bluuebunny/crossref_metadata_2025_split huggingface dataset:
Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation
Authors: Gneiting Tilmann , Raftery Adrian E. , Westveld Anton H. , Goldman Tom 
Published: June 2005

AbstractEnsemble prediction systems typically show positive spread-error correlation, but they are subject to forecast bias and dispersion errors, and are therefore uncalibrated. This work proposes the use of ensemble model output statistics (EMOS), an easy-to-implement postprocessing technique that addresses both forecast bias and underdispersion and takes into account the spread-skill relationship. The technique is based on multiple linear regression and is akin to the superensemble approach that has traditionally been used for deterministic-style forecasts. The EMOS technique yields probabilistic forecasts that take the form of Gaussian predictive probability density functions (PDFs) for continuous weather variables and can be applied to gridded model output. The EMOS predictive mean is a bias-corrected weighted average of the ensemble member forecasts, with coefficients that can be interpreted in terms of the relative contributions of the member models to the ensemble, and provides a highly competitive deterministic-style forecast. The EMOS predictive variance is a linear function of the ensemble variance. For fitting the EMOS coefficients, the method of minimum continuous ranked probability score (CRPS) estimation is introduced. This technique finds the coefficient values that optimize the CRPS for the training data. The EMOS technique was applied to 48-h forecasts of sea level pressure and surface temperature over the North American Pacific Northwest in spring 2000, using the University of Washington mesoscale ensemble. When compared to the bias-corrected ensemble, deterministic-style EMOS forecasts of sea level pressure had root-mean-square error 9% less and mean absolute error 7% less. The EMOS predictive PDFs were sharp, and much better calibrated than the raw ensemble or the bias-corrected ensemble.
A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction Systems
Authors: Buizza Roberto , Houtekamer P. L. , Pellerin Gerald , Toth Zoltan , Zhu Yuejian , Wei Mozheng 
Published: June 2005

Abstract
The present paper summarizes the methodologies used at the European Centre for Medium-Range Weather Forecasts (ECMWF), the Meteorological Service of Canada (MSC), and the National Centers for Environmental Prediction (NCEP) to simulate the effect of initial and model uncertainties in ensemble forecasting. The characteristics of the three systems are compared for a 3-month period between May and July 2002. The main conclusions of the study are the following:the performance of ensemble prediction systems strongly depends on the quality of the data assimilation system used to create the unperturbed (best) initial condition and the numerical model used to generate the forecasts;a successful ensemble prediction system should simulate the effect of both initial and model-related uncertainties on forecast errors; andfor all three global systems, the spread of ensemble forecasts is insufficient to systematically capture reality, suggesting that none of them is able to simulate all sources of forecast uncertainty.The relative strengths and weaknesses of the three systems identified in this study can offer guidelines for the future development of ensemble forecasting techniques.
Singular-Vector-Based Covariance Propagation in a Quasigeostrophic Assimilation System
Authors: Beck Alexander , Ehrendorfer Martin 
Published: June 2005

Abstract
Variational data assimilation systems require the specification of the covariances of background and observation errors. Although the specification of the background-error covariances has been the subject of intense research, current operational data assimilation systems still rely on essentially static and thus flow-independent background-error covariances. At least theoretically, it is possible to use flow-dependent background-error covariances in four-dimensional variational data assimilation (4DVAR) through exploiting the connection between variational data assimilation and estimation theory.
This paper reports on investigations concerning the impact of flow-dependent background-error covariances in an idealized 4DVAR system that, based on quasigeostrophic dynamics, assimilates artificial observations. The main emphasis is placed on quantifying the improvement in analysis quality that is achievable in 4DVAR through the use of flow-dependent background-error covariances. Flow dependence is achieved through dynamical error-covariance evolution based on singular vectors in a reduced-rank approach, referred to as reduced-rank Kalman filter (RRKF). The RRKF yields partly dynamic background-error covariances through blending static and dynamic information, where the dynamic information is obtained from error evolution in a subspace of dimension k (defined here through the singular vectors) that may be small compared to the dimension of the model’s phase space n, which is equal to 1449 in the system investigated here.
The results show that the use of flow-dependent background-error covariances based on the RRKF leads to improved analyses compared to a system using static background-error statistics. That latter system uses static background-error covariances that are carefully tuned given the model dynamics and the observational information available. It is also shown that the performance of the RRKF approaches the performance of the extended Kalman filter, as k approaches n. Results therefore support the hypothesis that significant analysis improvement is possible through the use of flow-dependent background-error covariances given that a sufficiently large number (here on the order of n/10) of singular vectors is used.
Contributions from California Coastal-Zone Surface Fluxes to Heavy Coastal Precipitation: A CALJET Case Study during the Strong El Niño of 1998
Authors: Persson P. Ola G. , Neiman P. J. , Walter B. , Bao J-W. , Ralph F. M. 
Published: June 2005

