bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surface Skin Temperature and the Interplay between Sensible and Ground Heat Fluxes over Arid Regions
Authors: Zeng Xubin , Wang Zhuo , Wang Aihui 
Published: May 2012

Abstract
Over arid regions, two community land models [Noah and Community Land Model (CLM)] still have difficulty in realistically simulating the diurnal cycle of surface skin temperature. Based on theoretical arguments and synthesis of previous observational and modeling efforts, three revisions are developed here to address this issue. The revision of the coefficients in computing roughness length for heat significantly reduces the underestimate of daytime skin temperature but has a negligible effect on nighttime skin temperature. The constraints of the minimum friction velocity and soil thermal conductivity help improve nighttime skin temperature under weak wind and dry soil conditions. These results are robust in both Noah and CLM, as well as in Noah, with 4 versus 10 soil layers based on in situ data at the Desert Rock site in Nevada with a monthly averaged diurnal amplitude of 31.7 K and the Gaize site over Tibet, China, with an amplitude of 44.6 K. While these revisions can be directly applied to CLM or other land models with subgrid tiles (including bare soil), suggestions are also made on their application to Noah and other land models that treat bare soil and vegetated area together in a model grid cell. It is suggested that the challenging issue of measuring and simulating surface sensible heat flux under stable conditions should be treated as a land–atmosphere coupled issue, involving the interplay of ground and sensible heat fluxes in balancing the net radiation over arid regions, rather than as an atmospheric turbulence issue alone. The implications of such a coupling perspective are also discussed.
Toward a Framework for Systematic Error Modeling of Spaceborne Precipitation Radar with NOAA/NSSL Ground Radar–Based National Mosaic QPE
Authors: Kirstetter Pierre-Emmanuel , Hong Y. , Gourley J. J. , Chen S. , Flamig Z. , Zhang J. , Schwaller M. , Petersen W. , Amitai E. 
Published: May 2012

Abstract
Characterization of the error associated with satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. The authors focus here on the error structure of NASA’s Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar–based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a 3-month data sample in the southern part of the United States. The primary contribution of this study is the presentation of the detailed steps required to derive a trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relies on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors are revealed and quantified including sensitivity to the processing steps with the reference rainfall, comparisons of rainfall detectability and rainfall-rate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall-rate estimates from other sensors on board low-earth-orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission.
Evaluation of Global Flood Detection Using Satellite-Based Rainfall and a Hydrologic Model
Authors: Wu Huan , Adler Robert F. , Hong Yang , Tian Yudong , Policelli Fritz 
Published: May 2012

Abstract
A new version of a real-time global flood monitoring system (GFMS) driven by Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) rainfall has been developed and implemented using a physically based hydrologic model. The purpose of this paper is to evaluate the performance of this new version of the GFMS in terms of flood event detection against flood event archives to establish a baseline of performance and directions for improvement. This new GFMS is quantitatively evaluated in terms of flood event detection during the TRMM era (1998–2010) using a global retrospective simulation (3-hourly and ⅛° spatial resolution) with the TMPA 3B42V6 rainfall. Four methods were explored to define flood thresholds from the model results, including three percentile-based statistical methods and a Log Pearson type-III flood frequency curve method. The evaluation showed the GFMS detection performance improves [increasing probability of detection (POD)] with longer flood durations and larger affected areas. The impact of dams was detected in the validation statistics, with the presence of dams tending to result in more false alarms and greater false-alarm duration. The GFMS validation statistics for flood durations &gt;3 days and for areas without dams vary across the four methods, but center around a POD of ~0.70 and a false-alarm rate (FAR) of ~0.65. The generally positive results indicate the value of this approach for monitoring and researching floods on a global scale, but also indicate limitations and directions for improvement of such approaches. These directions include improving the rainfall estimates, utilizing higher resolution in the runoff-routing model, taking into account the presence of dams, and improving the method for flood identification.
The Land Surface Analysis in the NCEP Climate Forecast System Reanalysis
Authors: Meng Jesse , Yang Rongqian , Wei Helin , Ek Michael , Gayno George , Xie Pingping , Mitchell Kenneth 
Published: May 2012

