bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Convection East of the Andes Cordillera: A Test Case Analysis of Airmass Origin
Authors: Teitelbaum Hector , Le Treut Hervé , Moustaoui Mohamed , Cabrera Gustavo C. , Ibañez Guillermo 
Published: July 2008

Abstract
Warm and moist air masses, required to generate deep convection east of the Andes Cordillera, are generally the result of humidity transport by the so-called low-level jet (LLJ). In this paper, it is shown from detailed test cases that the eastern part of the continent and the adjacent Atlantic Ocean may constitute another source of moist, warm air, which could be of potential importance even in the presence of a southerly LLJ. The position of the anticyclones crossing South America from the Pacific Ocean to the Atlantic Ocean appears to be a key factor affecting the origin of moisture over the continent. In particular, the LLJ may weaken and even change its direction when the eastern side of the South Pacific anticyclone crosses the mountains; this wind reversal is generally associated with deep convection suppression. Thus, as a South Pacific anticyclone crosses the continent more to the east and its western side reaches the east coast of South America, deep convection can reappear east of the Andes, over the Mendoza region, although the LLJ is frequently suppressed. This is associated with a transport of warm and moist air from Uruguay, southeast Brazil, or even directly from the Atlantic Ocean.
A Comparison of Two Shallow-Water Models with Nonconforming Adaptive Grids
Authors: St-Cyr Amik , Jablonowski Christiane , Dennis John M. , Tufo Henry M. , Thomas Stephen J. 
Published: July 2008

Abstract
In an effort to study the applicability of adaptive mesh refinement (AMR) techniques to atmospheric models, an interpolation-based spectral element shallow-water model on a cubed-sphere grid is compared to a block-structured finite-volume method in latitude–longitude geometry. Both models utilize a nonconforming adaptation approach that doubles the resolution at fine–coarse mesh interfaces. The underlying AMR libraries are quad-tree based and ensure that neighboring regions can only differ by one refinement level. The models are compared via selected test cases from a standard test suite for the shallow-water equations, and via a barotropic instability test. These tests comprise the passive advection of a cosine bell and slotted cylinder, a steady-state geostrophic flow, a flow over an idealized mountain, a Rossby–Haurwitz wave, and the evolution of a growing barotropic wave. Both static and dynamics adaptations are evaluated, which reveal the strengths and weaknesses of the AMR techniques. Overall, the AMR simulations show that both models successfully place static and dynamic adaptations in local regions without requiring a fine grid in the global domain. The adaptive grids reliably track features of interests without visible distortions or noise at mesh interfaces. Simple threshold adaptation criteria for the geopotential height and the relative vorticity are assessed.
Development and Testing of Polar Weather Research and Forecasting (WRF) Model. Part I: Greenland Ice Sheet Meteorology*
Authors: Hines Keith M. , Bromwich David H. 
Published: July 2008

Abstract
A polar-optimized version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) was developed to fill climate and synoptic needs of the polar science community and to achieve an improved regional performance. To continue the goal of enhanced polar mesoscale modeling, polar optimization should now be applied toward the state-of-the-art Weather Research and Forecasting (WRF) Model. Evaluations and optimizations are especially needed for the boundary layer parameterization, cloud physics, snow surface physics, and sea ice treatment. Testing and development work for Polar WRF begins with simulations for ice sheet surface conditions using a Greenland-area domain with 24-km resolution. The winter month December 2002 and the summer month June 2001 are simulated with WRF, version 2.1.1, in a series of 48-h integrations initialized daily at 0000 UTC. The results motivated several improvements to Polar WRF, especially to the Noah land surface model (LSM) and the snowpack treatment. Different physics packages for WRF are evaluated with December 2002 simulations that show variable forecast skill when verified with the automatic weather station observations. The WRF simulation with the combination of the modified Noah LSM, the Mellor–Yamada–Janjić boundary layer parameterization, and the WRF single-moment microphysics produced results that reach or exceed the success standards of a Polar MM5 simulation for December 2002. For summer simulations of June 2001, WRF simulates an improved surface energy balance, and shows forecast skill nearly equal to that of Polar MM5.
The Importance of the Boundary Layer Parameterization in the Prediction of Low-Level Convergence Lines
Authors: Thomsen Gerald L. , Smith Roger K. 
Published: July 2008

