bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cycling the Representer Algorithm for Variational Data Assimilation with the Lorenz Attractor
Authors: Ngodock H. E. , Smith S. R. , Jacobs G. A. 
Published: February 2007

Abstract
Realistic dynamic systems are often strongly nonlinear, particularly those for the ocean and atmosphere. Applying variational data assimilation to these systems requires a tangent linearization of the nonlinear dynamics about a background state for the cost function minimization. The tangent linearization may be accurate for limited time scales. Here it is proposed that linearized assimilation systems may be accurate if the assimilation time period is less than the tangent linear accuracy time limit. In this paper, the cycling representer method is used to test this assumption with the Lorenz attractor. The outer loops usually required to accommodate the linear assimilation for a nonlinear problem may be dropped beyond the early cycles once the solution (and forecast used as the background in the tangent linearization) is sufficiently accurate. The combination of cycling the representer method and limiting the number of outer loops significantly lowers the cost of the overall assimilation problem. In addition, this study shows that weak constraint assimilation corrects tangent linear model inaccuracies and allows extension of the limited assimilation period. Hence, the weak constraint outperforms the strong constraint method. Assimilated solution accuracy at the first cycle end is computed as a function of the initial condition error, model parameter perturbation magnitude, and outer loops. Results indicate that at least five outer loops are needed to achieve solution accuracy in the first cycle for the selected error range. In addition, this study clearly shows that one outer loop in the first cycle does not preclude accuracy convergence in future cycles.
The Impact of Assimilating SSM/I and QuikSCAT Satellite Winds on Hurricane Isidore Simulations
Authors: Chen Shu-Hua 
Published: February 2007

AbstractThree observational datasets of Hurricane Isidore (in 2002) were analyzed and compared: the Special Sensor Microwave Imager (SSM/I), the Quick Scatterometer (QuikSCAT) winds, and dropsonde winds. SSM/I and QuikSCAT winds were on average about 1.9 and 0.3 m s−1 stronger, respectively, than dropsonde winds. With more than 20 000 points of data, SSM/I wind speed was about 2.2 m s−1 stronger than QuikSCAT. Comparison of the wind direction observed by QuikSCAT with those from the dropsondes showed that the quality of QuikSCAT data is good. The effect of assimilating SSM/I wind speeds and/or QuikSCAT wind vectors for the analysis of Hurricane Isidore was assessed using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and its three-dimensional variational data assimilation system. For the Hurricane Isidore case study, it was found that the assimilation of either satellite winds strengthened the cyclonic circulation in the analysis. However, the increment of the QuikSCAT wind analysis is more complicated than that from the SSM/I analysis due to the correction of the storm location, a positive result from the assimilation of wind vectors. The increase in low-level wind speeds enhanced the air–sea interaction processes and improved the simulated intensity for Isidore. In addition, the storm structure was better simulated. Assimilation of QuikSCAT wind vectors clearly improved simulation of the storm track, in particular during the later period of the simulation, but lack of information about the wind direction from SSM/I data prevented it from having much of an effect. Assessing the assimilation of QuikSCAT wind speed versus wind vector data confirmed this hypothesis. The track improvement partially resulted from the relocation of the storm’s initial position after assimilation of the wind vectors. For this case study, it was found that the assimilation of SSM/I or QuikSCAT data had the greatest impact on the Hurricane Isidore simulation during the first 2 days.
The Impact of Multisatellite Data on the Initialization and Simulation of Hurricane Lili’s (2002) Rapid Weakening Phase
Authors: Zhang Xiaoyan , Xiao Qingnong , Fitzpatrick Patrick J. 
Published: February 2007