Abstract
The NCEP Climate Forecast System Reanalysis (CFSR) uses the NASA Land Information System (LIS) to create its land surface analysis: the NCEP Global Land Data Assimilation System (GLDAS). Comparing to the previous two generations of NCEP global reanalyses, this is the first time a coupled land–atmosphere data assimilation system is included in a global reanalysis. Global observed precipitation is used as direct forcing to drive the land surface analysis, rather than the typical reanalysis approach of using precipitation assimilating from a background atmospheric model simulation. Global observed snow cover and snow depth fields are used to constrain the simulated snow variables. This paper describes 1) the design and implementation of GLDAS/LIS in CFSR, 2) the forcing of the observed global precipitation and snow fields, and 3) preliminary results of global and regional soil moisture content and land surface energy and water budgets closure. With special attention made during the design of CFSR GLDAS/LIS, all the source and sink terms in the CFSR land surface energy and water budgets can be assessed and the total budgets are balanced. This is one of many aspects indicating improvements in CFSR from the previous NCEP reanalyses.
Simulation of Wave Breaking in One-Dimensional Spectral Environment
Authors: Chalikov Dmitry , Babanin Alexander V. 
Published: May 2012

Abstract
Results of numerical investigations, based on full dynamic equations, are presented for wave breaking in a one-dimensional environment with a wave spectrum. The breaking is defined as a process of irreversible collapse of an individual wave in physical space, and the incipient breaker is a wave that reached a dynamic condition of the limiting stability where the collapse has not started yet but is inevitable. The main attention is paid to documenting the evolution of different wave characteristics before the breaking commences. It is shown that the breaking is a localized process that rapidly develops in space and time. No single characteristic, such as wave steepness, wave height, and asymmetry, can serve as a predictor of the incipient breaking. The process of breaking is intermittent; it happens spontaneously and is individually unpredictable. The evolution of geometric, kinematic, and dynamic characteristics of the breaking wave describes the process of breaking itself rather than indicating an imminent breaking. It is shown that the criterion of breaking, valid for the breaking due to modulation instability in one-dimensional waves trains, is not universal if applied to the conditions of spectral environment. In this context, the development of algorithms for parameterization of breaking for wave prediction models and for direct wave simulations is more important.
Averaging-Related Biases in Monthly Latent Heat Fluxes
Authors: Hughes Paul J. , Bourassa Mark A. , Rolph Jeremy J. , Smith Shawn R. 
Published: May 2012

Abstract
Seasonal-to-multidecadal applications that require ocean surface energy fluxes often require accuracies of surface turbulent fluxes to be 5 W m−2 or better. While there is little doubt that uncertainties in the flux algorithms and input data can cause considerable errors, the impact of temporal averaging has been more controversial. The biases resulting from using monthly averaged winds, temperatures, and humidities in the bulk aerodynamic formula (i.e., the so-called classical method) to estimate the monthly mean latent heat fluxes are shown to be substantial and spatially varying in a manner that is consistent with most prior work. These averaging-related biases are linked to nonnegligible submonthly covariances between the wind, temperature, and humidity. To provide additional insight into the averaging-related bias, the methodology behind the third-generation Florida State University monthly mean surface flux product (FSU3) is detailed to highlight additional sources of errors in gridded datasets. The FSU3 latent heat fluxes suffer from this averaging-related bias, which can be as large as 90 W m−2 in western boundary current regions during winter and can exceed 40 W m−2 in synoptically active portions of the tropics. The regional impacts of these biases on the mixed layer temperature tendency are shown to demonstrate that the error resulting from applying the classical method is physically substantial.
An Analysis of the Nonstationarity in the Bias of Sea Surface Temperature Forecasts for the NCEP Climate Forecast System (CFS) Version 2
Authors: Kumar A. , Chen M. , Zhang L. , Wang W. , Xue Y. , Wen C. , Marx L. , Huang B. 
Published: May 2012

