bluuebunny/crossref_metadata_2025_split huggingface dataset:
Error Covariance Matrices Characterization in the Ocean Salinity Retrieval Cost Function within the SMOS Mission
Authors: Talone M. , Gabarró C. , Camps A. , Sabia R. , Gourrion J. , Vall-llossera M. , Font J. 
Published: May 2011

Abstract
The interests of the scientific community working on the Soil Moisture and Ocean Salinity (SMOS) ocean salinity level 2 processor definition are currently focused on improving the performance of the retrieval algorithm, which is based on an iterative procedure where a cost function relating models, measurements, and auxiliary data is minimized. For this reason, most of the effort is currently focused on the analysis and the optimization of the cost function.
Within this framework, this study represents a contribution to the assessment of one of the pending issues in the definition of the cost function: the optimal weight to be given to the radiometric measurements with respect to the weight given to the background geophysical terms.
A whole month of brightness temperature acquisitions have been simulated by means of the SMOS-End-to-End Performance Simulator. The level 2 retrieval has been performed using the Universitat Politècnica de Catalunya (UPC) level 2 processor simulator using four different configurations, namely, the direct covariance matrices, the two cost functions currently described in the SMOS literature, and, finally, a new weight (the so-called effective number of measurement).
Results show that not even the proposed weight properly drives the minimization, and that the current cost function has to be modified in order to avoid the introduction of artifacts in the retrieval procedure. The calculation of the brightness temperature misfit covariance matrices reveals the presence of very complex patterns, and the inclusion of those in the cost function strongly modifies the retrieval performance. Worse but more Gaussian results are obtained, pointing out the need for a more accurate modeling of the correlation between brightness temperature misfits, in order to ensure a proper balancing with the relative weights to be given to the geophysical terms.
Toward a Multiscale Approach for Computational Atmospheric Modeling
Authors: Alam Jahrul M. 
Published: May 2011

Abstract
Atmospheric motions are generally characterized by a wide range of multiple length and time scales, and a numerical method must use a fine grid to resolve such a wide range of scales. Furthermore, a very fine grid requires an extremely small time step in order to keep explicit time integration schemes stable. Therefore, high-resolution meteorological simulations are very expensive.
A novel multiscale modeling approach is, therefore, presented for simulating atmospheric flows. In this approach, a prognostic variable representing a highly intermittent multiscale feature is decomposed into a significant and a nonsignificant part using wavelets, where the significant part is represented by a small fraction of the wavelet modes. The proposed multiscale methodology has been verified for simulating three cases: Smolarkiewicz’s deformational flow model, warm thermals in a dry atmosphere, and the dynamics of a vortex pair with ambient stable stratification. Comparisons with benchmark simulations and with a reference model are evidence for the convergence and stability of the proposed model. The comparison with the reference model has revealed that about 93% of the grid points are not necessary to resolve the significant motion in a warm thermal simulation, saving about 96% of the CPU time. Moreover, the CPU time varies linearly with the number of significant wavelet modes, showing that the present fully implicit adaptive model is asymptotically optimal for this simulation. These primary results point toward the benefit of constructing multiscale atmospheric models using the adaptive wavelet methodology.
A Preliminary Look at the Social Perspective of Warn-on-Forecast: Preferred Tornado Warning Lead Time and the General Public’s Perceptions of Weather Risks
Authors: Hoekstra S. , Klockow K. , Riley R. , Brotzge J. , Brooks H. , Erickson S. 
Published: May 2011

AbstractTornado warnings are currently issued an average of 13 min in advance of a tornado and are based on a warn-on-detection paradigm. However, computer model improvements may allow for a new warning paradigm, warn-on-forecast, to be established in the future. This would mean that tornado warnings could be issued one to two hours in advance, prior to storm initiation. In anticipation of the technological innovation, this study inquires whether the warn-on-forecast paradigm for tornado warnings may be preferred by the public (i.e., individuals and households). The authors sample is drawn from visitors to the National Weather Center in Norman, Oklahoma. During the summer and fall of 2009, surveys were distributed to 320 participants to assess their understanding and perception of weather risks and preferred tornado warning lead time. Responses were analyzed according to several different parameters including age, region of residency, educational level, number of children, and prior tornado experience. A majority of the respondents answered many of the weather risk questions correctly. They seemed to be familiar with tornado seasons; however, they were unaware of the relative number of fatalities caused by tornadoes and several additional weather phenomena each year in the United States. The preferred lead time was 34.3 min according to average survey responses. This suggests that while the general public may currently prefer a longer average lead time than the present system offers, the preference does not extend to the 1–2-h time frame theoretically offered by the warn-on-forecast system. When asked what they would do if given a 1-h lead time, respondents reported that taking shelter was a lesser priority than when given a 15-min lead time, and fleeing the area became a slightly more popular alternative. A majority of respondents also reported the situation would feel less life threatening if given a 1-h lead time. These results suggest that how the public responds to longer lead times may be complex and situationally dependent, and further study must be conducted to ascertain the users for whom the longer lead times would carry the most value. These results form the basis of an informative stated-preference approach to predicting public response to long (&gt;1 h) warning lead times, using public understanding of the risks posed by severe weather events to contextualize lead-time demand.
Gulf Coast Residents Underestimate Hurricane Destructive Potential
Authors: Stewart Alan E. 
Published: May 2011