AbstractNumerical experiments have been conducted to examine the impact of multisatellite data on the initialization and forecast of the rapid weakening of Hurricane Lili (in 2002) from 0000 UTC to landfall in Louisiana on 1300 UTC 3 October 2002. Fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) 4DVAR sensitivity runs were conducted separately with QuikSCAT surface winds, the Geostationary Operational Environmental Satellite-8 (GOES-8) cloud drift–water vapor winds, and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) temperature–dewpoint sounding data to investigate their individual impact on storm track and intensity. The results were compared against a simulation initialized from a Global Forecast System background interpolated to the MM5 grid. Assimilating QuikSCAT surface wind data improves the analyzed outer-core surface winds, as well as the inner-core low-level temperature and moisture fields. Substantial adjustments of winds are noted on the periphery of the hurricane by assimilating GOES-8 satellite-derived upper-level winds. Both track forecasts initialized at 1200 UTC 2 October 2002 with four-dimensional variational data assimilation (4DVAR) of QuikSCAT and GOES-8 show improvement compared to those initialized with the model background. Assimilating Aqua MODIS sounding data improves the outer-core thermodynamic features. The Aqua MODIS data has a slight impact on the track forecast, but more importantly shows evidence of impacting the model intensity predicting by retarding the incorrect prediction of intensification. All three experiments also show that bogusing of an inner-core wind vortex is required to depict the storm’s initial intensity.To properly investigate Lili’s weakening, data assimilation experiments that incorporate bogusing vortex, QuikSCAT winds, GOES-8 winds, and Aqua MODIS sounding data were performed. The 4DVAR satellite-bogus data assimilation is conducted in two consecutive 6-h windows preceding Lili’s weakening. Comparisons of the results between the experiments with and without satellite data indicated that the satellite data, particularly the Aqua MODIS sounding information, makes an immediate impact on the hurricane intensity change beyond normal bogusing procedures. The track forecast with the satellite data is also more accurate than just using bogusing alone. This study suggests that dry air intrusion played an important role in Lili’s rapid weakening. It also demonstrates the potential benefit of using satellite data in a 4DVAR context—particularly high-resolution soundings—on unusual cases like Hurricane Lili.
Estimating and Correcting Global Weather Model Error
Authors: Danforth Christopher M. , Kalnay Eugenia , Miyoshi Takemasa 
Published: February 2007

Abstract
The purpose of the present study is to explore the feasibility of estimating and correcting systematic model errors using a simple and efficient procedure, inspired by papers by Leith as well as DelSole and Hou, that could be applied operationally, and to compare the impact of correcting the model integration with statistical corrections performed a posteriori. An elementary data assimilation scheme (Newtonian relaxation) is used to compare two simple but realistic global models, one quasigeostrophic and one based on the primitive equations, to the NCEP reanalysis (approximating the real atmosphere). The 6-h analysis corrections are separated into the model bias (obtained by time averaging the errors over several years), the periodic (seasonal and diurnal) component of the errors, and the nonperiodic errors. An estimate of the systematic component of the nonperiodic errors linearly dependent on the anomalous state is generated.
Forecasts corrected during model integration with a seasonally dependent estimate of the bias remain useful longer than forecasts corrected a posteriori. The diurnal correction (based on the leading EOFs of the analysis corrections) is also successful. State-dependent corrections using the full-dimensional Leith scheme and several years of training actually make the forecasts worse due to sampling errors in the estimation of the covariance. A sparse approximation of the Leith covariance is derived using univariate and spatially localized covariances. The sparse Leith covariance results in small regional improvements, but is still computationally prohibitive. Finally, singular value decomposition is used to obtain the coupled components of the correction and forecast anomalies during the training period. The corresponding heterogeneous correlation maps are used to estimate and correct by regression the state-dependent errors during the model integration. Although the global impact of this computationally efficient method is small, it succeeds in reducing state-dependent model systematic errors in regions where they are large. The method requires only a time series of analysis corrections to estimate the error covariance and uses negligible additional computation during a forecast. As a result, it should be suitable for operational use at relatively small computational expense.
Scale-Selective Bias Correction in a Downscaling of Global Analysis Using a Regional Model
Authors: Kanamaru Hideki , Kanamitsu Masao 
Published: February 2007

