Abstract

This paper describes the observational aspects of explosive East Coast cyclogenesis using composites constructed from the daily global analyses generated and archived by the European Center for Medium Range Weather Forecasts (ECMWF). An explosively deepening storm or bomb is defined following Sanders and Gyakum as an extratropical cyclone whose mean sea level pressure falls at least 1 mb per hour for 24 hours. The ECMWF datasets are used to examine the three-dimensional kinematic and thermodynamic structure of bombs over the entire depth of the troposphere. The evolution and structure of the composite bomb is diagnosed using a moving coordinate system consisting of a box with dimensions of 35°×35° of latitude-longitude.

The results reveal that explosive cyclogenesis is a baroclinic phenomenon in which the rapid development in the presence of strong upper tropospheric forcing is most likely enhanced by a highly destabilized lower troposphere. Additionally, the composite analyses of the bomb show a considerable amount of detail considering the horizontal and vertical resolution of the ECMWF data.

Abstract

Numerical experimentation of explosive East Coast cyclogenesis is performed using the Florida State University Global Spectral Model (FSUGSM). The three cases examined here are the Presidents'Day storm of 18–19 February 1979 and the North Atlantic and Pacific bombs of 18–20 January 1979 which formed off the east coasts of the United States and Japan respectively. The use of a global model provides a framework for studying the phenomena on the 3–5 day time scale. The forecast verifications of the numerical experiments indicate that the FSUGSM was able to adequately predict the phase, intensity, and synoptic-scale structure of three aforementioned cases. These results justify the use of model data for diagnostic studies of the bomb.

The model data are used to quantify the role of the adiabatic and diabatic forcing in the explosive cyclogenetic process using surface pressure tendency (SPT) to gauge development. The results of the partioning technique substantiate the fact that the bomb is fundamentally a baroclinic phenomenon in which the dynamical forcing initiates and sustains explosive development. Convective and noncenvective latent heat release were the primary physical mechanisms responsible for generating at most, roughly 40% during the later phase of case 1. The remaining physical processes that are parameterized in the FSUGSM, including the, surface fluxes of heat, moisture, and momentum, do not directly or instantaneously impact bomb development as they force less than 10% of the negative SPT.

Abstract

This paper describes an objective verification of the National Centers for Environmental Prediction 29-km Eta Model from May 1996 through January 1998. The evaluation was designed to assess the model’s surface and upper-air point forecast accuracy at three selected locations during separate warm (May–August) and cool (October–January) season periods. In order to enhance sample sizes available for statistical calculations, the objective verification includes two consecutive warm and cool season periods.

The statistical evaluation identified model biases that result from inadequate parameterization of physical processes. However, since the model biases are relatively small compared to the random error component, most of the total model error results from day-to-day variability in the forecasts and/or observations. To some extent, these nonsystematic errors reflect the variability in point observations that sample spatial and temporal scales of atmospheric phenomena that cannot be resolved by the model.

On average, Meso Eta point forecasts provide useful guidance for predicting the evolution of the larger-scale environment. A more substantial challenge facing model users in real time is the discrimination of nonsystematic errors that tend to inflate the total forecast error. It is important that users maintain awareness of ongoing model updates because they modify the basic error characteristics, particularly near the surface. While some of the changes in error were expected, others were not consistent with the intent of the model updates and further emphasize the need for ongoing sensitivity studies and localized statistical verification efforts.

Objective verification of point forecasts is a stringent measure of model performance, but when used alone, is not enough to quantify the overall value that model guidance may add to the forecast process. Therefore, results from a subjective verification of the Meso Eta Model over the Florida peninsula are discussed in the companion paper by Manobianco and Nutter.

Abstract

This paper describes a subjective evaluation of the National Centers for Environmental Prediction 29-km (Meso) Eta Model during the 1996 warm (May–August) and cool (October–January) seasons. The companion paper by Nutter and Manobianco presents results from an objective evaluation of the Meso Eta Model at three selected locations during the 1996 and 1997 warm and cool seasons. The overall evaluation is designed to assess the utility of the model for operational weather forecasting by the U.S. Air Force 45th Weather Squadron, National Weather Service (NWS) Spaceflight Meteorology Group, and NWS Office in Melbourne, Florida. In the subjective verification, limited case studies are used to highlight model capabilities and limitations in forecasting convective activity, the location and movement of cold fronts, and the onset of sea breezes over regions including east-central Florida. In addition, contingency tables and categorical scores are used to verify the occurrence of these phenomena throughout the season.

