bluuebunny/crossref_metadata_2025_split huggingface dataset:
Climatological Characteristics and Seasonal Forecasting of Tropical Cyclones Making Landfall along the South China Coast
Authors: Liu K. S. , Chan Johnny C. L. 
Published: July 2003

Abstract
This paper presents the important climatological features of the tropical cyclones making landfall along the South China coast and proposes a statistical scheme for the prediction of the annual number of such tropical cyclones. This number is found to have a large variation, which is mainly due to the occurrence or nonoccurrence of the El Niño–Southern Oscillation (ENSO) phenomenon. A strong El Niño event is found to reduce the number of landfalling tropical cyclones whereas more tropical cyclones tend to make landfall in years associated with La Niña events. Such variations are more prominent in some seasons. The late season (October–November) activity is generally suppressed (enhanced) in El Niño (La Niña) years whereas the chance of a tropical cyclone striking the South China coast increases (decreases) significantly in the early season (May and June) after the mature phase of a La Niña (El Niño) event. These anomalous activities are apparently linked to the ENSO-induced anomalies in the low- and midlevel large-scale circulation.
Based on the ENSO-related indices such as the Niño-3.4 sea surface temperature anomaly and the equatorial Southern Oscillation index, a statistical prediction scheme for the annual number of such landfalling tropical cyclones by 1 April is developed using the projection–pursuit regression technique. This scheme provides a 40% skill improvement in root-mean-square error with respect to climatology. A real-time prediction made in 2001 gave reasonable results.
Assimilation of Simulated Doppler Radar Observations with an Ensemble Kalman Filter*
Authors: Snyder Chris , Zhang Fuqing 
Published: July 2003

Abstract
Assimilation of Doppler radar data into cloud models is an important obstacle to routine numerical weather prediction for convective-scale motions; the difficulty lies in initializing fields of wind, temperature, moisture, and condensate given only observations of radial velocity and reflectivity from the radar. This paper investigates the potential of the ensemble Kalman filter (EnKF), which estimates the covariances between observed variables and the state through an ensemble of forecasts, to assimilate radar observations at convective scales. In the basic experiment, simulated observations are extracted from a reference simulation of a splitting supercell and assimilated using the EnKF and the same numerical model that produced the reference simulation. The EnKF produces accurate analyses, including the unobserved variables, after roughly 30 min (or six scans) of radial velocity observations. Additional experiments, in which forecasts are made from the ensemble-mean analysis, reveal that forecast errors grow significantly in this simple system, so that the ability of the EnKF to track the reference solution is not simply because of stable system dynamics. It is also found that the covariances between radial velocity and temperature, moisture, and condensate are important to the quality of the analyses, as is the initialization chosen for the ensemble members prior to assimilating the first observations. These results are promising, especially given the ease of implementing the EnKF. A number of important issues remain, however, including the initialization of the ensemble prior to the first observation, the treatment of uncertainty in the environmental sounding, the role of error in the forecast model (particularly the microphysical parameterizations), and the treatment of lateral boundary conditions.
Cell Merger Potential in Multicell Thunderstorms of Weakly Sheared Environments: Cell Separation Distance versus Planetary Boundary Layer Depth
Authors: Stalker James R. , Knupp Kevin R. 
Published: July 2003

Abstract
Using high-resolution three-dimensional numerical experiments, this paper shows that the cell separation distance scales as 0.75 times the planetary boundary layer (PBL) depth for successful cell mergers between constructively interacting cells within multicell thunderstorms. This boundary layer scaling is determined from several simulations of convective cell pairs with a fixed PBL depth and is shown to be valid for other sensitivity simulations with larger PBL depths. This research establishes a robust and quantitative relation between prestorm ambient conditions and cell merger potential useful for research efforts on the multifaceted cell merger process of multicell thunderstorms. The weakly sheared ambient prestorm conditions of the 9 August 1991 Convection and Precipitation/Electrification Experiment (CaPE) multicell thunderstorm are used to initialize the cell pair simulations.
Since ambient wind and wind shear are assumed to be zero, only simple cell mergers, defined in this study as those between cell updraft cores joined but not overlapping in the convective stage, are shown to be possible. The coarse-resolution simulations of Stalker suggest that ambient wind shear may be necessary for forced cell mergers, defined in this study as those in which the initial updraft cores are found apart. The scenarios of overlapping initial updraft cores for cell merger are considered physically invalid in this study.
Applying a Neural Network Collocation Method to an Incompletely Known Dynamical System via Weak Constraint Data Assimilation
Authors: Liaqat Ali , Fukuhara Makoto , Takeda Tatsuoki 
Published: July 2003