Abstract
Most people do not realize that hurricane destructiveness increases nonlinearly with increases in storm intensity. Three studies were conducted to examine people’s perceptions of hurricane destructive potential and their likelihood of evacuation. In the first study, undergraduate students (n = 349) provided damage ratings of hurricanes in each Saffir–Simpson category. A majority (84%) of students produced only linearly increasing damage profiles by hurricanes. In the second study, a simple random sample of Gulf Coast residents (n = 402) who participated in a telephone survey when a tropical storm was affecting the U.S. east coast revealed that a majority (77%) thought hurricane damages increased linearly with hurricane category and hence underestimated the damage major hurricanes could produce. In the third study, a simple random sample (n = 396) of Gulf Coast residents participated in an experiment over the telephone during an active phase of the 2008 hurricane season. One-half of the sample received information about the nonlinearly increasing damage potential of hurricanes; the other half received the Saffir–Simpson hurricane scale category alone. The group in which hurricane damages were framed nonlinearly reported significantly greater self-reported likelihood of evacuation than residents who received the Saffir–Simpson hurricane category information. Studies 1 and 2 suggest that the public needs to learn more about the nonlinear relationship between hurricane intensity and the corresponding damages that may result. Study 3 suggests that framing possible storm damages in the nonlinearly increasing multiples of damages produced relative to a minimal hurricane may increase compliance with evacuation orders.
Vermont Climate Change Indicators
Authors: Betts Alan K. 
Published: May 2011

AbstractClimate change indicators are developed for Vermont in recent decades based on the trends in freeze dates, the length of the growing season, the frozen period of small lakes, and the onset of spring. These trends, which show a consistent pattern of a warming climate in Vermont during the past 50 yr, provide useful information for climate change adaptation planning for the state. The freeze period has become shorter and the growing season for frost-sensitive plants has become longer by about 3.7 (±1.1) days decade−1, the date of the last spring freeze has come earlier by 2.3 (±0.7) days decade−1, and the first autumn freeze has come later by 1.5 (±0.8) days decade−1. The frozen period for small lakes, which depends on mean temperatures over longer periods, has decreased faster by 6.9 (±1.5) days decade−1. Lake freeze-up has occurred later by 3.9 (±1.1) days decade−1, while ice-out has come earlier by 2.9 (±1.0) days decade−1. Lilac first leaf has also been coming earlier by 2.9 (±0.8) days decade−1, while lilac first bloom has advanced more slowly, by 1.6 (±0.6) days decade−1. The first leaf of Vermont lilacs, an indicator of early spring, is closely correlated with the ice-out of the small reference lake, Stile’s Pond, because both are related to temperatures in February–April. In the past 40 yr, the growing season for frost-sensitive plants has increased by 2 weeks, and the growing season for frost-hardy plants may have increased more.
Column Water Vapor Statistics and Their Relationship to Deep Convection, Vertical and Horizontal Circulation, and Moisture Structure at Nauru
Authors: Lintner Benjamin R. , Holloway Christopher E. , Neelin J. David 
Published: May 2011