Abstract
Analysis of the case of 3 February 1998, using an extensive observational system in the California Bight during an El Niño winter, has revealed that surface sensible and latent heat fluxes within 150 km of the shore contributed substantially to the destabilization of air that subsequently produced strong convection and flooding along the coast. Aircraft, dropsonde, and satellite observations gathered offshore documented the sea surface temperatures (SSTs), surface fluxes, stratification, and frontal structures. These were used to extrapolate the effects of the fluxes on the warm-sector, boundary layer air ahead of a secondary cold front as this air moved toward the coast. The extrapolated structure was then validated in detail with nearshore aircraft, wind profiler, sounding, and buoy observations of the frontal convection along the coast, and the trajectory transformations were confirmed with a model simulation. The results show that the surface fluxes increased CAPE by about 26% such that the nearshore boundary layer values of 491 J kg−1 were near the upper end of those observed for cool-season California thunderstorms.
The increased CAPE due to upward sensible and latent heat fluxes was a result of the anomalously warm coastal SSTs (+1°–3°C) typical of strong El Niño events. Applications of the extrapolation method using a surface flux parameterization scheme and different SSTs suggested that convective destabilization due to nearshore surface fluxes may only occur during El Niño years when positive coastal SST anomalies are present. The fluxes may have no effect or a stabilizing effect during non–El Niño years, characterized by zero or negative coastal SST anomalies. In short, during strong El Niños, it appears that the associated coastal SST anomalies serve to further intensify the already anomalously strong storms in southern California, thus contributing to the increased flooding. This modulating effect by El Niño–Southern Oscillation (ENSO) of a mesoscale process has not been considered before in attempts at assessing the impacts of ENSO on U.S. west coast precipitation.
Using Green's Functions to Calibrate an Ocean General Circulation Model
Authors: Menemenlis Dimitris , Fukumori Ichiro , Lee Tong 
Published: June 2005

Abstract
Green's functions provide a simple yet effective method to test and to calibrate general circulation model (GCM) parameterizations, to study and to quantify model and data errors, to correct model biases and trends, and to blend estimates from different solutions and data products. The method is applied to an ocean GCM, resulting in substantial improvements of the solution relative to observations when compared to prior estimates: overall model bias and drift are reduced and there is a 10%–30% increase in explained variance. Within the context of this optimization, the following new estimates for commonly used ocean GCM parameters are obtained. Background vertical diffusivity is (15.1 ± 0.1) × 10−6 m2 s−2. Background vertical viscosity is (18 ± 3) × 10−6 m2 s−2. The critical bulk Richardson number, which sets boundary layer depth, is Ric = 0.354 ± 0.004. The threshold gradient Richardson number for shear instability vertical mixing is Ri0 = 0.699 ± 0.008. The estimated isopycnal diffusivity coefficient ranges from 550 to 1350 m2 s−2, with the largest values occurring at depth in regions of increased mesoscale eddy activity. Surprisingly, the estimated isopycnal diffusivity exhibits a 5%–35% decrease near the surface. Improved estimates of initial and boundary conditions are also obtained. The above estimates are the backbone of a quasi-operational, global-ocean circulation analysis system.
The July 2003 Dakota Hailswaths: Creation, Characteristics, and Possible Impacts
Authors: Parker Matthew D. , Ratcliffe Ian C. , Henebry Geoffrey M. 
Published: June 2005