Abstract
For long-range predictions (e.g., seasonal), it is a common practice for retrospective forecasts (also referred to as the hindcasts) to accompany real-time predictions. The necessity for the hindcasts stems from the fact that real-time predictions need to be calibrated in an attempt to remove the influence of model biases on the predicted anomalies. A fundamental assumption behind forecast calibration is the long-term stationarity of forecast bias that is derived based on hindcasts.
Hindcasts require specification of initial conditions for various components of the prediction system (e.g., ocean, atmosphere) that are generally taken from a long reanalysis. Trends and discontinuities in the reanalysis that are either real or spurious can arise due to several reasons, for example, the changing observing system. If changes in initial conditions were to persist during the forecast, there is a potential for forecast bias to depend over the period it is computed, making calibration even more of a challenging task. In this study such a case is discussed for the recently implemented seasonal prediction system at the National Centers for Environmental Prediction (NCEP), the Climate Forecast System version 2 (CFS.v2).
Based on the analysis of the CFS.v2 for 1981–2009, it is demonstrated that the characteristics of the forecast bias for sea surface temperature (SST) in the equatorial Pacific had a dramatic change around 1999. Furthermore, change in the SST forecast bias, and its relationship to changes in the ocean reanalysis from which the ocean initial conditions for hindcasts are taken is described. Implications for seasonal and other long-range predictions are discussed.
Impact of Microphysics Scheme Complexity on the Propagation of Initial Perturbations
Authors: Wang Hongli , Auligné Thomas , Morrison Hugh 
Published: May 2012

AbstractThe study of evolution characteristics of initial perturbations is an important subject in four-dimensional variational data assimilation (4DVAR) and mesoscale predictability research. This paper evaluates the impact of microphysical scheme complexity on the propagation of the perturbations in initial conditions for warm-season convections over the central United States. The Weather Research and Forecasting Model (WRF), in conjunction with four schemes of the Morrison microphysics parameterization with varying complexity, was used to simulate convective cases using grids nested to 5-km horizontal grid spacing. Results indicate that, on average, the four schemes show similar perturbation evolution in amplitude and spatial pattern during the first 2 h. After that, the simplified schemes introduce significant error in amplitude and spatial pattern. The simplest (liquid only) and most complex schemes show almost the same growth rate of initial perturbations with different amplitudes during 6-h forecast, suggesting that the simplest scheme does not reduce the nonlinearity in the most complex scheme. The evolution of vertical velocity and total condensates is more nonlinear than horizontal wind, temperature, and humidity, which suggest that the observations of cloud variables and vertical velocity should have a shorter time window (less than 1 h) compared to horizontal wind, temperature, and humidity observations. The simplified liquid-only microphysics scheme can be used as an acceptable substitute for the more complex one with a short time window (less than 1 h).
Application of Boyd’s Periodization and Relaxation Method in a Spectral Atmospheric Limited-Area Model. Part II: Accuracy Analysis and Detailed Study of the Operational Impact
Authors: Degrauwe Daan , Caluwaerts Steven , Voitus Fabrice , Hamdi Rafiq , Termonia Piet 
Published: May 2012