Abstract
A method based on a neural network collocation method is proposed for approximating incompletely known dynamical systems via weak constraint data assimilation formulation. The aim of the new method is to solve several difficult issues encountered in previous research. For this purpose, the weak constraint property of the neural network collocation method is used. The problem regarding the wider assimilation window is tackled by interconnecting narrower windows with finite overlapping interfaces. The method is examined by considering the Lorenz system as an example where one of the three equations of the system is unknown. The object function of the neural network training is composed of squared residuals of differential equations at collocation points and squared deviations of the observations from their corresponding calculated values.
The weakly and highly nonlinear cases of the Lorenz system are considered. The numerical experiments have been carried out with simulated noiseless and noisy observation data under various conditions. The performance of the method for approximating an unknown equation during the assimilation and testing periods is examined for the two cases. Also, the parameters of incomplete dynamical systems are estimated for the two cases. Satisfactory results have been obtained in both cases.
A Study of Subseasonal Predictability
Authors: Newman Matthew , Sardeshmukh Prashant D. , Winkler Christopher R. , Whitaker Jeffrey S. 
Published: July 2003

Abstract
The predictability of weekly averaged circulation anomalies in the Northern Hemisphere, and diabatic heating anomalies in the Tropics, is investigated in a linear inverse model (LIM) derived from their observed simultaneous and time-lag correlation statistics. In both winter and summer, the model's forecast skill at week 2 (days 8–14) and week 3 (days 15–21) is comparable to that of a comprehensive global medium-range forecast (MRF) model developed at the National Centers for Environmental Prediction (NCEP). Its skill at week 3 is actually higher on average, partly due to its better ability to forecast tropical heating variations and their influence on the extratropical circulation. The geographical and temporal variations of forecast skill are also similar in the two models. This makes the much simpler LIM an attractive tool for assessing and diagnosing atmospheric predictability at these forecast ranges.
The LIM assumes that the dynamics of weekly averages are linear, asymptotically stable, and stochastically forced. In a forecasting context, the predictable signal is associated with the deterministic linear dynamics, and the forecast error with the unpredictable stochastic noise. In a low-order linear model of a high-order chaotic system, this stochastic noise represents the effects of both chaotic nonlinear interactions and unresolved initial components on the evolution of the resolved components. Its statistics are assumed here to be state independent.
An average signal-to-noise ratio is estimated at each grid point on the hemisphere and is then used to estimate the potential predictability of weekly variations at the point. In general, this predictability is about 50% higher in winter than summer over the Pacific and North America sectors; the situation is reversed over Eurasia and North Africa. Skill in predicting tropical heating variations is important for realizing this potential skill. The actual LIM forecast skill has a similar geographical structure but weaker magnitude than the potential skill.
In this framework, the predictable variations of forecast skill from case to case are associated with predictable variations of signal rather than of noise. This contrasts with the traditional emphasis in studies of shorter-term predictability on flow-dependent instabilities, that is, on the predictable variations of noise. In the LIM, the predictable variations of signal are associated with variations of the initial state projection on the growing singular vectors of the LIM's propagator, which have relatively large amplitude in the Tropics. At times of strong projection on such structures, the signal-to-noise ratio is relatively high, and the Northern Hemispheric circulation is not only potentially but also actually more predictable than at other times.
Ensemble Forecasts and the Properties of Flow-Dependent Analysis-Error Covariance Singular Vectors
Authors: Hamill Thomas M. , Snyder Chris , Whitaker Jeffrey S. 
Published: July 2003

Abstract
Approximations to flow-dependent analysis-error covariance singular vectors (AEC SVs) were calculated in a dry, T31 L15 primitive-equation global model. Sets of 400-member ensembles of analyses were generated by an ensemble-based data assimilation system. A sparse network of simulated rawinsonde observations were assimilated, and a perfect model was assumed. Ensembles of 48-h forecasts were also generated from these analyses. The structure of evolved singular vectors was determined by finding the linear combination of the forecast ensemble members that resulted in the largest forecast-error variance, here measured in a total-energy norm north of 20°N latitude. The same linear combination of analyses specifies the initial-time structure that should evolve to the forecast singular vector under assumptions of linearity of error growth.
The structures of these AEC SVs are important because they represent the analysis-error structures associated with the largest forecast errors. If singular vectors using other initial norms have very different structures, this indicates that these structures may be statistically unlikely to occur. The European Centre for Medium-Range Weather Forecasts currently uses singular vectors using an initial total-energy norm [“total-energy singular vectors” or (TE SVs)] to generate perturbations to initialize their ensemble forecasts. Approximate TE SVs were also calculated by drawing an initial random ensemble with perturbations that were white in total energy and applying the same approach as for AEC SVs. Comparing AEC SVs and approximate TE SVs, the AEC SVs had maximum amplitude in midlatitudes near the tropopause, both at the initial and evolved times. The AEC SVs were synoptic in scale, deep, and did not appear to be geographically localized nor tilted dramatically upshear. This contrasts with TE SVs, which started off relatively smaller in scale, were tilted upshear, and had amplitudes typically largest in the lower to midtroposphere.
The difference between AEC SVs and TE SVs suggests that operational ensemble forecasts based on TE SVs could be improved by changing the type of singular vector used to generate initial perturbations. This is particularly true for short-range ensemble forecasts, where the structure of the forecast ensemble is more closely tied to the analysis ensemble.
Comparative Analysis of Conformal Mappings Used in Limited-Area Models of Numerical Weather Prediction
Authors: Bourchtein Andrei , Bourchtein Ludmila 
Published: July 2003