AbstractThe importance of the boundary layer parameterization in the numerical prediction of low-level convergence lines over northeastern Australia is investigated. High-resolution simulations of convergence lines observed in one event during the 2002 Gulf Lines Experiment are carried out using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). Calculations using five different parameterizations are compared with observations to determine the optimum scheme for capturing these lines. The schemes that give the best agreement with the observations are the three that include a representation of countergradient fluxes and a surface layer scheme based on Monin–Obukhov theory. One of these, the Medium-Range Forecast scheme, is slightly better than the other two, based on its ability to predict the surface pressure distribution. The findings are important for the design of mesoscale forecasting systems for the arid regions of Australia and elsewhere.
Evaluating Rank Histograms Using Decompositions of the Chi-Square Test Statistic
Authors: Jolliffe Ian T. , Primo Cristina 
Published: July 2008

Abstract
Rank histograms are often plotted to evaluate the forecasts produced by an ensemble forecasting system—an ideal rank histogram is “flat” or uniform. It has been noted previously that the obvious test of “flatness,” the well-known χ2 goodness-of-fit test, spreads its power thinly and hence is not good at detecting specific alternatives to flatness, such as bias or over- or underdispersion. Members of the Cramér–von Mises family of tests do much better in this respect. An alternative to using the Cramér–von Mises family is to decompose the χ2 test statistic into components that correspond to specific alternatives. This approach is described in the present paper. It is arguably easier to use and more flexible than the Cramér–von Mises family of tests, and does at least as well as it in detecting alternatives corresponding to bias and over- or underdispersion.
A Perfect Prognosis Scheme for Forecasting Warm-Season Lightning over Florida
Authors: Shafer Phillip E. , Fuelberg Henry E. 
Published: July 2008

Abstract
This study develops and evaluates a statistical scheme for forecasting warm-season lightning over Florida. Four warm seasons of analysis data from the Rapid Update Cycle (RUC) and lightning data from the National Lightning Detection Network are used in a perfect prognosis technique to develop a high-resolution, gridded forecast guidance product for warm-season cloud-to-ground (CG) lightning over Florida. The most important RUC-derived parameters are used to develop equations producing 3-hourly spatial probability forecasts for one or more CG flashes, as well as the probability of exceeding various flash count percentile thresholds. Binary logistic regression is used to develop the equations for one or more flashes, while a negative binomial model is used to predict the amount of lightning, conditional on one or more flashes occurring. The scheme is applied to output from three mesoscale models during an independent test period (the 2006 warm season). The evaluation is performed using output from the National Centers for Environmental Prediction (NCEP) 13-km RUC (RUC13), the NCEP 12-km North American Mesoscale Model, and local high-resolution runs of the Weather Research and Forecasting (WRF) Model for a domain over south Florida. Forecasts from all three mesoscale models generally show positive skill through the 2100–2359 UTC period with respect to a model containing only climatology and persistence (L-CLIPER) and persistence alone. A forecast example using the high-resolution WRF Model is shown for 16–17 August 2006. Although the exact timing and placement of forecast lightning are not perfect, there generally is good agreement between the forecasts and their verification, with most of the observed lightning occurring within the higher forecast probability contours.
The Integral Role of a Diabatic Rossby Vortex in a Heavy Snowfall Event
Authors: Moore Richard W. , Montgomery Michael T. , Davies Huw C. 
Published: July 2008