Abstract
Spectral limited-area models face a particular challenge at their lateral boundaries: the fields need to be made periodic. Boyd proposed a windowing-based method to improve the periodization and relaxation. In a companion paper, the implementation of this windowing method in the operational semi-implicit semi-Lagrangian spectral HARMONIE system was described and some first reproducibility tests, comparing this method to the old existing one, were presented.
The present paper provides an in-depth study of the impact of this method for different configurations of the implementation. This is carried out in three steps in well-controlled experimental setups of increasing complexity. First, different aspects of Boyd’s method are analyzed in an idealized perfect-model test using a representative 1D shallow-water model. Second, the implementation is tested in an adiabatic 3D numerical weather prediction (NWP) model with perfect-model experiments. Finally, the impact of using Boyd’s method in a more operational-like NWP context is investigated as well. The presented tests show that, while the implementation of Boyd’s method is neutral in terms of scores, it is superior to the existing spline method in the case of strong dynamical forcings at the lateral boundaries.
Application of Boyd’s Periodization and Relaxation Method in a Spectral Atmospheric Limited-Area Model. Part I: Implementation and Reproducibility Tests
Authors: Termonia Piet , Voitus Fabrice , Degrauwe Daan , Caluwaerts Steven , Hamdi Rafiq 
Published: May 2012

Abstract
This paper describes the implementation of a proposal of Boyd for the periodization and relaxation of the fields in a full three-dimensional spectral semi-implicit semi-Lagrangian limited-area model structure of an atmospheric modeling system called HARMONIE that is used for numerical weather prediction and regional climate studies. Some first feasibility tests in an operational numerical weather prediction context are presented. They show that, in terms of standard operational forecast scores, Boyd’s windowing-based method provides comparable performance as the old existing spline-based periodization procedure. However, the real improvements of this method should be expected in specific cases of strong dynamical forcings at the lateral boundaries. An extensive demonstration of the superiority of this windowing-based method is provided in an accompanying paper.
Influence of the Lake Erie Overlake Boundary Layer on Deep Convective Storm Evolution
Authors: Workoff Thomas E. , Kristovich David A. R. , Laird Neil F. , LaPlante Robert , Leins Daniel 
Published: May 2012

Abstract
The influence that the overlake boundary layer has on storm intensity and structure is not well understood. To improve scientists’ understanding of the evolution of storms crossing Lake Erie, 111 events during 2001–09 were examined using observations from Weather Surveillance Radar-1988 Doppler (WSR-88D), surface, buoy, and rawinsonde sites. It was found that on average, all storm modes tended to weaken over the lake; however, considerable variability in changes of storm intensity existed, with some storms exhibiting steady-state or increasing intensity in specific environments. Noteworthy changes in the storm maximum reflectivity generally occurred within 60 min after storms crossed the upwind shoreline. Isolated and cluster storm modes exhibited much greater weakening than those storms organized into lines or convective complexes. The atmospheric parameters having the greatest influence on storm intensity over Lake Erie varied by mode. Isolated and cluster storms generally weakened more rapidly with increasingly cold overlake surface air temperatures. Linear and complex systems, on the other hand, tended to exhibit constant or increasing maximum reflectivity with cooler overlake surface air temperatures. It is suggested that strongly stable conditions near the lake surface limit the amount of boundary layer air ingested into storms in these cases.
Convective Modes for Significant Severe Thunderstorms in the Contiguous United States. Part I: Storm Classification and Climatology
Authors: Smith Bryan T. , Thompson Richard L. , Grams Jeremy S. , Broyles Chris , Brooks Harold E. 
Published: May 2012

