bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Influence of Cloud and Surface Properties on the Arctic Ocean Shortwave Radiation Budget in Coupled Models*
Authors: Gorodetskaya Irina V. , Tremblay L-Bruno , Liepert Beate , Cane Mark A. , Cullather Richard I. 
Published: March 2008

Abstract
The impact of Arctic sea ice concentrations, surface albedo, cloud fraction, and cloud ice and liquid water paths on the surface shortwave (SW) radiation budget is analyzed in the twentieth-century simulations of three coupled models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The models are the Goddard Institute for Space Studies Model E-R (GISS-ER), the Met Office Third Hadley Centre Coupled Ocean–Atmosphere GCM (UKMO HadCM3), and the National Center for Atmosphere Research Community Climate System Model, version 3 (NCAR CCSM3). In agreement with observations, the models all have high Arctic mean cloud fractions in summer; however, large differences are found in the cloud ice and liquid water contents. The simulated Arctic clouds of CCSM3 have the highest liquid water content, greatly exceeding the values observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. Both GISS-ER and HadCM3 lack liquid water and have excessive ice amounts in Arctic clouds compared to SHEBA observations. In CCSM3, the high surface albedo and strong cloud SW radiative forcing both significantly decrease the amount of SW radiation absorbed by the Arctic Ocean surface during the summer. In the GISS-ER and HadCM3 models, the surface and cloud effects compensate one another: GISS-ER has both a higher summer surface albedo and a larger surface incoming SW flux when compared to HadCM3. Because of the differences in the models’ cloud and surface properties, the Arctic Ocean surface gains about 20% and 40% more solar energy during the melt period in the GISS-ER and HadCM3 models, respectively, compared to CCSM3.
In twenty-first-century climate runs, discrepancies in the surface net SW flux partly explain the range in the models’ sea ice area changes. Substantial decrease in sea ice area simulated during the twenty-first century in CCSM3 is associated with a large drop in surface albedo that is only partly compensated by increased cloud SW forcing. In this model, an initially high cloud liquid water content reduces the effect of the increase in cloud fraction and cloud liquid water on the cloud optical thickness, limiting the ability of clouds to compensate for the large surface albedo decrease. In HadCM3 and GISS-ER, the compensation of the surface albedo and cloud SW forcing results in negligible changes in the net SW flux and is one of the factors explaining moderate future sea ice area trends. Thus, model representations of cloud properties for today’s climate determine the ability of clouds to compensate for the effect of surface albedo decrease on the future shortwave radiative budget of the Arctic Ocean and, as a consequence, the sea ice mass balance.
Droughts and Persistent Wet Spells over the United States and Mexico
Authors: Mo Kingtse C. , Schemm Jae E. 
Published: March 2008

Abstract
Droughts and persistent wet spells over the United States and northwest Mexico have preferred regions of occurrence and persistence. Wet or dry conditions that persist more than 1 yr tend to occur over the interior United States west of 90°–95°W and northwest Mexico. In contrast, events over the eastern United States are less likely to occur and often last less than 6 months.
The long persistent drought and wet spells are often modulated by low-frequency sea surface temperature anomalies (SSTAs). The persistent dry or wet conditions over northwest Mexico and the Southwest are associated with decadal variability of SSTAs over the North Pacific. Persistent events over the northwestern mountains are associated with two decadal SSTA modes. One mode has loadings over three southern oceans and another one is an El Niño–Southern Oscillation (ENSO) like decadal mode. Wet and dry conditions over the Pacific Northwest and the Great Plains are often associated with ENSO.
The seasonal cycle of precipitation over the central-eastern United States, the East Coast, and the Ohio Valley is weak. Drought and wet spells over these regions are less persistent because the ENSO events have opposite impacts on precipitation for summer and winter.
Shifts in the Statistics of Daily Rainfall in South America Conditional on ENSO Phase
Authors: Ropelewski C. F. , Bell M. A. 
Published: March 2008