Abstract
Relationships among relatively high-frequency probability distribution functions (pdfs) of anomalous column water vapor (cwv), precipitating deep convection, and the vertical and horizontal structures of circulation and tropospheric moisture are investigated for the Atmospheric Radiation Measurement (ARM) climate observing facility at Nauru in the western equatorial Pacific. At the highest frequencies (subdaily) analyzed, the cwv pdf exhibits a Gaussian core with pronounced longer-than-Gaussian, approximately exponential tails, with the relatively lower-frequency submonthly pdfs becoming more Gaussian distributed across the entire range of cwv variability. The genesis and morphology of the longer-than-Gaussian tails are examined within the context of several hypothetical mechanisms outlined in prior work. For example, pdf conditioning on ARM optical gauge precipitation measurements reveals an association of the positive-side tail with precipitating deep convective conditions; thus, despite the condensation and fallout of cwv during rainfall events, it is argued that updraft vertical motions associated with deep convection locally compensate the loss by increasing cwv. Using vertical moisture profiles from ARM radiosonde measurements, vertical structures of specific humidity anomalies associated with tail-regime cwv excursions are computed, with the negative cwv profile significantly departing from the mean profile in the lower free troposphere. Such behavior is consistent with local restorative surface evaporative forcing and turbulent mixing in the atmospheric boundary layer and drying of the column from above during descent conditions. Analysis of cwv variability with respect to the horizontal moisture structure, using gridded measurements from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and trajectories from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by NCEP–NCAR reanalysis meteorology underscores how the horizontal and vertical components modulate Nauru cwv: in particular, high cwv conditions at Nauru are often associated with weakened low-level inflow from the dry regions to the east of Nauru and stronger along-trajectory ascent. Finally, comparison of the ARM-based pdfs to those estimated from the reanalysis illustrates how pdf-based diagnostics may be useful tools for model intercomparison and validation.
A New Characterization of the Land Surface Heterogeneity over Africa for Use in Land Surface Models
Authors: Kaptué Tchuenté Armel Thibaut , Roujean Jean-Louis , Bégué Agnès , Los Sietse O. , Boone Aaron A. , Mahfouf Jean-François , Carrer Dominique , Daouda Badiane 
Published: May 2011

AbstractInformation related to land surface is immensely important to global change science. For example, land surface changes can alter regional climate through its effects on fluxes of water, energy, and carbon. In the past decades, data sources and methodologies for characterizing land surface heterogeneity (e.g., land cover, leaf area index, fractional vegetation cover, bare soil, and vegetation albedos) from remote sensing have evolved rapidly. The double ECOCLIMAP database—constituted of a land cover map and land surface variables and derived from Advanced Very High Resolution Radiometer (AVHRR) observations acquired between April 1992 and March 1993—was developed to support investigations that require information related to spatiotemporal dynamics of land surface. Here is the description of ECOCLIMAP-II: a new characterization of the land surface heterogeneity based on the latest generation of sensors, which represents an update of the ECOCLIMAP-I database over Africa. Owing to the many features of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors (more accurate in spatial resolution and spectral information compared to the AVHRR sensor), a variety of methods have been developed for an extended period of 8 yr (2000–07) to strengthen consistency between land surface variables as required by the meteorological and ecological communities. The relative accuracy (or performance) quality of ECOCLIMAP-II was assessed (i.e., by comparison with other global datasets). Results illustrate a substantial refinement; for instance, the fractional vegetation cover resulting in a root-mean-square error of 34% instead of 64% in comparison with the original version of ECOCLIMAP.
Monitoring of IR Clear-Sky Radiances over Oceans for SST (MICROS)
Authors: Liang Xingming , Ignatov Alexander 
Published: May 2011

Abstract
Monitoring of IR Clear-Sky Radiances over Oceans for SST (MICROS) is a Web-based tool to monitor “model minus observation” (M − O) biases in clear-sky brightness temperatures (BTs) and sea surface temperatures (SSTs) produced by the Advanced Clear-Sky Processor for Oceans (ACSPO). Currently, MICROS monitors M − O biases in three Advanced Very High Resolution Radiometer (AVHRR) bands centered at 3.7, 11, and 12 μm for five satellites, NOAA-16, -17, -18, -19 and Meteorological Operational (MetOp)-A. The fast Community Radiative Transfer Model (CRTM) is employed to simulate clear-sky BTs, using Reynolds SST and National Centers for Environmental Prediction Global Forecast System profiles as input. Simulated BTs are used in ACSPO for improving cloud screening, physical SST inversions, and monitoring and validating satellite BTs. The key MICROS objectives are to fully understand and reconcile CRTM and AVHRR BTs, and to minimize cross-platform biases through improvements to ACSPO algorithms, CRTM and its inputs, satellite radiances, and skin-bulk and diurnal SST modeling.
Initially, MICROS was intended for internal use within the National Environmental Satellite, Data, and Information Service (NESDIS) SST team for testing and improving ACSPO products. However, it has quickly outgrown this initial objective and is now used by several research and applications groups. In particular, inclusion of double differences in MICROS has contributed to sensor-to-sensor monitoring within the Global Space-Based Intercalibration System, which is customarily performed using the well-established simultaneous nadir overpass technique. Also, CRTM scientists have made a number of critical improvements to CRTM using MICROS results. They now routinely use MICROS to continuously monitor M − O biases and validate and improve CRTM performance. MICROS is also instrumental in evaluating the accuracy of the first-guess SST and upper-air fields used as input to CRTM. This paper gives examples of these applications and discusses ongoing work and future plans.
On the Rapid Intensification of Hurricane Wilma (2005). Part I: Model Prediction and Structural Changes
Authors: Chen Hua , Zhang Da-Lin , Carton James , Atlas Robert 
Published: May 2011