Abstract
Systematic large-scale errors are often found within the regional domain in the regional dynamical downscaling procedure. This paper proposes a method to suppress such errors using a combination of spectral tendency damping and area average correction of temperature, humidity, and surface pressure in the Regional Spectral Model. The proposed scale-selective bias-correction method reduces the time tendency of the zonal and meridional wind components for the physical scale greater than a predetermined length. In addition, the area mean perturbations of temperature and humidity are forced to zero. The surface pressure difference between the model field and the global field is adjusted from the hydrostatic equation using the mean elevation difference between the two fields and the area mean temperature. Each of these three components of the technique is necessary for the model to effectively reduce large-scale errors in the regional domain. With this method, the downscaled field becomes less dependent on the domain size. Furthermore, the downscaled precipitation compares better with observations, as do the near-surface temperature and wind fields. The scheme allows much weaker lateral boundary relaxation, although it is still an essential part of the regional model. The use of a similar scheme is recommended for any regional model in the application of dynamical downscaling of analysis for climate studies.
Predictability of June–September Rainfall in Ethiopia
Authors: Korecha Diriba , Barnston Anthony G. 
Published: February 2007

Abstract
In much of Ethiopia, similar to the Sahelian countries to its west, rainfall from June to September contributes the majority of the annual total, and is crucial to Ethiopia’s water resource and agriculture operations. Drought-related disasters could be mitigated by warnings if skillful summer rainfall predictions were possible with sufficient lead time. This study examines the predictive potential for June–September rainfall in Ethiopia using mainly statistical approaches. The skill of a dynamical approach to predicting the El Niño–Southern Oscillation (ENSO), which impacts Ethiopian rainfall, is assessed. The study attempts to identify global and more regional processes affecting the large-scale summer climate patterns that govern rainfall anomalies. Multivariate statistical techniques are applied to diagnose and predict seasonal rainfall patterns using historical monthly mean global sea surface temperatures and other physically relevant predictor data. Monthly rainfall data come from a newly assembled dense network of stations from the National Meteorological Agency of Ethiopia. Results show that Ethiopia’s June–September rainy season is governed primarily by ENSO, and secondarily reinforced by more local climate indicators near Africa and the Atlantic and Indian Oceans. Rainfall anomaly patterns can be predicted with some skill within a short lead time of the summer season, based on emerging ENSO developments. The ENSO predictability barrier in the Northern Hemisphere spring poses a major challenge to providing seasonal rainfall forecasts two or more months in advance. Prospects for future breakthroughs in ENSO prediction are thus critical to future improvements to Ethiopia’s summer rainfall prediction.
Impact of Configurations of Rapid Intermittent Assimilation of WSR-88D Radar Data for the 8 May 2003 Oklahoma City Tornadic Thunderstorm Case
Authors: Hu Ming , Xue Ming 
Published: February 2007

Abstract
Various configurations of the intermittent data assimilation procedure for Level-II Weather Surveillance Radar-1988 Doppler radar data are examined for the analysis and prediction of a tornadic thunderstorm that occurred on 8 May 2003 near Oklahoma City, Oklahoma. Several tornadoes were produced by this thunderstorm, causing extensive damages in the south Oklahoma City area. Within the rapidly cycled assimilation system, the Advanced Regional Prediction System three-dimensional variational data assimilation (ARPS 3DVAR) is employed to analyze conventional and radar radial velocity data, while the ARPS complex cloud analysis procedure is used to analyze cloud and hydrometeor fields and adjust in-cloud temperature and moisture fields based on reflectivity observations and the preliminary analysis of the atmosphere. Forecasts for up to 2.5 h are made from the assimilated initial conditions. Two one-way nested grids at 9- and 3-km grid spacings are employed although the assimilation configuration experiments are conducted for the 3-km grid only while keeping the 9-km grid configuration the same. Data from the Oklahoma City radar are used. Different combinations of the assimilation frequency, in-cloud temperature adjustment schemes, and the length and coverage of the assimilation window are tested, and the results are discussed with respect to the length and evolution stage of the thunderstorm life cycle. It is found that even though the general assimilation method remains the same, the assimilation settings can significantly impact the results of assimilation and the subsequent forecast. For this case, a 1-h-long assimilation window covering the entire initial stage of the storm together with a 10-min spinup period before storm initiation works best. Assimilation frequency and in-cloud temperature adjustment scheme should be set carefully to add suitable amounts of potential energy during assimilation. High assimilation frequency does not necessarily lead to a better result because of the significant adjustment during the initial forecast period. When a short assimilation window is used, covering the later part of the initial stage of storm and using a high assimilation frequency and a temperature adjustment scheme based on latent heat release can quickly build up the storm and produce a reasonable analysis and forecast. The results also show that when the data from a single Doppler radar are assimilated with properly chosen assimilation configurations, the model is able to predict the evolution of the 8 May 2003 Oklahoma City tornadic thunderstorm well for up to 2.5 h. The implications of the choices of assimilation settings for real-time applications are discussed.
Sensitivity of Mesoscale Gravity Waves to the Baroclinicity of Jet-Front Systems
Authors: Wang Shuguang , Zhang Fuqing 
Published: February 2007