Abstract
There are several well-documented studies showing the shifts in seasonal mean rainfall and temperature conditional on El Niño–Southern Oscillation (ENSO) phase. Here the shifts in the seasonal histograms of daily rainfall over South America conditional on ENSO phase are examined. The authors are motivated to analyze daily rainfall statistics over seasons by the demands for information on the shorter temporal scales voiced by users of climate data. In the first stage of the analysis the Kolmogorov–Smirnov (K-S) test is used, comparing El Niño to La Niña histograms of daily station data, to identify regions where there are significant shifts in the histograms. The K-S statistic analyses of daily station data are then compared to the same analyses performed on existing publicly available gridded station datasets. The degree to which the station and gridded data agree in showing geographical regions of significance provides evidence that the gridded fields might provide guidance on the nature of the ENSO signal where station data are not available. Further, the analysis of the gridded datasets can be used to motivate and guide efforts to obtain more complete daily data where the gridded datasets suggest an ENSO signal. As an example a detailed comparison of one station in southern Brazil and its nearest neighbors in the gridded data are presented, suggesting that, despite biases, the gridded fields are generally consistent with the station data where both are available.
For many regions of the world neither daily station data nor daily gridded datasets are available for analysis. Thus despite documented and well-known regional biases in the precipitation fields available in the NCEP–NCAR reanalysis the extent to which shifts in the daily statistics of the NCEP–NCAR reanalysis precipitation are consistent with station and gridded station analyses is also examined. The preliminary work described here suggests that while the reanalysis does not ideally replicate the gridded station results the reanalysis may be useful as a tool for indicating candidate regions for further analysis with station or gridded data.
Volcanic Eruptions, Large-Scale Modes in the Northern Hemisphere, and the El Niño–Southern Oscillation
Authors: Christiansen Bo 
Published: March 2008

Abstract
The author analyzes the impact of 13 major stratospheric aerosol producing volcanic eruptions since 1870 on the large-scale variability modes of sea level pressure in the Northern Hemisphere winter. The paper focuses on the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO) to address the question about the physical nature of these modes. The hypothesis that the phase of the El Niño–Southern Oscillation (ENSO) may control the geographical extent of the dominant mode in the Northern Hemisphere is also investigated, as well as the related possibility that the impact of the eruptions may be different according to the phase of ENSO.
The author finds that both the AO and the NAO are excited in the first winter after the eruptions with statistical significance at the 95% level. Both the signal and the significance are larger for the NAO than for the AO. The excitation of the AO and the NAO is connected with the excitation of a secondary mode, which resembles an augmented Pacific–North American pattern. This mode has opposite polarity in the Atlantic and the Pacific and interferes negatively with the AO in the Pacific and positively in the Atlantic in the first winter after the eruptions, giving the superposition a strong NAO resemblance.
Some evidence is found that the correlations between the Atlantic and the Pacific are stronger in the negative ENSO phase than in the positive phase, although this difference is not statistically significant when all data since 1870 are considered. The author does not find any evidence that the impact of the volcanic eruptions is more hemispheric in the negative than in the positive ENSO phase.
Regional Model Simulations of the Bodélé Low-Level Jet of Northern Chad during the Bodélé Dust Experiment (BoDEx 2005)
Authors: Todd Martin C. , Washington Richard , Raghavan Srivatsan , Lizcano Gil , Knippertz Peter 
Published: March 2008

