bluuebunny/crossref_metadata_2025_split huggingface dataset:
Polarimetric Radar Observation of the Melting Layer in a Convective Rainfall System during the Rainy Season over the East China Sea
Authors: Shusse Yukari , Takahashi Nobuhiro , Nakagawa Katsuhiro , Satoh Shinsuke , Iguchi Toshio 
Published: October 2010

Abstract
During the rainy season over the East China Sea, convective rainfalls often show melting layer (ML) characteristics in polarimetric radar variables. In this research, the appearance ratio of the ML (the ratio of rainfall area accompanied by polarimetric ML signatures) and the variation in height of the level of the ML signature maximum (MLSM level; defined by the level of the ρhv minimum in the ML) in a convective rainfall region in a rainfall system over the East China Sea observed on 2 June 2006 were studied using C-band polarimetric radar (COBRA). For this analysis, a method of rainfall type classification that evaluates the presence of an ML in addition to providing conventional convective–stratiform classification using range–height indicator (RHI) observation data was developed. This rainfall type classification includes two steps: conventional convective–stratiform separation using the horizontal distribution of Zh at 2-km altitude, and ML detection using the vertical profile of ρhv at each horizontal grid point. Using a combination of these two classifications, the following four rainfall types were identified: 1) convective rainfall with an ML, 2) convective rainfall with no ML, 3) stratiform rainfall with an ML, and 4) stratiform rainfall with no ML. An ML was detected in 53.9% of the convective region in the rainfall system. Using the same definition, an ML was detected in 83.1% of the stratiform region. The ML in the convective region showed a marked decrease in ρhv coincident with an increase in ZDR around the ambient 0°C level, as did that in the stratiform region. Melting aggregated snow was the likely cause of the ML signature in the convective region. The average height of the MLSM level in the convective region was 4.64 km, which is 0.46 km higher than that in the stratiform region (4.18 km) and 0.27 km higher than the ambient 0°C level (4.37 km).
Uncertainty Analysis for CloudSat Snowfall Retrievals
Authors: Hiley Michael J. , Kulie Mark S. , Bennartz Ralf 
Published: October 2010

Abstract
A new method to derive radar reflectivity–snow rate (Ze–S) relationships from scattering properties of different ice particle models is presented. Three statistical Ze–i relationships are derived to characterize the best estimate and uncertainties due to ice habit. The derived relationships are applied to CloudSat data to derive near-surface snowfall retrievals. Other uncertainties due to various method choices, such as vertical continuity tests, the near-surface reflectivity threshold used for choosing snowfall cases, and correcting for attenuation, are also explored on a regional and zonally averaged basis. The vertical continuity test in particular is found to have interesting regional effects. Although it appears to be useful for eliminating ground clutter over land, it also masks out potential lake-effect-snowfall cases over the Southern Ocean storm-track region. The choice of reflectivity threshold is found to significantly affect snowfall detection but is insignificant in terms of the mean snowfall rate. The use of an attenuation correction scheme can increase mean snowfall rates by ∼20%–30% in some regions. The CloudSat-collocated Advanced Microwave Scanning Radiometer (AMSR)-derived liquid water path is also analyzed, and significant amounts of cloud liquid water are often present in snowfall cases in which surface temperature is below freezing, illustrating the need to improve the arbitrary model-derived surface temperature criterion used to select “dry” snowfall cases. Precipitation measurements from conventional surface weather stations across Canada are used in an initial attempt to evaluate CloudSat snowfall retrievals. As expected, evaluation with ground-based data is fraught with difficulties. Encouraging results are found at a few stations, however—in particular, those located at very high latitudes.
Future Occurrence of Threshold-Crossing Seasonal Rainfall Totals: Methodology and Application to Sites in Africa
Authors: Siebert Asher B. , Ward M. Neil 
Published: October 2010