Abstract
This study investigates the sensitivity of mesoscale gravity waves to the baroclinicity of the background jet-front systems by simulating different life cycles of baroclinic waves with a high-resolution mesoscale model. Four simulations are made starting from two-dimensional baroclinic jets having different static stability and wind shear in order to obtain baroclinic waves with significantly different growth rates. In all experiments, vertically propagating mesoscale gravity waves are simulated in the exit region of upper-tropospheric jet streaks. A two-dimensional spectral analysis demonstrates that these gravity waves have multiple components with different wave characteristics. The short-scale wave components that are preserved by a high-pass filter with a cutoff wavelength of 200 km have horizontal wavelengths of 85–161 km and intrinsic frequencies of 3–11 times the Coriolis parameter. The medium-scale waves that are preserved by a bandpass filter (with 200- and 600-km cutoff wavelengths) have horizontal wavelengths of 250–350 km and intrinsic frequencies less than 3 times the Coriolis parameter. The intrinsic frequencies of these gravity waves tend to increase with the growth rate of the baroclinic waves; gravity waves with similar frequency are found in the experiments with similar average baroclinic wave growth rate but with significantly different initial tropospheric static stability and tropopause geometry. The residuals of the nonlinear balance equation are used to assess the flow imbalance. In all experiments, the developing background baroclinic waves evolve from an initially balanced state to the strongly unbalanced state especially near the exit region of upper-level jet fronts before mature mesoscale gravity waves are generated. It is found that the growth rate of flow imbalance also correlates well to the growth rate of baroclinic waves and thus correlates to the frequency of gravity waves.
An Analytic Longwave Radiation Formula for Liquid Layer Clouds
Authors: Larson Vincent E. , Kotenberg Kurt E. , Wood Norman B. 
Published: February 2007

Abstract
Many Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) intercomparisons of boundary layer clouds have used a convenient but idealized longwave radiation formula for clouds in their large-eddy simulations (LESs). Under what conditions is this formula justified? Can it be extended to midlevel layer clouds? This note first derives the GCSS formula using an alternative method to effective emissivity. A key simplifying assumption is that the cloud is isothermal in the vertical (and horizontal). However, this assumption does not turn out to be overly restrictive in practice. Then the GCSS formula is compared with a detailed numerical code, BugsRad. Sensitivity studies are performed in which cloud properties, cloud altitude, and thermodynamic profiles are modified. Here, the focus is primarily on midlevel, altostratocumulus layers. The results here show that the GCSS formula can be successfully extended to liquid (ice free), midlevel clouds. The GCSS formula produces remarkably accurate radiative profiles if the parameters are adjusted on a case-by-case basis. However, the formula needs to be calibrated using a more general radiative transfer code.
Chronic GvHD decreases antiviral immune responses in allogeneic BMT
Authors: Hossain Mohammad S. , Roback John D. , Pollack Brian P. , Jaye David L. , Langston Amelia , Waller Edmund K. 
Published: February 2007