Results from the subjective verification demonstrate that model forecasts of developing weather events such as thunderstorms, sea breezes, and cold fronts are not always as accurate as might otherwise be implied by the seasonally averaged error statistics. Although the objective statistics do not indicate whether the model provides more accurate forecast guidance on average during either the warm or cool seasons, results from the subjective verification suggest that model forecasts over central Florida may be more useful during the cool season. This is because the Meso Eta Model resolution is not yet sufficient to resolve the small-scale details of sea and river/lake breeze circulations, thunderstorm outflow boundaries, and other phenomena, which play a dominant role in determining the short-term evolution of weather over east-central Florida during the warm season. Lessons learned from the subjective portion of the Meso Eta evaluation should apply equally as well to the recently upgraded “early” Eta Model running with a similar 32-km horizontal resolution.

This paper describes the capabilities and operational utility of a version of the Mesoscale Atmospheric Simulation System (MASS) that has been developed to support operational weather forecasting at the Kennedy Space Center (KSC) and Cape Canaveral Air Station (CCAS). The implementation of local, mesoscale modeling systems at KSC/CCAS is designed to provide detailed short-range (< 24 h) forecasts of winds, clouds, and hazardous weather such as thunderstorms. Short-range forecasting is a challenge for daily operations, and manned and unmanned launches since KSC/CCAS is located in central Florida where the weather during the warm season is dominated by mesoscale circulations like the sea breeze.

For this application, MASS has been modified to run on a Stardent 3000 workstation. Workstation-based, real-time numerical modeling requires a compromise between the requirement to run the system fast enough so that the output can be used before expiration balanced against the desire to improve the simulations by increasing resolution and using more detailed physical parameterizations. It is now feasible to run high-resolution mesoscale models such as MASS on local workstations to provide timely forecasts at a fraction of the cost required to run these models on mainframe supercomputers.

MASS has been running in the Applied Meteorology Unit (AMU) at KSC/CCAS since January 1994 for the purpose of system evaluation. In March 1995, the AMU began sending real-time MASS output to the forecasters and meteorologists at CCAS, Spaceflight Meteorology Group (Johnson Space Center, Houston, Texas), and the National Weather Service (Melbourne, Florida). However, MASS is not yet an operational system. The final decision whether to transition MASS for operational use will depend on a combination of forecaster feedback, the AMU's final evaluation results, and the life-cycle costs of the operational system.

Abstract

The present study uses a regional-scale numerical model to test the impact of dynamically assimilating, satellite-derived precipitation rates on the numerical simulations of one of the deepest extratropical cyclones to develop south of 40°N in this century. This cyclone event occurred during the Experiment on Rapidly Intensifying Cyclones over the Atlantic (ERICA) intensive observing period 4 and has been selected because of the strength of the cyclone and the availability of the special ERICA data in addition to the Special Sensor Microwave/Imager (SSM/I) and Geostationary Operational Environmental Satellite (GOES) infrared (IR) satellite data.

The unique methodology developed herein to synthesize the SSM/I and GOES IR satellite data produces precipitation estimates that have realistic spatial and temporal structure. The assimilation of satellite-derived precipitation is accomplished by scaling the internally generated model profiles of total latent heating. At points where the model is not producing precipitation, the vertical distribution of total latent heating given by satellite precipitation is specified from instantaneous model-based profiles at adjacent points using a search algorithm. The technique does not assume a priori that the satellite-estimated precipitation corresponds to either convective or stratiform model precipitation, and uses heating profiles that are consistent with the model's parameterization of either type of precipitation since they are not specified from externally based parabolic or other structure functions.

Several simulations are performed with and without satellite data assimilation at varying horizontal and vertical model resolutions. The results from the 80-km 40-layer control and assimilation runs demonstrate that the assimilation of satellite precipitation 1) does not introduce noise into the simulations at any time during or after the data assimilation period, 2) forces the model to reproduce the magnitude and distribution of satellite precipitation, and 3) improves the simulated central mean sea level pressure (MSLP) minima slightly, frontal positions, and, to a greater extent, the low-level vertical-motion patterns when compared with subjective analyses and satellite imagery. The model retains the information introduced by the assimilation of satellite-derived precipitation 8.5 h after the end of the data assimilation period.