Abstract
A statistical simulation framework is developed to explore the future frequencies of threshold-crossing events, focusing here on low seasonal rainfall totals. Global change (GC) is represented by a trend on the seasonal mean rainfall total. Natural decadal to multidecadal variability (MDV) is represented by an autoregressive process. Interannual variability (IV) of seasonal totals is represented by white noise with either a normal or skew normal distribution consistent with parameters observed in the historical record at the location being modeled. Monte Carlo simulations are undertaken for various combinations of the above components, and the authors evaluate the extent to which future event frequencies can be estimated from the statistics of previous years. The sample of four study locations used to illustrate the approach is drawn from the Millennium Villages Project in Africa, where the potential of index insurance as a development and adaptation tool has been considered, thereby bringing a targeted problem setting to the analyses. The simulations highlight a number of general principles. For example, it is shown that a 10% change in the mean rainfall can lead to a change of order times 2 in the number of threshold-crossing low seasonal rainfall totals, even without invoking any change in the characteristics of the IV. The magnitudes of change are also shown to be sensitive to the threshold studied, as well as to site-specific climate features (here, coefficient of variation and skewness). The framework developed permits quantification of how, especially in the near term (of order 30 years), MDV can strongly add to uncertainty about future event frequencies. Therefore, statistical treatment of estimated MDV magnitudes will often be a key input to optimal risk management, with further enhancements expected through explicit MDV forecasts. The results highlight the importance of finding optimal ways to update climate statistics such as event thresholds, in the presence of GC and MDV.
A Modular Optimal Estimation Method for Combined Radar–Radiometer Precipitation Profiling
Authors: Munchak S. Joseph , Kummerow Christian D. 
Published: October 2010

Abstract
Although zonal mean rain rates from the Tropical Rainfall Measuring Mission (TRMM) are in good (&lt;10%) agreement between the TRMM Microwave Imager (TMI) and precipitation radar (PR) rainfall algorithms, significant uncertainties remain in some regions where these estimates differ by as much as 30% over the period of record. Previous comparisons of these algorithms with ground validation (GV) rainfall have shown significant (&gt;10%) biases of differing sign at various GV locations. Reducing these biases is important in the context of developing a database of cloud profiles for passive microwave retrievals that is based upon the PR-measured profiles. A retrieval framework based upon optimal estimation theory is proposed wherein three parameters describing the raindrop size distribution (DSD), ice particle size distribution, and cloud water path (cLWP) are retrieved for each radar profile. The modular nature of the framework provides the opportunity to test the sensitivity of the retrieval to the inclusion of different measurements, retrieved parameters, and models for microwave scattering properties of hydrometeors. The retrieved rainfall rate is found to be strongly sensitive to the a priori constraints in DSD and cLWP; thus, these parameters are tuned to match polarimetric radar estimates of rainfall near Kwajalein, Republic of Marshall Islands. An independent validation against gauge-tuned radar rainfall estimates at Melbourne, Florida, shows agreement within 2%, which exceeds previous algorithms’ ability to match rainfall at these two sites. Errors between observed and simulated brightness temperatures are reduced and climatological features of the DSD, as measured by disdrometers at these two locations, are also reproduced in the output of the combined algorithm.
Indian and Pacific Ocean Influences on Southeast Australian Drought and Soil Moisture
Authors: Ummenhofer Caroline C. , Sen Gupta Alexander , Briggs Peter R. , England Matthew H. , McIntosh Peter C. , Meyers Gary A. , Pook Michael J. , Raupach Michael R. , Risbey James S. 
Published: October 2010