Abstract
The authors investigate the meteorology associated with two elongated swaths of crop damage produced by severe hailstorms that crossed North Dakota and South Dakota on 4 July and 20 July 2003. These hailswaths, which were observed in a Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) image time series, each persisted for more than a month and were associated with local temperature increases, presumably owing to the enhanced Bowen ratio over dry, crop-free ground. This paper documents the creation and evolution of the convective storms that produced the hailswaths, and then presents evidence that devegetated hailswaths may impact future convective weather. Idealized numerical simulations including hailswath-like surface anomalies, as well as analogies to the extant literature, suggest that hailswaths may play a part in initiating new convective clouds, especially when the low-level winds are parallel to their long axes. Analyses of conventional operational observations also show that the 4 July hailswath may have played a part in the initiation and intensification of a convective storm on 17 July and in the temporarily deviant motion of a convective storm that crossed it on 20 July. Because devegetated hailswaths are common to the central and northern plains during the summer months, and because they have heretofore received little study, a deeper understanding of hailswaths’ impacts upon moist convection may lead to improved short-term weather prediction.
Comparison of Narrow Bipolar Events with Ordinary Lightning as Proxies for Severe Convection
Authors: Jacobson Abram R. , Heavner Mathew J. 
Published: June 2005

Abstract
Narrow bipolar events (NBEs) are a recently studied intracloud electrical-discharge process. It is speculated that an NBE is instigated by the extensive atmospheric shower of an energetic cosmic ray. NBEs cause significant relaxation of the charge separation within the electrified cloud in a short time, on the order of 10 μs. The current flow causes radiation of a distinctive “bipolar” low-frequency/very low frequency signal that can be recorded at locations on earth up to thousands of kilometers from the source. NBEs are preceded/accompanied by the most powerful very high frequency radio emissions seen in any kind of lightning. These intense pulsed radio emissions have been routinely detected with satellite-borne radio receivers in space. Owing to their easy detection and recognition, NBEs might be a useful remote sensing proxy for space-based global, near–real time remote sensing. However, in order for that potential to be realized, NBEs must be shown to be associated, as is ordinary lightning, with severe tropospheric convection, rather than to be just a curiosity of cosmic-ray–atmosphere interactions. This question is addressed with a detailed comparison of NBEs and ordinary lightning using a ground-based lightning-transient research facility that records signals from both ordinary lightning and NBEs, the Los Alamos Sferic-waveform Array (LASA), based in Florida. First, the data from LASA are internally compared to examine the relationship of NBEs and ordinary lightning in both position and time. Second, the relationship of both NBEs and ordinary lightning to simultaneous infrared cloud imagery is examined [from the Geostationary Operational Environmental Satellite-East (GOES-East)] in order to infer the relative affinities of NBEs and ordinary lightning for cloud signatures that are consistent with severe convection.
Western Pacific SST Prediction with an Intermediate El Niño Prediction Model
Authors: Kug Jong-Seong , Kang In-Sik , Jhun Jong-Ghap 
Published: June 2005

Abstract
To improve forecasting skills in the western Pacific sea surface temperature (SST), the authors utilized and modified an intermediate El Niño prediction model. The original model does not have the major SST thermodynamics for western Pacific SST variability, so it cannot simulate interannual variation in the western Pacific correctly. Therefore, the authors have introduced some modifications, such as heat flux and vertical mixing, into the dynamical model in order to capture SST thermodynamics more realistically. The modified model has better forecast skill than the original one, not only for the western Pacific but also for the eastern-central Pacific. The model has predictive skill up to 6-months lead time as judged by a correlation exceeding 0.5.
New Approach to Calculation of Atmospheric Model Physics: Accurate and Fast Neural Network Emulation of Longwave Radiation in a Climate Model
Authors: Krasnopolsky Vladimir M. , Fox-Rabinovitz Michael S. , Chalikov Dmitry V. 
Published: June 2005

Abstract
A new approach based on a synergetic combination of statistical/machine learning and deterministic modeling within atmospheric models is presented. The approach uses neural networks as a statistical or machine learning technique for an accurate and fast emulation or statistical approximation of model physics parameterizations. It is applied to development of an accurate and fast approximation of an atmospheric longwave radiation parameterization for the NCAR Community Atmospheric Model, which is the most time consuming component of model physics. The developed neural network emulation is two orders of magnitude, 50–80 times, faster than the original parameterization. A comparison of the parallel 10-yr climate simulations performed with the original parameterization and its neural network emulations confirmed that these simulations produce almost identical results. The obtained results show the conceptual and practical possibility of an efficient synergetic combination of deterministic and statistical learning components within an atmospheric climate or forecast model. A developmental framework and practical validation criteria for neural network emulations of model physics components are outlined.
Anatomical Reconstruction of the Lateral Ligaments of the Ankle with a Gracilis Autograft
Authors: Takao Masato , Oae Kazunori , Uchio Yuji , Ochi Mitsuo , Yamamoto Haruyasu 
Published: June 2005