Abstract
On 24–25 February 2005, a significant East Coast cyclone deposited from 4 to nearly 12 in. (∼10–30 cm) of snow on parts of the northeastern United States. The heaviest snowfall and most rapid deepening of the cyclone coincided with the favorable positioning of an upper-level, short-wave trough immediately upstream of a preexisting surface cyclone. The surface cyclone in question formed approximately 15 h before the heaviest snowfall along a coastal front in a region of frontogenesis and heavy precipitation. The incipient surface cyclone subsequently intensified as it moved to the northeast, consistently generating the strongest convection to the east-northeast of the low-level circulation center. The use of potential vorticity (PV) inversion techniques and a suite of mesoscale model simulations illustrates that the early intensification of the incipient surface cyclone was primarily driven by diabatic effects and was not critically dependent on the upper-level wave. These facts, taken in conjunction with the observed structure, energetics, and Lagrangian evolution of the incipient surface disturbance, identify it as a diabatic Rossby vortex (DRV). The antecedent surface vorticity spinup associated with the DRV phase of development is found to be integral to the subsequent rapid growth. The qualitative similarity with a number of observed cases of explosive cyclogenesis leaves open the possibility that a DRV-like feature comprises the preexisting positive low-level PV anomaly in a number of cyclogenetic events that exhibit a two-stage evolution.
Mesoscale Features Associated with Tropical Cyclone Formations in the Western North Pacific
Authors: Lee Cheng-Shang , Cheung Kevin K. W. , Hui Jenny S. N. , Elsberry Russell L. 
Published: July 2008

Abstract
The mesoscale features of 124 tropical cyclone formations in the western North Pacific Ocean during 1999–2004 are investigated through large-scale analyses, satellite infrared brightness temperature (TB), and Quick Scatterometer (QuikSCAT) oceanic wind data. Based on low-level wind flow and surge direction, the formation cases are classified into six synoptic patterns: easterly wave (EW), northeasterly flow (NE), coexistence of northeasterly and southwesterly flow (NE–SW), southwesterly flow (SW), monsoon confluence (MC), and monsoon shear (MS). Then the general convection characteristics and mesoscale convective system (MCS) activities associated with these formation cases are studied under this classification scheme. Convection processes in the EW cases are distinguished from the monsoon-related formations in that the convection is less deep and closer to the formation center. Five characteristic temporal evolutions of the deep convection are identified: (i) single convection event, (ii) two convection events, (iii) three convection events, (iv) gradual decrease in TB, and (v) fluctuating TB, or a slight increase in TB before formation. Although no dominant temporal evolution differentiates cases in the six synoptic patterns, evolutions ii and iii seem to be the common routes taken by the monsoon-related formations. The overall percentage of cases with MCS activity at multiple times is 63%, and in 35% of cases more than one MCS coexisted. Most of the MC and MS cases develop multiple MCSs that lead to several episodes of deep convection. These two patterns have the highest percentage of coexisting MCSs such that potential interaction between these systems may play a role in the formation process. The MCSs in the monsoon-related formations are distributed around the center, except in the NE–SW cases in which clustering of MCSs is found about 100–200 km east of the center during the 12 h before formation. On average only one MCS occurs during an EW formation, whereas the mean value is around two for the other monsoon-related patterns. Both the mean lifetime and time of first appearance of MCS in EW are much shorter than those developed in other synoptic patterns, which indicates that the overall formation evolution in the EW case is faster. Moreover, this MCS is most likely to be found within 100 km east of the center 12 h before formation. The implications of these results to internal mechanisms of tropical cyclone formation are discussed in light of other recent mesoscale studies.
Convective Storm Initiation in a Moist Tropical Environment
Authors: Lima Maria Andrea , Wilson James W. 
Published: July 2008