AbstractThe relative influences of Indian and Pacific Ocean modes of variability on Australian rainfall and soil moisture are investigated for seasonal, interannual, and decadal time scales. For the period 1900–2006, observations, reanalysis products, and hindcasts of soil moisture during the cool season (June–October) are used to assess the impacts of El Niño–Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD) on southeastern Australia and the Murray–Darling Basin, two regions that have recently suffered severe droughts. A distinct asymmetry is found in the impacts of the opposite phases of both ENSO and IOD on Australian rainfall and soil moisture. There are significant differences between the dominant drivers of drought at interannual and decadal time scales. On interannual time scales, both ENSO and the IOD modify southeastern Australian soil moisture, with the driest (wettest) conditions over the southeast and more broadly over large parts of Australia occurring during years when an El Niño and a positive IOD event (La Niña and a negative IOD event) co-occur. The atmospheric circulation associated with these responses is discussed. Lower-frequency variability over southeastern Australia, however, including multiyear drought periods, seems to be more robustly related to Indian Ocean temperatures than Pacific conditions. The frequencies of both positive and negative IOD events are significantly different during periods of prolonged drought compared to extended periods of “normal” rainfall. In contrast, the frequency of ENSO events remains largely unchanged during prolonged dry and wet periods. For the Murray–Darling Basin, there appears to be a significant influence by La Niña and both positive and negative IOD events. In particular, La Niña plays a much more prominent role than for more southern regions, especially on interannual time scales and during prolonged wet periods. For prolonged dry (wet) periods, positive IOD events also occur in unusually high (low) numbers.
Global-Scale Comparison of MISR and MODIS Land Surface Albedos
Authors: Pinty Bernard , Taberner Malcolm , Haemmerle Vance R. , Paradise Susan R. , Vermote Eric , Verstraete Michel M. , Gobron Nadine , Widlowski Jean-Luc 
Published: October 2010

AbstractThe Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky surface albedos are compared with similar products generated on the basis of the Multiangle Imaging SpectroRadiometer (MISR) surface bidirectional reflectance factor (BRF) model parameters available for the year 2005. The analysis is achieved using global-scale statistics to characterize the broad patterns of these two independent albedo datasets. The results obtained in M. Taberner et al. have shown that robust statistics can be established and that both datasets are highly correlated. As a result, the slight but consistent biases and trends identified in this paper, derived from statistics obtained on a global basis, should be considered sufficiently reliable to merit further investigation. The present paper reports on the zonal- and seasonal-mean differences retrieved from the analysis of the MODIS and MISR surface albedo broadband products. The MISR − MODIS differences exhibit a systematic positive bias or offset in the range of 0.01–0.03 depending on the spectral domain of interest. Results obtained in the visible domain exhibit a well-marked and very consistent meridional trend featuring a “smile effect” such that the MISR − MODIS differences reach maxima at the highest latitudes in both hemispheres. The analysis of seasonal variations observed in MISR and MODIS albedo products reveals that, in the visible domain, the MODIS albedos generate weaker seasonal changes than MISR and that the differences increase poleward from the equatorial regions. A detailed investigation of MODIS and MISR aerosol optical depth retrievals suggests that this large-scale meridional trend is probably not caused by differences in the aerosol load estimated by each instrument. The scale and regularity of the meridional trend suggests that this may be due to the particular sampling regime of each instrument in the viewing azimuthal planes and/or approximations in the atmospheric correction processes. If this is the case, then either MODIS is underestimating, or MISR overestimating, the surface anisotropy or both.
The Analysis of Sea Surface Imagery for Whitecap Kinematics
Authors: Kleiss Jessica M. , Melville W. Kendall 
Published: October 2010

Abstract
Visible sea surface images are analyzed to determine the distribution of the average length of breaking crests per unit sea surface area per unit speed increment Λ(c). The Λ(c) distribution offers a scale-dependent description of wave breaking that is valuable for understanding wave energy dissipation, momentum flux from the wave field to the surface currents, and air–sea fluxes of gas and sea salt aerosols. Two independent processing techniques for determining Λ(c) from video images are implemented. In particular, the importance of the definition of the velocity of a breaking event is considered, as a single value, as a function of time, or as a function of space and time. The velocity can furthermore be defined as the full translational velocity or as the velocity normal to the breaking front. The Λ(c) distributions resulting from various definitions of velocity, sensitivity to thresholds, observational resolution, and the effect of surface currents and long wave orbital velocity are presented. The appropriateness and limitations of the comparison of the first moment of Λ(c) with the breaking rate are discussed. Two previous field observations of Λ(c) give qualitatively different results: Melville and Matusov found an exponential form for Λ(c), whereas Gemmrich et al. obtained a function that peaks at intermediate speeds and is up to an order of magnitude higher than that of Melville and Matusov. Both results can qualitatively be reproduced using the current dataset by employing the definitions of breaking velocity used in the previous studies. The authors argue that the current optimal interpretation of breaking speed resolves the breaking velocity as a function of both space and time and considers the velocity orthogonal to the breaking crest.
An Ensemble Ocean Data Assimilation System for Seasonal Prediction
Authors: Yin Yonghong , Alves Oscar , Oke Peter R. 
Published: October 2010

