, QuikSCAT, and H*Wind. In this evaluation the AMSU adjustment algorithm for wind speed worked well. Results also showed that the bias correction algorithm for wind direction has room for improvement.

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Charles R. Sampson and John A. Knaff

Abstract

The National Hurricane Center (NHC) has been forecasting gale force wind radii for many years, and more recently (starting in 2004) began routine postanalysis or “best tracking” of the maximum radial extent of gale [34 knots (kt; 1 kt = 0.514 m s−1)] force winds in compass quadrants surrounding the tropical cyclone (wind radii). At approximately the same time, a statistical wind radii forecast, based solely on climatology and persistence, was implemented so that wind radii forecasts could be evaluated for skill. If the best-track gale radii are used as ground truth (even accounting for random errors in the analyses), the skill of the NHC forecasts appears to be improving at 2- and 3-day lead times, suggesting that the guidance has also improved. In this paper several NWP models are evaluated for their skill, an equally weighted average or “consensus” of the model forecasts is constructed, and finally the consensus skill is evaluated. The results are similar to what is found with tropical cyclone track and intensity in that the consensus skill is comparable to or better than that of the individual models. Furthermore, the consensus skill is high enough to be of potential use as forecast guidance or as a proxy for official gale force wind radii forecasts at the longer lead times.

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