Abstract
Radar and satellite data from the Tropical Rainfall Measuring Mission–Large-Scale Biosphere–Atmosphere (TRMM–LBA) project have been examined to determine causes for convective storm initiation in the southwest Amazon region. The locations and times of storm initiation were based on the National Center for Atmospheric Research (NCAR) S-band dual-polarization Doppler radar (S-Pol). Both the radar and the Geostationary Operational Environmental Satellite-8 (GOES-8) visible data were used to identify cold pools produced by convective precipitation. These data along with high-resolution topographic data were used to determine possible convective storm triggering mechanisms. The terrain elevation varied from 100 to 600 m. Tropical forests cover the area with numerous clear-cut areas used for cattle grazing and farming. This paper presents the results from 5 February 1999. A total of 315 storms were initiated within 130 km of the S-Pol radar. This day was classified as a weak monsoon regime where convection developed in response to the diurnal cycle of solar heating. Scattered shallow cumulus during the morning developed into deep convection by early afternoon. Storm initiation began about 1100 LST and peaked around 1500–1600 LST. The causes of storm initiation were classified into four categories. The most common initiation mechanism was caused by forced lifting by a gust front (GF; 36%). Forcing by terrain (&gt;300 m) without any other triggering mechanism accounted for 21% of the initiations and colliding GFs accounted for 16%. For the remaining 27% a triggering mechanism was not identified. Examination of all days during TRMM–LBA showed that this one detailed study day was representative of many days. A conceptual model of storm initiation and evolution is presented. The results of this study should have implications for other locations when synoptic-scale forcing mechanisms are at a minimum. These results should also have implications for very short-period forecasting techniques in any location where terrain, GFs, and colliding boundaries influence storm evolution.
Assimilation of Simulated Polarimetric Radar Data for a Convective Storm Using the Ensemble Kalman Filter. Part II: Impact of Polarimetric Data on Storm Analysis
Authors: Jung Youngsun , Xue Ming , Zhang Guifu , Straka Jerry M. 
Published: July 2008

Abstract
A data assimilation system based on the ensemble square-root Kalman filter (EnSRF) is extended to include the additional capability of assimilating polarimetric radar variables. It is used to assess the impact of assimilating additional polarimetric observations on convective storm analysis in the Observing System Simulation Experiment (OSSE) framework. The polarimetric variables considered include differential reflectivity ZDR, reflectivity difference Zdp, and specific differential phase KDP. To simulate the observational data more realistically, a new error model is introduced for characterizing the errors of the nonpolarimetric and polarimetric radar variables. The error model includes both correlated and uncorrelated error components for reflectivities at horizontal and vertical polarizations (ZH and ZV, respectively). It is shown that the storm analysis is improved when polarimetric variables are assimilated in addition to ZH or in addition to both ZH and radial velocity Vr. Positive impact is largest when ZDR, Zdp, and KDP are assimilated all together. Improvement is generally larger in vertical velocity, water vapor, and rainwater mixing ratios. The rainwater field benefits the most while the impacts on horizontal wind components and snow mixing ratio are smaller. Improvement is found at all model levels even though the polarimetric data, after the application of thresholds, are mostly limited to the lower levels. Among ZDR, Zdp, and KDP, ZDR is found to produce the largest positive impact on the analysis. It is suggested that ZDR provides more independent information than the other variables. The impact of polarimetric data is also expected to be larger when they are used to retrieve drop size distribution parameters. The polarimetric radar data thresholding prior to assimilation is found to be necessary to minimize the impact of noise. This study is believed to be the first to directly assimilate (simulated) polarimetric data into a numerical model.
Assessing the Skill of an All-Season Statistical Forecast Model for the Madden–Julian Oscillation
Authors: Jiang Xianan , Waliser Duane E. , Wheeler Matthew C. , Jones Charles , Lee Myong-In , Schubert Siegfried D. 
Published: July 2008