Abstract
A new ensemble ocean data assimilation system, developed for the Predictive Ocean Atmosphere Model for Australia (POAMA), is described. The new system is called PEODAS, the POAMA Ensemble Ocean Data Assimilation System. PEODAS is an approximate form of an ensemble Kalman filter system. For a given assimilation cycle, a central forecast is integrated, along with a small ensemble of forecasts that are forced with perturbed surface fluxes. The small ensemble is augmented with multiple small ensembles from previous assimilation cycles, yielding a larger ensemble that consists of perturbed forecasts from the last month. This larger ensemble is used to represent the system’s time-dependent background error covariance. At each assimilation cycle, a central analysis is computed utilizing the ensemble-based covariance. Each of the perturbed ensemble members are nudged toward the central analysis to control the ensemble spread and mean. The ensemble-based covariances generated by PEODAS potentially yield dynamically balanced analysis increments. The time dependence of the ensemble-based covariance yields spatial structures that change for different dynamical regimes, for example during El Niño and La Niña conditions. These differences are explored in terms of the dominant dynamics and the system’s errors. The performance of PEODAS during a 27-yr reanalysis is evaluated through a series of comparisons with assimilated and independent observations. When compared to its predecessor, POAMA version 1, and a simulation with no assimilation of subsurface observations, PEODAS demonstrates a quantitative improvement in skill. PEODAS will form the basis of Australia’s next operational seasonal prediction system.
Influence of the Madden–Julian Oscillation on Forecasts of Extreme Precipitation in the Contiguous United States
Authors: Jones Charles , Gottschalck Jon , Carvalho Leila M. V. , Higgins Wayne 
Published: October 2010

Abstract
Extreme precipitation events are among the most devastating weather phenomena since they are frequently accompanied by loss of life and property. This study uses reforecasts of the NCEP Climate Forecast System (CFS.v1) to evaluate the skill of nonprobabilistic and probabilistic forecasts of extreme precipitation in the contiguous United States (CONUS) during boreal winter for lead times up to two weeks.
The CFS model realistically simulates the spatial patterns of extreme precipitation events over the CONUS, although the magnitudes of the extremes in the model are much larger than in the observations. Heidke skill scores (HSS) for forecasts of extreme precipitation at the 75th and 90th percentiles showed that the CFS model has good skill at week 1 and modest skill at week 2. Forecast skill is usually higher when the Madden–Julian oscillation (MJO) is active and has enhanced convection occurring over the Western Hemisphere, Africa, and/or the western Indian Ocean than in quiescent periods. HSS greater than 0.1 extends to lead times of up to two weeks in these situations. Approximately 10%–30% of the CONUS has HSS greater than 0.1 at lead times of 1–14 days when the MJO is active.
Probabilistic forecasts for extreme precipitation events at the 75th percentile show improvements over climatology of 0%–40% at 1-day lead and 0%–5% at 7-day leads. The CFS has better skill in forecasting severe extremes (i.e., events exceeding the 90th percentile) at longer leads than moderate extremes (75th percentile). Improvements over climatology between 10% and 30% at leads of 3 days are observed over several areas across the CONUS—especially in California and in the Midwest.
Tropical Cyclone–like Vortices Detection in the NCEP 16-Day Ensemble System over the Western North Pacific in 2008: Application and Forecast Evaluation
Authors: Tsai Hsiao-Chung , Lu Kuo-Chen , Elsberry Russell L. , Lu Mong-Ming , Sui Chung-Hsiung 
Published: October 2010