Abstract
In this study, a 72-h cloud-permitting numerical prediction of Hurricane Wilma (2005), covering its initial 18-h spinup, an 18-h rapid intensification (RI), and the subsequent 36-h weakening stage, is performed using the Weather Research Forecast Model (WRF) with the finest grid length of 1 km. The model prediction uses the initial and lateral boundary conditions, including the bogus vortex, that are identical to the Geophysical Fluid Dynamics Laboratory’s then-operational data, except for the time-independent sea surface temperature field. Results show that the WRF prediction compares favorably in many aspects to the best-track analysis, as well as satellite and reconnaissance flight-level observations. In particular, the model predicts an RI rate of more than 4 hPa h−1 for an 18-h period, with the minimum central pressure of less than 889 hPa. Of significance is that the model captures a sequence of important inner-core structural variations associated with Wilma’s intensity changes, namely, from a partial eyewall open to the west prior to RI to a full eyewall at the onset of RI, rapid eyewall contraction during the initial spinup, the formation of double eyewalls with a wide moat area in between during the most intense stage, and the subsequent eyewall replacement leading to the weakening of Wilma. In addition, the model reproduces the boundary layer growth up to 750 hPa with an intense inversion layer above in the eye. Recognizing that a single case does not provide a rigorous test of the model predictability due to the stochastic nature of deep convection, results presented herein suggest that it is possible to improve forecasts of hurricane intensity and intensity changes, and especially RI, if the inner-core structural changes and storm size could be reasonably predicted in an operational setting using high-resolution cloud-permitting models with realistic initial conditions and model physical parameterizations.
The Potential for Seasonal Forecasting of Winter Wave Heights in the Northern North Sea
Authors: Colman Andrew W. , Palin Erika J. , Sanderson Michael G. , Harrison Robert T. , Leggett Ian M. 
Published: May 2011

Abstract
The height of waves at North Sea oil and gas installations is an important factor governing the degree to which operational activities may be undertaken at those facilities. A link between the North Atlantic Oscillation (NAO) and winter (defined as December–February) wave heights at North Sea oil and gas installations has been established. A tool has been developed that uses a forecast NAO index to predict the proportions of wave heights in four categories that could be used to assess the operational downtime that will be experienced in the coming winter. The wave height forecasting system is shown to have useful skill in predicting the probability of occurrence of a stormy winter, and therefore probability forecasts provide a potentially useful guide to whether more or less disruption than the “climatological mean” might be experienced. The main limit on the skill of the wave forecasts is our very limited ability to accurately predict the NAO index on seasonal time scales.
Modeling the Control of Attention in Visual Workspaces
Authors: Steelman Kelly S. , McCarley Jason S. , Wickens Christopher D. 
Published: May 2011

Objective: The present study developed and validated a stochastic model of overt attention within a visual workspace. Background: Technical specifications and recommended practices for the design of visual warning systems emphasize the role of alert salience. Task demands and display context can modulate alert noticeability, however, meaning that salience alone does not guarantee attention capture. Method: A stochastic model integrated elements from existing models of visual attention to predict attentional behavior in dynamic environments. Validation studies tested the predictions of the new model against scanning data from a high-fidelity simulator study and behavioral data from an alert detection experiment. Results: The model accurately predicted the steady-state distribution of attention within a simulated cockpit as well as the effects of color similarity, eccentricity, and dynamic visual noise on miss rates and response times in the alert detection task. Conclusion: The model successfully predicts attentional behavior in complex visual workspaces with the use of parameter values selected by either the modeler or a subject matter expert. Application: The model provides a tool to test the effectiveness of visual alerts in various display configurations and with varying task demands.
Identification of a non-linear F/A-18 model by the use of fuzzy logic and neural network methods
Authors: Boely N , Botez R M , Kouba G 
Published: May 2011

The aim of this article is to determine the mathematical model between control deflections and structural deflections in an F/A-18 modified aircraft in the active aeroelastic wing programme. One future application would be the design of a flutter suppression model based on flight flutter tests. Five excited sources were provided by NASA Dryden Flight Research Center from flight flutter tests. These excitations, given by aircraft control surfaces, are: differential and collective ailerons, collective and differential stabilizers, and rudders. The neural network and fuzzy logic algorithms were chosen in order to identify the multi-input multi-output system for the F/A-18 aircraft. One main contribution of this article is the mapping of fuzzy logic algorithm results into neural network data. Then, these methods were applied for the F/A-18 model identification and validation for sixteen flight conditions expressed in terms of Mach numbers variations between 0.85 and 1.30 and altitudes varying between 5000 and 25 000 ft. Accurate results were obtained, expressed in terms of fit coefficients between estimated and measured signals greater than 99 per cent, which allows one to conclude that these new methodologies are very efficient for an aircraft identification and validation.