Abstract
Conformal separable projections from a sphere onto a plane are introduced to generalize the concept of conformal stereographic, conic, and cylindrical projections. The concept of equivalence of projections is used for partition of all considered projections into equivalence classes. The variation coefficient is defined as the ratio between maximum and minimum mesh sizes of numerical grids. The problem of minimization of this coefficient inside each equivalence class is studied. The obtained variation coefficients from all classes are compared and the principal relation among stereographic, cylindrical, and conic projections is established. The stereographic conformal projection is indicated as that which generates the “best” numerical grids for numerical weather prediction limited-area models.
Large-Scale Circulation Patterns Associated with Heavy Spring Rain Events over Taiwan in Strong ENSO and Non-ENSO Years
Authors: Jiang Zhihong , Tai-Jen Chen George , Wu Ming-Chin 
Published: July 2003

Abstract
Daily rainfall data at 15 stations in Taiwan and the grid dataset of the National Centers for Environmental Prediction–National Center for Atmospheric Research during the period of February–March 1951–2000 were used to reveal the characteristics of large-scale circulations associated with spring heavy rain events over Taiwan in strong ENSO and non-ENSO years. The effect of interdecadal variation on the relationship of spring rainfall and ENSO was also examined.
Results showed that the different regimes of interdecadal variation that occurred in the late 1970s exert significant effect on the relationship between ENSO and spring rainfall in Taiwan. A pronounced positive correlation with statistical significance between cold season Niño-3 SST and the following spring rainfall over western Taiwan was only found since the late 1970s. Large-scale environmental conditions associated with the heavy spring rain events in strong ENSO and non-ENSO years were found to be quite different. Intrusion of a weak midlatitude frontal system into the eastern China coastal area coupled with an anomalous anticyclone over the Philippine Sea (PSAC) in the lower troposphere were primarily responsible for the spring heavy rain events in strong ENSO years. On the other hand, the intrusion of a much more intense midlatitude frontal system into China and the coastal area was necessary to generate spring heavy rain events in non-ENSO years. This difference is also instrumental for more frequent occurrence of heavy rainfall events and more rainfall amount observed in ENSO years.
Sea Surface Temperature Variability in Hurricanes: Implications with Respect to Intensity Change
Authors: Cione Joseph J. , Uhlhorn Eric W. 
Published: July 2003

Abstract
Scientists at NOAA's Hurricane Research Division recently analyzed the inner-core upper-ocean environment for 23 Atlantic, Gulf of Mexico, and Caribbean hurricanes between 1975 and 2002. The interstorm variability of sea surface temperature (SST) change between the hurricane inner-core environment and the ambient ocean environment ahead of the storm is documented using airborne expendable bathythermograph (AXBT) observations and buoy-derived archived SST data. The authors demonstrate that differences between inner-core and ambient SST are much less than poststorm, “cold wake” SST reductions typically observed (i.e., ∼0°–2°C versus 4°–5°C). These findings help define a realistic parameter space for storm-induced SST change within the important high-wind inner-core hurricane environment. Results from a recent observational study yielded estimates of upper-ocean heat content, upper-ocean energy extracted by the storm, and upper-ocean energy utilization for a wide range of tropical systems. Results from this analysis show that, under most circumstances, the energy available to the tropical cyclone is at least an order of magnitude greater than the energy extracted by the storm. This study also highlights the significant impact that changes in inner-core SST have on the magnitude of air–sea fluxes under high-wind conditions. Results from this study illustrate that relatively modest changes in inner-core SST (order 1°C) can effectively alter maximum total enthalpy (sensible plus latent heat) flux by 40% or more.
The magnitude of SST change (ambient minus inner core) was statistically linked to subsequent changes in storm intensity for the 23 hurricanes included in this research. These findings suggest a relationship between reduced inner-core SST cooling (i.e., increased inner-core surface enthalpy flux) and tropical cyclone intensification. Similar results were not found when changes in storm intensity were compared with ambient SST or upper-ocean heat content conditions ahead of the storm. Under certain circumstances, the variability associated with inner-core SST change appears to be an important factor directly linked to the intensity change process.
The Deep-Atmosphere Euler Equations in a Generalized Vertical Coordinate
Authors: Staniforth Andrew , Wood Nigel 
Published: July 2003