Background Few anatomical and minor invasive procedures have been reported for surgical reconstruction of the lateral ligaments to treat lateral instability of the ankle. Furthermore, there are no standards according to which ligaments should be reconstructed. Hypothesis A new technique for anatomically reconstructing the lateral ligaments of the ankle using an interference fit anchoring system and determining which ligaments need to be reconstructed according to the results of standard stress radiography of the talocrural and subtalar joints will be effective for treating lateral instability of the ankle. Study Design Case series; level of evidence, 4. Methods Twenty-one patients with lateral instability of the ankle underwent surgery using the proposed interference fit anchoring system. Standard stress radiographs of the subtalar joint were performed, and if the talocalcaneal angle was less than 10°, only the anterior talofibular ligament was reconstructed; if there was a 10° or greater opening of the talocalcaneal angle, both the anterior talofibular ligament and the calcaneofibular ligament were reconstructed. Results In the 17 patients who received only the anterior talofibular ligament reconstruction, the mean talar tilt angle on standard stress radiography of the talocrural joint was 14.5°± 1.7° before surgery and 2.6°± 0.8° 2 years after surgery (P <. 0001). For the 4 patients who had both the anterior talofibular ligament and calcaneofibular ligament reconstructed, the mean talar tilt angle was 16.5°± 1.5° before surgery and 3.0°± 0.5° 2 years after surgery (P =. 0015). The overall mean talocalcaneal angle on standard stress radiography of the subtalar joint was 11.3°± 1.4° before surgery and 3.5°± 0.8° 2 years after surgery (P =. 0060). Conclusion The proposed system has several advantages, including anatomical reconstruction with normal stability and range of motion restored, the need for only a small incision during the reconstruction, and sufficient strength at the tendon graft-bone tunnel junction, in comparison with the tension strength of the lateral ligaments of the ankle.
Stability of naujakasite in hyperagpaitic melts, and the petrology of naujakasite lujavrite in the llímaussaq alkaline complex, South Greenland
Authors: Andersen T. , Sørensen H. 
Published: June 2005

AbstractNaujakasite (Na6(Fe,Mn)Al4Si8O26) is a characteristic, rock-forming mineral of hyperagpaitic naujakasite lujavrite (arfvedsonite + naujakasite + steenstrupine + albite ± relict nepheline ± microcline ± ussingite) from the Ilímaussaq complex, South Greenland, and is only known from this complex. The qualitative stability relationships of naujakasite-bearing, low-variance liquidus mineral assemblages at near-solidus conditions in lujavritic magma can be modelled within the six-component system Si-Al-Fe-Na-O-H. The modelling suggests that an uncommon combination of elevated water activity and low oxygen fugacity is needed to stabilize arfvedsonite + naujakasite mineral assemblages in highly sodic liquids. These conditions are incompatible with the stable coexistence of aegirine and arfvedsonite. They are met in the arfvedsonite-bearing lujavrites of Ilímaussaq, but apparently not in rocks of similar composition in the Khibina and Lovozero complexes, Kola Peninsula, where aegirine- or aegirine-arfvedsonite-bearing mineral assemblages are characteristic. Liquid lines of descent leading to crystallization of naujakasite have to pass through the albite+nepheline+arfvedsonite liquidus field in the Si-Al-Fe-Na-O-H system, reaching this field at the high-Na side of the albite-nepheline-arfvedsonite plane.
A new mineral, zincolibethenite, CuZnPO4OH, a stoichiometric species of specific site occupancy
Authors: Braithwaite R. S. W. , Pritchard R. G. , Paar W. H. , Pattrick R. A. D. 
Published: June 2005