Abstract
The low-level jet (LLJ) over the Bodélé depression in northern Chad is a newly identified feature. Strong LLJ events are responsible for the emission of large quantities of mineral dust from the depression, the world’s largest single dust source, and its subsequent transport to West Africa, the tropical Atlantic, and beyond. Accurate simulation of this key dust-generating atmospheric feature is, therefore, an important requirement for dust models. The objectives of the present study are (i) to evaluate the ability of regional climate models (RCMs) and global analyses/reanalyses to represent this feature, and (ii) to determine the driving mechanisms of the LLJ and its strong diurnal cycle. Observational data obtained during the Bodélé Dust Experiment (BoDEx 2005) are utilized for comparison. When suitably configured, the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) RCM can represent very accurately many of the key features of the jet including the structure, diurnal cycle, and day-to-day variability. Surface winds are also well reproduced, including the peak winds, which activate dust emission. Model fidelity is, however, strongly dependent on the boundary layer parameterization scheme, surface roughness, and vertical resolution in the lowest layers. A model horizontal resolution of a few tens of kilometers is sufficient to resolve most of the key features of the LLJ, while in global analyses/reanalyses many features of the LLJ are not adequately represented. Idealized RCM simulations indicate that under strong synoptic forcing the surrounding orography of the Tibesti and Ennedi Mountains acts to focus the LLJ onto the Bodélé and to accelerate the jet by ∼40%. From the RCM experiments it is diagnosed that the pronounced diurnal cycle of the Bodélé LLJ is largely a result of varying eddy viscosity, with elevated heating/cooling over the Tibesti Mountains to the north as a second-order contribution.
The Summer Cyclone Maximum over the Central Arctic Ocean
Authors: Serreze Mark C. , Barrett Andrew P. 
Published: March 2008

Abstract
A fascinating feature of the northern high-latitude circulation is a prominent summer maximum in cyclone activity over the Arctic Ocean, centered near the North Pole in the long-term mean. This pattern is associated with the influx of lows generated over the Eurasian continent and cyclogenesis over the Arctic Ocean itself. Its seasonal onset is linked to the following: an eastward shift in the Urals trough, migration of the 500-hPa vortex core to near the pole, and development of a separate region of high-latitude baroclinicity. The latter two features are consistent with differential atmospheric heating between the Arctic Ocean and snow-free land. Variability in the strength of the cyclone pattern can be broadly linked to the phase of the summer northern annular mode. When the cyclone pattern is well developed, the 500-hPa vortex is especially strong and symmetric about the pole, with negative sea level pressure (SLP) anomalies over the pole and positive anomalies over middle latitudes. Net precipitation tends to be anomalously positive over the Arctic Ocean. When poorly developed, the opposite holds.
Spatial Variability of Shortwave Irradiance for Snowmelt in Forests
Authors: Pomeroy John , Ellis Chad , Rowlands Aled , Essery Richard , Hardy Janet , Link Tim , Marks Danny , Sicart Jean Emmanuel 
Published: March 2008

Abstract
The spatial variation of melt energy can influence snow cover depletion rates and in turn be influenced by the spatial variability of shortwave irradiance to snow. The spatial variability of shortwave irradiance during melt under uniform and discontinuous evergreen canopies at a U.S. Rocky Mountains site was measured, analyzed, and then compared to observations from mountain and boreal forests in Canada. All observations used arrays of pyranometers randomly spaced under evergreen canopies of varying structure and latitude. The spatial variability of irradiance for both overcast and clear conditions declined dramatically, as the sample averaging interval increased from minutes to 1 day. At daily averaging intervals, there was little influence of cloudiness on the variability of subcanopy irradiance; instead, it was dominated by stand structure. The spatial variability of irradiance on daily intervals was higher for the discontinuous canopies, but it did not scale reliably with canopy sky view. The spatial variation in irradiance resulted in a coefficient of variation of melt energy of 0.23 for the set of U.S. and Canadian stands. This variability in melt energy smoothed the snow-covered area depletion curve in a distributed melt simulation, thereby lengthening the duration of melt by 20%. This is consistent with observed natural snow cover depletion curves and shows that variations in melt energy and snow accumulation can influence snow-covered area depletion under forest canopies.
Mesocell Study Area Snow Distributions for the Cold Land Processes Experiment (CLPX)
Authors: Liston Glen E. , Hiemstra Christopher A. , Elder Kelly , Cline Donald W. 
Published: March 2008