AbstractChronic graft-versus-host disease (cGvHD) is associated with functional immunodeficiency and an increased risk of opportunistic infections in allogeneic bone marrow transplantation (BMT). We used a parent to F1 model of allogeneic BMT to test the hypothesis that cGvHD leads to impaired antigen-specific antiviral immunity and compared BM transplant recipients with cGvHD to control groups of allogeneic BM transplant recipients without GvHD. Mice with and without cGvHD received a nonlethal dose of murine cytomegalovirus (MCMV) +100 days after transplantation. Recipients with cGvHD had more weight loss and higher viral loads in the spleen and liver. MCMV infection led to greater than 25-fold expansion of donor spleen–derived MCMV peptide–specific tetramer-positive CD8+ T cells in blood of transplant recipients with and without cGvHD, but mice with cGvHD had far fewer antigen-specific T cells in peripheral tissues and secondary lymphoid organs. The immunosuppression associated with cGvHD was confirmed by vaccinating transplant recipients with and without cGvHD using a recombinant Listeria expressing MCMV early protein (Lm-MCMV). Secondary adoptive transfer of lymphocytes from donor mice with or without cGvHD into lymphopenic congenic recipients showed that cGvHD impaired tissue-specific homing of antigen-specific T cells. These results indicate that cGvHD causes an intrinsic immunosuppression and explain, in part, the functional immunodeficiency in allogeneic transplant recipients.
New thrombopoietic growth factors
Authors: Kuter David J. 
Published: February 2007

AbstractAlthough development of first-generation thrombopoietic growth factors (recombinant human thrombopoietin [TPO] and pegylated recombinant human megakaryocyte growth and development factor [PEG-rHuMGDF]) was stopped due to development of antibodies to PEG-rHuMGDF, nonimmunogenic second-generation thrombopoietic growth factors with unique pharmacologic properties have been developed. TPO peptide mimetics contain TPO receptor-activating peptides inserted into complementarity-determining regions of Fab (Fab 59), attached to the IgG Fc region (AMG 531), or pegylated (Peg-TPOmp). Orally available, TPO nonpeptide mimetics (eltrombopag, AKR-501) bind and activate the TPO receptor by a mechanism different from TPO and may have an additive effect to TPO. TPO agonist antibodies are monoclonal antibodies activating the TPO receptor but modified in size [TPO minibodies; ie, VB22B sc(Fv)2] or immunoglobuln type (domain subclass-converted TPO agonist antibodies; ie, MA01G4G344). All second-generation thrombopoietic growth factors stimulate growth of TPO-dependent cell lines via JAK2/STAT signaling pathways and increase platelet counts in animals. When tested in healthy humans, TPO peptide and nonpeptide mimetics produced a dose-dependent rise in platelet count. AMG 531 and eltrombopag markedly increase platelet counts in patients with immune thrombocytopenic purpura, without significant adverse effects. One or more second-generation thrombopoietic growth factors should soon be clinically available for treating thrombocytopenic disorders.
Treatment-related risk factors of inhibitor development in previously untreated patients with hemophilia A: the CANAL cohort study
Authors: Gouw Samantha C. , van der Bom Johanna G. , Marijke van den Berg H. 
Published: February 2007

AbstractThe CANAL Study (Concerted Action on Neutralizing Antibodies in severe hemophilia A) was designed to describe the relationship between treatment characteristics and inhibitor development in previously untreated patients with severe hemophilia A. This multicenter retrospective cohort study investigated 366 consecutive patients born between 1990 and 2000. The outcome was clinically relevant inhibitor development, defined as the occurrence of at least 2 positive inhibitor titers combined with a decreased recovery. Eighty-seven (24%) patients developed inhibitors (69 high titer [19%]). The incidence of inhibitors appeared to be associated with age at first treatment, decreasing from 41% for those treated within the first month of age to 18% in those treated after 18 months; after adjustment for treatment intensity, this association largely disappeared. Surgical procedures and peak treatment moments at start of treatment increased inhibitor risk (relative risk [RR], 3.7; 95% confidence interval [CI], 2.0-7.1; and RR, 3.3; CI, 2.1-5.3, respectively). Regular prophylaxis was associated with a 60% lower risk than on-demand treatment (RR, 0.4; CI, 0.2-0.8). Our findings suggest that the previously reported associated between an early age at first exposure and the risk of inhibitor development is largely explained by early, intensive treatment. The latter appears to be an independent risk factor for inhibitor development. In addition, early, regular prophylaxis may protect patients with hemophilia against the development of inhibitors.