AbstractTiny green crystals from Kabwe, Zambia, associated with hopeite and tarbuttite (and probably first recorded in 1908 but never adequately characterized because of their scarcity) have been studied by X-ray diffraction, microchemical and electron probe microanalysis, infrared spectroscopy, and synthesis experiments. They are shown to be orthorhombic, stoichiometric CuZnPO4OH, of species rank, forming the end-member of a solid-solution series to libethenite, Cu2PO4OH, and are named zincolibethenite. The libethenite structure is unwilling to accommodate any more Zn substituting for Cu at atmospheric pressure, syntheses using Zn-rich solutions precipitating a mixture of zincolibethenite with hopeite, Zn3(PO4)2.4H2O. Single-crystal X-ray data confirm that the Cu(II) occupies the Jahn-Teller distorted 6-coordinate cation site in the libethenite lattice, and the Zn(II) occupies the 5-coordinate site. The space group of zincolibethenite is Pnnm, the same as that of libethenite, with unit-cell parameters a = 8.326, b = 8.260, c = 5.877 Å , V = 404.5 Å 3, Z = 4, calculated density = 3.972 g/cm3 (libethenite has a = 8.076, b = 8.407, c = 5.898 Å , V = 400.44 Å 3, Z = 4, calculated density = 3.965 g/cm3). Zincolibethenite is biaxial negative, with 2Vα(calc.) of 49°, r<v, and α = 1.660, β = 1.705, and γ = 1.715 The mineral is named for its relationship to libethenite.
Compositional and textural variation in detrital chrome-spinels from the Murray Basin, southeastern Australia
Authors: Pownceby M. 
Published: June 2005

AbstractDetrital chrome-spinels are contaminant grains within heavy-mineral concentrates found in the Murray Basin of southeastern Australia. The presence of even minor levels of chromia in the predominantly ilmenite-rich concentrates downgrades their market value as potential feedstocks for the production of titania pigment.Compositions from a database of close to 5000 chrome-spinel analyses show a broad range in chemistry. The major element components and their ranges (wt.%) are Cr: 3.10–52.06, Al: 0.46–32.50, Fe: 3.50–44.48 and Mg: 0.03–15.79. Minor components include; Ti: 0.01–6.41, Zn: 0.00–23.00 and Mn: 0.00–5.82. The broad variation in composition suggests multiple source areas for the chrome-spinels although detailed textural examination indicates that variation has also been introduced through pre- and post-deposition alteration processes.The Murray Basin chrome-spinel database has the potential to be used in interpreting and predicting the effects of various processing conditions used to separate the chrome-spinels from the ilmenite.
Thermal expansion of troilite and pyrrhotite determined byin situcooling (873 to 373 K) neutron powder diffraction measurements
Authors: Tenailleau C. , Etschmann B. , Wang H. , Pring A. , Grguric B. A. , Studer A. 
Published: June 2005

AbstractThe thermal expansion coefficients for natural troilite, FeS, Ni-rich pyrrhotite, Fe0.84Ni0.11S, and Ni-poor pyrrhotite, Fe0.87Ni0.02S, were measured during cooling by in situ neutron powder diffraction over the temperature range 873–373 K. Between 873 and 573 K, the mean thermal expansion coefficients for the three compositions are 7.4(3)×10−5{FeS}, 8.0(4)×10−5{Fe0.84Ni0.11S} and 8.5(4)×10−5K−1{Fe0.87Ni0.02S}. Below 573 down to 373 K, the first two increase considerably to 14.1(7)×10−5{FeS} and 9.3(5)×10−5{Fe0.84Ni0.11S} while the latter sample shows no significant variation, 8.4(5)×10−5K−1. Below 573 K, the thermal expansion is highly anisotropic, with Δa/100 K−1ranging from 0.89(9)% {FeS} to 0.48(12)% {Fe0.87Ni0.02S} while Δc/100 K−1ranges from −0.39(11)% {FeS} to −0.13(2)% {Fe0.87Ni0.02S}.Upon cooling through 573 K, troilite and pyrrhotite undergo a transition where the FeS6octahedra distort and in the case of pyrrhotite, cation-vacancy clustering occurs. The thermal expansion coefficients are bigger for low cation-vacancy concentrations and decrease as the pyrrhotites become less stoichiometric. This indicates that the thermal expansion in these minerals is damped by vacancy ordering or clustering. The thermal expansion coefficients for troilite and pyrrhotite are amongst the largest reported for sulphide minerals and their role in the formation of ore textures is discussed briefly.