AbstractThe Cold Land Processes Experiment (CLPX) had a goal of describing snow-related features over a wide range of spatial and temporal scales. This required linking disparate snow tools and datasets into one coherent, integrated package. Simulating realistic high-resolution snow distributions and features requires a snow-evolution modeling system (SnowModel) that can distribute meteorological forcings, simulate snowpack accumulation and ablation processes, and assimilate snow-related observations. A SnowModel was developed and used to simulate winter snow accumulation across three 30 km × 30 km domains, enveloping the CLPX mesocell study areas (MSAs) in Colorado. The three MSAs have distinct topography, vegetation, meteorological, and snow characteristics. Simulations were performed using a 30-m grid increment and spanned the snow accumulation season (1 October 2002–1 April 2003). Meteorological forcing was provided by 27 meteorological stations and 75 atmospheric analyses grid points, distributed using a meteorological model (MicroMet). The simulations included a data assimilation model (SnowAssim) that adjusted simulated snow water equivalent (SWE) toward ground-based and airborne SWE observations. The observations consisted of SWE over three 1 km × 1 km intensive study areas (ISAs) for each MSA and a collection of 117 airborne gamma observations, each integrating area 10 km long by 300 m wide. Simulated SWE distributions displayed considerably more spatial heterogeneity than the observations alone, and the simulated distribution patterns closely fit the current understanding of snow evolution processes and observed snow depths. This is the result of the MicroMet/SnowModel’s relatively finescale representations of orographic precipitation, elevation-dependant snowmelt, wind redistribution, and snow–vegetation interactions.
A Simple Data Assimilation System for Complex Snow Distributions (SnowAssim)
Authors: Liston Glen E. , Hiemstra Christopher A. 
Published: March 2008

Abstract
A methodology for assimilating ground-based and remotely sensed snow data within a snow-evolution modeling system (SnowModel) is presented. The data assimilation scheme (SnowAssim) is consistent with optimal interpolation approaches in which the differences between the observed and modeled snow values are used to constrain modeled outputs. The calculated corrections are applied retroactively to create improved fields prior to the assimilated observations. Thus, one of the values of this scheme is the improved simulation of snow-related distributions throughout the entire snow season, even when observations are only available late in the accumulation and/or ablation periods. Because of this, the technique is particularly applicable to reanalysis applications. The methodology includes the ability to stratify the assimilation into regions where either the observations and/or model has unique error properties, such as the differences between forested and nonforested snow environments. The methodologies are introduced using synthetic data and a simple simulation domain. In addition, the model is applied over NASA’s Cold Land Processes Experiment (CLPX), Rabbit Ears Pass, Colorado, observation domain. Simulations using the data assimilation scheme were found to improve the modeled snow water equivalent (SWE) distributions, and simulated SWE displayed considerably more realistic spatial heterogeneity than that provided by the observations alone.
Interannual Consistency in Fractal Snow Depth Patterns at Two Colorado Mountain Sites
Authors: Deems Jeffrey S. , Fassnacht Steven R. , Elder Kelly J. 
Published: March 2008

Abstract
Fractal dimensions derived from log–log variograms are useful for characterizing spatial structure and scaling behavior in snow depth distributions. This study examines the temporal consistency of snow depth scaling features at two sites using snow depth distributions derived from lidar datasets collected in 2003 and 2005. The temporal snow accumulation patterns in these two years were substantially different, but both years represent nearly average 1 April accumulation depths for these sites, with consistent statistical distributions. Two distinct fractal regions are observed in each log–log variogram, separated by a scale break, which indicates a length scale at which a substantial change in the driving processes exists. The lag distance of the scale break is 15 m at the Walton Creek site and 40 m at the Alpine site. The datasets show consistent fractal dimensions and scale break distances between the two years, suggesting that the scaling features observed in spatial snow depth distributions are largely determined by physiography and vegetation characteristics and are relatively insensitive to annual variations in snowfall. Directional variograms also show consistent patterns between years, with smaller fractal dimensions aligned with the dominant wind direction at each site.
The Interactions of Gravity Waves with Mesocyclones: Preliminary Observations and Theory
Authors: Coleman Timothy A. , Knupp Kevin R. 
Published: March 2008