Abstract
Motivated by an attempt to augment dynamical models in predicting the Madden–Julian oscillation (MJO), and to provide a realistic benchmark to those models, the predictive skill of a multivariate lag-regression statistical model has been comprehensively explored in the present study. The predictors of the benchmark model are the projection time series of the leading pair of EOFs of the combined fields of equatorially averaged outgoing longwave radiation (OLR) and zonal winds at 850 and 200 hPa, derived using the approach of Wheeler and Hendon. These multivariate EOFs serve as an effective filter for the MJO without the need for bandpass filtering, making the statistical forecast scheme feasible for the real-time use. Another advantage of this empirical approach lies in the consideration of the seasonal dependence of the regression parameters, making it applicable for forecasts all year-round. The forecast model exhibits useful extended-range skill for a real-time MJO forecast. Predictions with a correlation skill of greater than 0.3 (0.5) between predicted and observed unfiltered (EOF filtered) fields still can be detected over some regions at a lead time of 15 days, especially for boreal winter forecasts. This predictive skill is increased significantly when there are strong MJO signals at the initial forecast time. The analysis also shows that predictive skill for the upper-tropospheric winds is relatively higher than for the low-level winds and convection signals. Finally, the capability of this empirical model in predicting the MJO is further demonstrated by a case study of a real-time “hindcast” during the 2003/04 winter. Predictive skill demonstrated in this study provides an estimate of the predictability of the MJO and a benchmark for the dynamical extended-range models.
An Indirect Effect of Ice Nuclei on Atmospheric Radiation
Authors: Zeng Xiping , Tao Wei-Kuo , Zhang Minghua , Hou Arthur Y. , Xie Shaocheng , Lang Stephen , Li Xiaowen , Starr David O’C. , Li Xiaofan , Simpson Joanne 
Published: July 2008

AbstractA three-dimensional cloud-resolving model (CRM) with observed large-scale forcing is used to study how ice nuclei (IN) affect the net radiative flux at the top of the atmosphere (TOA). In all the numerical experiments carried out, the cloud ice content in the upper troposphere increases with IN number concentration via the Bergeron process. As a result, the upward solar flux at the TOA increases whereas the infrared one decreases. Because of the opposite response of the two fluxes to IN concentration, the sensitivity of the net radiative flux at the TOA to IN concentration varies from one case to another.Six tropical and three midlatitudinal field campaigns provide data to model the effect of IN on radiation in different latitudes. Classifying the CRM simulations into tropical and midlatitudinal and then comparing the two types reveals that the indirect effect of IN on radiation is greater in the middle latitudes than in the tropics. Furthermore, comparisons between model results and observations suggest that observational IN data are necessary to evaluate long-term CRM simulations.
An Energetics Study of Wintertime Northern Hemisphere Storm Tracks under 4 × CO2 Conditions in Two Ocean–Atmosphere Coupled Models
Authors: Laîné Alexandre , Kageyama Masa , Salas-Mélia David , Ramstein Gilles , Planton Serge , Denvil Sébastien , Tyteca Sophie 
Published: July 2008

Abstract
Different possible behaviors of winter Northern Hemisphere storm tracks under 4 × CO2 forcing are considered by analyzing the response of two of the ocean–atmosphere coupled models that were run for the fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4), namely the Institut Pierre Simon Laplace’s global coupled model (IPSL-CM4) and the Centre National de Recherches Meteorologiques’s coupled ocean–atmosphere model (CNRM-CM3). It is interesting to compare these models due to their very different responses, especially concerning the North Atlantic storm track.
A local energetics study of the synoptic variability in both models is performed, derived from the eddy energy equations, including diabatic terms. The ability of both models to simulate the present-day eddy energetics is considered, indicating no major discrepancies.
Both models indicate that the primary cause for synoptic activity changes at the western end of the storm tracks is related to the baroclinic conversion process, due to mean temperature gradient changes in some localized regions of the western oceanic basins, but also resulting from changes in the eddy efficiency to convert energy from the mean flow. Farther downstream, latent heat release during the developing and mature stages of eddies becomes an important eddy energy source especially in terms of changes between 4 × CO2 and preindustrial conditions. This diabatic process amplifies the upstream synoptic (hence usually baroclinic) changes, with more and/or stronger storms implying more latent heat being released (and the converse being true for weaker synoptic activity). This amplification is asymmetrical for the models considered under the simulated 4 × CO2 conditions, due to a greater amount of water vapor contained in warmer air and hence the potential for more condensation for a given synoptic activity. The magnitude of the reduced latent heating is attenuated, whereas increased latent heating is strengthened. Ageostrophic geopotential fluxes are also important in relocating eddy kinetic energy, especially in the vertical.