An increase in the vertical and horizontal model resolution further reduces the errors in simulating the MSLP minima but does not consistently improve the cyclone position errors in the assimilation runs. Either the exclusion of the search algorithm, the doubling of satellite precipitation, or an eastward shift of satellite precipitation by 400 km increases the MSLP and position users; therefore, the impact of assimilating satellite precipitation depends on model resolution, the use of the search algorithm, and the magnitude and position of satellite precipitation. The increase in horizontal resolution generates the largest reduction in MSLP errors, while the shifting of satellite precipitation generates the largest increase in MSLP errors. The results confirm the findings of earlier studies that the impact of assimilating satellite precipitation on the subsequent simulations is less sensitive to errors in magnitude rather than to the distribution of satellite-derived precipitation and depends on the relative accuracy with which the model simulates the cyclone in the control run. Despite the fact that this study focuses on a single case, it does demonstrate the promise of using combined infrared and microwave satellite precipitation estimates to produce sustained positive impacts in mesoscale model forecasts of midlatitude cyclogenesis over data-sparse oceanic regions.

Abstract

Numerical simulations were performed with the Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model Version 5 (MM5) to study the impact of initial conditions, satellite-derived rain assimilation, and cumulus parameterization on Hurricane Florence (1988). A few modifications were made to the J. Manobianco et al. (MKKN) rain assimilation scheme, which was developed originally for midlatitude weather systems, to successfully simulate organized tropical weather systems such as Florence. These changes consist of replacing latent heating scaling with convective rainfall in the Kuo–Anthes scheme in areas where both the model-predicted and satellite-derived rainfall coincide, and specifying a normalized parabolic heating profile in deep convective regions where there is satellite rain but no model rain. Restoration of the original Kuo–Anthes heating distribution function in lieu of the fixed heating profile specified in the MM5 model is another change implemented in the Kuo–Anthes scheme.

Results from the sensitivity simulations made with the modified rain assimilation scheme show that 1) the enhanced initial conditions with the omega dropsonde data yield a positive impact on the development of Florence for both the Betts–Miller and the modified Kuo–Anthes schemes, 2) the effect of ingesting continuous (Special Sensor Microwave/Imager and Geostationary Operational Environmental Satellite Infrared) satellite-derived rainfall rates as latent heating by the modified rain assimilation scheme is much greater with the modified Kuo–Anthes scheme than with the Betts–Miller scheme, and 3) the combined impact of enhanced initial conditions and rain assimilation yields a superior simulation of Florence, particularly with the Kuo–Anthes scheme. The weak response of the Betts–Miller scheme to rain assimilation, compared to the large impact with the Kuo–Anthes scheme, appears to be related mainly to the differences in the treatment of convective rainfall and its latent heat release in respective cumulus parameterization schemes. Since the MKKN scheme mainly invokes latent heat scaling to ingest satellite rainfall, the Kuo–Anthes scheme responds to increased latent heating from satellite rainfall rates more favorably through conditional instability of the second kind (CISK)-type feedback effects than the Betts–Miller scheme. The latter result clearly suggests that the success of the modified rain assimilation scheme on development of organized tropical systems such as Hurricane Florence depends to a large extent on the choice of cumulus parameterization scheme.

Abstract

An ongoing challenge in mesoscale numerical weather prediction (NWP) is to determine the ideal method for verifying the performance of high-resolution, detailed forecasts. Traditional objective techniques that evaluate NWP model performance based on point error statistics may not be positively correlated with the value of forecast information for certain applications of mesoscale NWP, and subjective evaluation techniques are often costly and time consuming. As a result, objective event-based verification methodologies are required in order to determine the added value of high-resolution NWP models.

This paper presents a new objective technique to verify predictions of the sea-breeze phenomenon over east-central Florida by the Regional Atmospheric Modeling System (RAMS) NWP model. The contour error map (CEM) technique identifies sea-breeze transition times in objectively analyzed grids of observed and forecast wind, verifies the forecast sea-breeze transition times against the observed times, and computes the mean post-sea-breeze wind direction and wind speed to compare the observed and forecast winds behind the sea-breeze front. The CEM technique improves upon traditional objective verification techniques and previously used subjective verification methodologies because it is automated, accounts for both spatial and temporal variations, correctly identifies and verifies the sea-breeze transition times, and provides verification contour maps and simple statistical parameters for easy interpretation. The CEM algorithm details are presented and validated against independent meteorological assessments of the sea-breeze transition times and results from a previously published subjective evaluation.