Abstract
Previous analysis of the hydrostatic primitive equations using a generalized vertical coordinate is extended to the deep-atmosphere nonhydrostatic Euler equations, and some special vertical coordinates of interest are noted. Energy and axial angular momentum budgets are also derived. This would facilitate the development of conserving finite-difference schemes for deep-atmosphere models. It is found that the implied principles of energy and axial angular momentum conservation depend on the form of the upper boundary. In particular, for a modeled atmosphere of finite extent, global energy conservation is only obtained for a rigid lid, fixed in space and time. To additionally conserve global axial angular momentum, the height of the lid cannot vary with longitude.
Short-Term Performance of MM5 with Cloud-Cover Assimilation from Satellite Observations
Authors: Yucel Ismail , James Shuttleworth W. , Gao X. , Sorooshian S. 
Published: July 2003

Abstract
This study investigates the extent to which assimilating high-resolution remotely sensed cloud cover into the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) provides an improved regional diagnosis of downward shortwave surface radiation fluxes and precipitation and enhances the model's ability to make short-range prediction. The high-resolution (4 km × 4 km) clear- and cloudy-sky radiances derived using a cloud-screening algorithm from visible band Geostationary Operational Environmental Satellite (GOES) data were used in the University of Maryland Global Energy and Water Cycle Experiment's Surface Radiation Budget (UMD GEWEX/SRB) model to infer the vertically integrated cloud mass via cloud optical thickness. Three-dimensional cloud fields were created that took their horizontal distribution from the satellite image but derived their vertical distribution, in part, from the fields simulated by MM5 during the time step immediately prior to assimilation and, in part, from the observed cloud-top height derived from the infrared band of GOES. Linear interpolation was used to derive 1-min cloud images between 15-min GOES samples, and the resulting images were ingested every minute. Comparisons were made between modeled and observed data taken from the Arizona Meteorological Network (AZMET) in southern Arizona for model runs with and without cloud ingestion. Cloud ingestion substantially improved the ability of the MM5 model to capture temporal and spatial variations in surface fields associated with cloud cover. Experiments in which the model was operated in forecast mode suggest that cloud ingestion gave some limited enhancement in MM5 short-term prediction ability for up to 3 h. However, an analysis suggests that, in order to get additional forecasting capability, it will be necessary to modify the atmospheric dynamics and thermodynamics in the model to be consistent with the ingested cloud fields.
Evolution of Cloud-to-Ground Lightning and Storm Structure in the Spencer, South Dakota, Tornadic Supercell of 30 May 1998
Authors: Carey Lawrence D. , Petersen Walter A. , Rutledge Steven A. 
Published: July 2003

Abstract
On 30 May 1998, a tornado devastated the town of Spencer, South Dakota. The Spencer tornado (rated F4 on the Fujita tornado intensity scale) was the third and most intense of five tornadoes produced by a single supercell storm during an approximate 1-h period. The supercell produced over 76% positive cloud-to-ground (CG) lightning and a peak positive CG flash rate of 18 flashes min−1 (5-min average) during a 2-h period surrounding the tornado damage. Earlier studies have reported anomalous positive CG lightning activity in some supercell storms producing violent tornadoes. However, what makes the CG lightning activity in this tornadic storm unique is the magnitude and timing of the positive ground flashes relative to the F4 tornado. In previous studies, supercells dominated by positive CG lightning produced their most violent tornado after they attained their maximum positive ground flash rate, whenever the rate exceeded 1.5 flashes min−1. Further, tornadogenesis often occurred during a lull in CG lightning activity and sometimes during a reversal from positive to negative polarity. Contrary to these findings, the positive CG lightning flash rate and percentage of positive CG lightning in the Spencer supercell increased dramatically while the storm was producing F4 damage on Spencer.
These results have important implications for the use of CG lightning in the nowcasting of tornadoes and for the understanding of cloud electrification in these unique storms. In order to further explore these issues, the authors present detailed analyses of storm evolution and structure using Sioux Falls, South Dakota, (KFSD) Weather Surveillance Radar-1988 Doppler (WSR-88D) radar reflectivity and Doppler velocity and National Lightning Detection Network (NLDN) CG lightning data. The analyses suggest that a merger between the Spencer supercell and a squall line on its rear flank may have provided the impetus for both the F4 tornadic damage and the dramatic increase in positive CG lightning during the tornado, possibly explaining the difference in timing compared to past studies.