Abstract
Apparent interactions between ducted gravity waves and preexisting mesocyclones are investigated. Preliminary analyses of Weather Surveillance Radar-1988 Doppler (WSR-88D) observations from several cases reveal that the intersection of fine lines, whose propagation speed is consistent with that of gravity waves, and existing mesocyclones leads to an increase in the rotational velocity of the mesocyclone. Utilizing simplified ducted wave kinematics and the vorticity equation, changes in vorticity associated with convergence–divergence and perturbation wind shear within the gravity wave are examined. Convergence ahead of wave ridges may be significant, causing mesocyclone intensification through vorticity stretching. It will also be shown that a wave may significantly change the vertical wind shear and streamwise vorticity in storm inflow. A simple one-dimensional model is presented, which shows that vorticity decreases temporarily ahead of the wave ridge, then increases rapidly behind the ridge as positive tilting and stretching act together. The mesocyclone vorticity reaches a peak just ahead of the wave ridge, then begins to rapidly decrease behind the ridge. Model results compared very well to actual measurements in a sample case in which a mesocyclone interacted with two gravity waves of different amplitudes.
Assessing the Capability of a Regional-Scale Weather Model to Simulate Extreme Precipitation Patterns and Flooding in Central Texas
Authors: Lowrey Marla R. Knebl , Yang Zong-Liang 
Published: March 2008

Abstract
A regional-scale weather model is used to determine the potential for flood forecasting based on model-predicted rainfall. Extreme precipitation and flooding events are a significant concern in central Texas, due to both the high occurrence and severity of flooding in the area. However, many current regional prediction models do not provide sufficient accuracy at the watershed scale necessary for flood mitigation efforts. The Weather Research and Forecasting (WRF) model, created with the purpose of improving upon the current fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), is specifically designed for regional grid spacings of 1–10 km. Previous research by the authors resulted in the development of a regional-scale prediction system over the San Antonio River basin, using a geographic information system (GIS) database, a hydrologic model, and a hydraulic model. Observed precipitation drives the prediction system; the authors hypothesize that the WRF model has the potential to predict flooding, at a lead time of several days, with a level of accuracy near that of observed precipitation. Causes of model error are also investigated, to determine the relative errors caused by model physics, initialization interval, buffer zone and domain size, and small-amplitude random errors. Results show that the Betts–Miller–Janjić cumulus and Lin et al. microphysics schemes, 48-h initialization interval, and two-domain configuration covering minimal ocean and having a parent-to-nest area ratio of greater than 10 best simulates a recent (July 2002) large storm event over the San Antonio River basin. This particular storm was selected because it produced extreme rainfall volumes and intensities, and also because its meteorological characteristics are typical of central Texas storm events. Location errors in rainfall are most significant because of their typically nonlinear patterns (increasing location error does not linearly modify streamflow output). Errors in intensity and timing show a more predictable (linear) watershed response that may be useful in the estimation of streamflow ranges for flood forecasting.
Etiological Relationships in Atopy: A Review of Twin Studies
Authors: Thomsen Simon Francis , Kyvik Kirsten Ohm , Backer Vibeke 
Published: March 2008

AbstractThe genetics of asthma and atopy has been studied frequently in twin populations from various parts of the world. However, emphasis has been put on univariate analysis of questionnaire data, whereas clinical and intermediate traits only sporadically have been studied, especially in multivariate settings. This review focuses on multivariate twin studies of atopy and related traits. We conclude that the genetic liability to most atopic traits is significantly correlated but that trait-specific genes also play a role. Previous studies have estimated the genetic correlation between upper and lower respiratory allergic symptoms, that is, asthma and hay fever, to be between .47 and .95. Furthermore, atopic traits share a portion of their genetic determinants with other complex disorders like obesity and behavioral traits. A correlation of about .3 and .34 has been reported between genes associated with asthma and obesity, and between genes associated with asthma and depression, respectively. We emphasize that multivariate methods applied to twin studies, especially when genetic marker information is available, provide a valuable framework within which complex etiological mechanisms underlying atopy can be disentangled.