Abstract
Radar-based convective modes were assigned to a sample of tornadoes and significant severe thunderstorms reported in the contiguous United States (CONUS) during 2003–11. The significant hail (≥2-in. diameter), significant wind (≥65-kt thunderstorm gusts), and tornadoes were filtered by the maximum event magnitude per hour on a 40-km Rapid Update Cycle model horizontal grid. The filtering process produced 22 901 tornado and significant severe thunderstorm events, representing 78.5% of all such reports in the CONUS during the sample period. The convective mode scheme presented herein begins with three radar-based storm categories: 1) discrete cells, 2) clusters of cells, and 3) quasi-linear convective systems (QLCSs). Volumetric radar data were examined for right-moving supercell (RM) and left-moving supercell characteristics within the three radar reflectivity designations. Additional categories included storms with marginal supercell characteristics and linear hybrids with a mix of supercell and QLCS structures. Smoothed kernel density estimates of events per decade revealed clear geographic and seasonal patterns of convective modes with tornadoes. Discrete and cluster RMs are the favored convective mode with southern Great Plains tornadoes during the spring, while the Deep South displayed the greatest variability in tornadic convective modes in the fall, winter, and spring. The Ohio Valley favored a higher frequency of QLCS tornadoes and a lower frequency of RM compared to the Deep South and the Great Plains. Tornadoes with nonsupercellular/non-QLCS storms were more common across Florida and the high plains in the summer. Significant hail events were dominated by Great Plains supercells, while variations in convective modes were largest for significant wind events.
Steady‐State Pharmacokinetics of Etravirine and Lopinavir/Ritonavir Melt Extrusion Formulation, Alone and in Combination, in Healthy HIV‐Negative Volunteers
Authors: Schöller‐Gyüre Monika , Kakuda Thomas N. , Witek James , Akuma Sophie H. , Smedt Goedele De , Spittaels Kurt , Vyncke Veerle , Hoetelmans Richard M.W. 
Published: May 2012

AbstractBackgroundA previous study investigating coadministration of etravirine, a nonnucleoside reverse transcriptase inhibitor, and lopinavir/ritonavir soft‐gel formulation resulted in nonclinically relevant changes in etravirine and lopinavir exposure. The current study evaluated the pharmacokinetic interaction between etravirine and the lopinavir/ritonavir melt extrusion formulation.MethodSixteen human immunodeficiency virus (HIV)‐negative volunteers were randomized to either treatment sequence A/B or B/A, with 14 days— washout between treatments (treatment A: etravirine 200 mg bid for 8 days; treatment B: lopinavir/ritonavir 400/100 mg bid for 16 days with etravirine 200 mg bid on days 9‐16). Steady‐state pharmacokinetics were assessed for all antiretrovirals alone and coadministered; pharmacokinetic parameters were obtained by noncompartmental analysis. Safety and tolerability were assessed.ResultsCoadministration of etravirine and lopinavir/ritonavir resulted in a 35% decrease in etravirine exposure. Smaller decreases (<13%) were observed in lopinavir and ritonavir exposure. Six volunteers reported headache; 1 grade 3 triglyceride increase was reported.ConclusionLopinavir/ritonavir induced etravirine metabolism to a similar extent as most other boosted HIV protease inhibitors. The short‐term coadministration of etravirine and lopinavir/ritonavir was well tolerated and did not lead to increased incidences of adverse events.
The Combination of Exposure‐Response and Case‐Control Analyses in Regulatory Decision Making
Authors: Yang Jun , Zhao Hong , Garnett Christine , Rahman Atiqur , Gobburu Jogarao V. , Pierce William , Schechter Genevieve , Summers Jeffery , Keegan Patricia , Booth Brian , Wang Yaning 
Published: May 2012

AbstractTo reduce the bias introduced by confounding risk factors, a case‐control comparison was incorporated in the exposure‐response (ER) analysis to evaluate the recommended dosing regimen for trastuzumab in a pivotal trial. Results of Kaplan‐Meier survival analysis suggest that patients with metastatic gastric cancer (mGC) in the lowest quartile trough concentrations of trastuzumab in cycle 1 (Cmin 1) had shorter overall survival (OS) than did those in other quartiles. The result of the case‐matched control comparison suggests that adjusting for these risk factors, patients with the lowest quartile of trastuzumab exposure did not benefit from addition of trastuzumab treatment to chemotherapy. The identified subgroup without survival benefit and the ER relationship support the recommendation on conducting clinical trials to identify a treatment regimen with greater exposure and acceptable safety profiles and to prospectively evaluate whether this treatment regimen will result in survival benefit for the identified subgroup.