Abstract
An automated technique has been developed for the detection and tracking of tropical cyclone–like vortices (TCLVs) in numerical weather prediction models, and especially for ensemble-based models. A TCLV is detected in the model grid when selected dynamic and thermodynamic fields meet specified criteria. A backward-and-forward extension from the mature stage of the track is utilized to complete the track. In addition, a fuzzy logic approach is utilized to calculate the TCLV fuzzy combined-likelihood value (TFCV) for representing the TCLV characteristics in the ensemble forecast outputs. The primary objective of the TCLV tracking and TFCV maps is for use as an evaluation tool for the operational forecasters. It is demonstrated that this algorithm efficiently extracts western North Pacific TCLV information from the vast amount of ensemble data from the NCEP Global Ensemble Forecast System (GEFS). The predictability of typhoon formation and activity during June–December 2008 is also evaluated. The TCLV track numbers and TFCV averages around the formation locations during the 0–96-h period are more skillful than for the 102–384-h forecasts. Compared to weak tropical cyclones (TCs; maximum intensity ≤ 50 kt), the storms that eventually become stronger TCs do have larger TFCVs. Depending on the specified domain size and the ensemble track numbers to define a forecast event, some skill is indicated in predicting the named TC activity. Although this evaluation with the 2008 typhoon season indicates some potential, an evaluation with a larger sample is necessary to statistically verify the reliability of the GEFS forecasts.
Beyond the reach of traditional analyses: using Rasch to evaluate the DASH in people with multiple sclerosis
Authors: Cano SJ , Barrett LE , Zajicek JP , Hobart JC 
Published: October 2010

Background: Few upper limb functioning patient rating scales have been used in multiple sclerosis (MS) research and none developed specifically for people with MS. Objectives: In this study, we examined the Disabilities of the Arm, Shoulder and Hand (DASH) to determine its utility as a useful, scientifically robust and clinically meaningful tool in MS. Methods: DASH data from 300 people with MS underwent two independent phases of psychometric analyses: (1) a traditional psychometric analysis (including data quality, scaling assumptions, reliability and validity); and (2) a Rasch analysis (including response option thresholds ordering, tests of fit, spread of item locations, residual correlations, and person separation index). Results: Overall, the traditional psychometric analysis supported the DASH as a reliable and valid measure of upper limb function in people with MS. However, several issues were raised by the Rasch analysis that questioned the validity of the DASH, including misfit in 13/30 items, disordered item response option thresholds for 9/30 items, and six pairs of items with high residual correlations (>0.60). Conclusion: Rasch analysis highlights areas for potential improvement for the use of the DASH. Our findings further support our previous arguments that traditional psychometric methods provide weak scale evaluations and can mislead clinicians as to the reliability and validity of outcome measures.
The effect of ambient air pollution on exhaled nitric oxide in the Children's Health Study
Authors: Berhane K. , Zhang Y. , Linn W.S. , Rappaport E.B. , Bastain T.M. , Salam M.T. , Islam T. , Lurmann F. , Gilliland F.D. 
Published: October 2010

We assessed the effect of daily variations in ambient air pollutants on exhaled nitric oxide fraction (FeNO) using data from a cohort of school children with large differences in air pollutant exposures from the Children's Health Study.Based on a cohort of 2,240 school children from 13 Southern Californian communities, cumulative lagged average regression models were fitted to determine the association betweenFeNOand ambient air pollution levels from central site monitors with lags of up to 30 days prior toFeNOtesting.Daily 24-h cumulative lagged averages of particles with a 50% cut-off aerodynamic diameter of 2.5 µm (PM2.5; over 1–8 days) and particles with a 50% cut-off aerodynamic diameter of 10 µm (PM10; over 1–7 days), as well as 10:00–18:00 h cumulative lagged average of O3(over 1–23 days) were significantly associated with 17.42% (p<0.01), 9.25% (p<0.05) and 14.25% (p<0.01) higherFeNOlevels over the interquartile range of 7.5 μg·m−3, 12.97 μg·m−3and 15.42 ppb, respectively. The effects of PM2.5, PM10and O3were higher in the warm season. The particulate matter effects were robust to adjustments for effects of O3and temperature and did not vary by asthma or allergy status.In summary, short-term increases in PM2.5, PM10and O3were associated with airway inflammation independent of asthma and allergy status, with PM10effects significantly higher in the warm season.