Abstract

The rapid intensification of a surface cyclone that battered the Queen Elizabeth II (QE II) ocean liner in the western Atlantic Ocean during September 1978 has been the focus of several observational and model-based case studies. The storm is considered a classic example of a cyclone that undergoes explosive deepening, marked by a 60-hPa decrease of the central mean sea level pressure (MSLP) in 24 h.

The present study uses a regional-scale numerical model in conjunction with dynamic data assimilation via Newtonian relaxation (or “nudging”) to provide initial conditions for subsequent simulations of the QE II cyclone. The objectives of this paper are 1) to show that the simulations initialized from the results of 12-h precyclogenetic data-assimilation cycles (with and without bogus data) are superior to those initialized statically from the same data and 2) to resolve the evolution of the upper-level trough-jet system in the 24-h period from 0000 UTC 9 September–0000 UTC 10 September using the dynamically consistent four-dimensional (4D) datasets generated by the model.

The 4D model-generated datasets provide the spatial and temporal data resolution not afforded in the observational studies to document the structure and evolution of the dynamical forcing associated with the QE II cyclone. However, the temporal continuity of the cyclone's development, especially the evolution of the upper-level trough-jet system and the associated indirect circulations in the exit region of the upper-tropospheric jet streak, is interrupted at the end of the nudging cycle. This problem poses a limitation for using the 4D datasets for diagnostic studies of the QE II cyclone in the precyclogenetic period during the data-assimilation cycle.

Dynamic data assimilation and the inclusion of supplementary data both have a large positive impact on the simulated position and intensity of the QE II cyclone from 1200 UTC 9 September to 0000 UTC 10 September during the initial phase of rapid cyclone development. These runs capture the developing cyclone and associated rate of MSLP falls at 1200 UTC 9 September, whereas the runs based on static initialization delay the deepening six to nine hours into the model simulation. The diagnostic analyses based on these simulations show that the initial development of the QE II storm between 0000 UTC 9 September and 0000 UTC 10 September was embedded within an indirect circulation of an intense 300-hPa jet streak, was related to baroclinic processes that extended throughout a deep portion of the troposphere and was associated with a classic two-layer mass-divergence profile expected for an extratropical cyclone.

The runs initialized from data-assimilation cycles, including the bogus data, still underestimate the MSLP of the QE II cyclone by 30% at 24 h into the simulations (1200 UTC 10 September). These results provide further supporting evidence that increasing the horizontal model resolution and improving the subgrid-scale physical parameterizations (especially the precipitation schemes) may be required to simulate the most rapid development phase of the QE II cyclone.

Abstract

Seven years of wind and temperature data from a high-resolution network of 44 towers at the Kennedy Space Center and Cape Canaveral Air Force Station were used to develop an objective method for identifying land breezes, which are defined as seaward-moving wind shift lines in this study. The favored meteorological conditions for land breezes consisted of surface high pressure in the vicinity of the Florida peninsula, mainly clear skies, and light synoptic onshore flow and/or the occurrence of a sea breeze during the afternoon preceding a land breeze. The land breeze characteristics are examined for two events occurring under different weather regimes—one with light synoptic onshore flow and no daytime sea breeze, and another following a daytime sea breeze under a prevailing offshore flow. Land breezes were found to occur over east-central Florida in all months of the year and had varied onset times and circulation depths. Land breezes were most common in the spring and summer months and least common in the winter. The average onset times were ∼4–5 h after sunset from May to July and ∼6.5–8 h after sunset from October to January. Land breezes typically moved from the west or southwest during the spring and summer, from the northwest in the autumn, and nearly equally from all directions in the winter. Shallow land breezes (<150-m depth) were typically not associated with the afternoon sea breeze and behaved like density currents, exhibiting the largest temperature decreases and latest onset times. Deep land breezes (>150-m depth) were most often preceded by an afternoon sea breeze, had the smallest horizontal temperature gradients, and experienced a mean onset time that is 4 h earlier than that of shallow land breezes.