Perceptual Biases in Relation to Paranormal and Conspiracy Beliefs

PubMed Central

van Elk, Michiel

2015-01-01

Previous studies have shown that one’s prior beliefs have a strong effect on perceptual decision-making and attentional processing. The present study extends these findings by investigating how individual differences in paranormal and conspiracy beliefs are related to perceptual and attentional biases. Two field studies were conducted in which visitors of a paranormal conducted a perceptual decision making task (i.e. the face / house categorization task; Experiment 1) or a visual attention task (i.e. the global / local processing task; Experiment 2). In the first experiment it was found that skeptics compared to believers more often incorrectly categorized ambiguous face stimuli as representing a house, indicating that disbelief rather than belief in the paranormal is driving the bias observed for the categorization of ambiguous stimuli. In the second experiment, it was found that skeptics showed a classical ‘global-to-local’ interference effect, whereas believers in conspiracy theories were characterized by a stronger ‘local-to-global interference effect’. The present study shows that individual differences in paranormal and conspiracy beliefs are associated with perceptual and attentional biases, thereby extending the growing body of work in this field indicating effects of cultural learning on basic perceptual processes. PMID:26114604

Perceptual Biases in Relation to Paranormal and Conspiracy Beliefs.

PubMed

van Elk, Michiel

2015-01-01

Previous studies have shown that one's prior beliefs have a strong effect on perceptual decision-making and attentional processing. The present study extends these findings by investigating how individual differences in paranormal and conspiracy beliefs are related to perceptual and attentional biases. Two field studies were conducted in which visitors of a paranormal conducted a perceptual decision making task (i.e. the face/house categorization task; Experiment 1) or a visual attention task (i.e. the global/local processing task; Experiment 2). In the first experiment it was found that skeptics compared to believers more often incorrectly categorized ambiguous face stimuli as representing a house, indicating that disbelief rather than belief in the paranormal is driving the bias observed for the categorization of ambiguous stimuli. In the second experiment, it was found that skeptics showed a classical 'global-to-local' interference effect, whereas believers in conspiracy theories were characterized by a stronger 'local-to-global interference effect'. The present study shows that individual differences in paranormal and conspiracy beliefs are associated with perceptual and attentional biases, thereby extending the growing body of work in this field indicating effects of cultural learning on basic perceptual processes.

Systems Factorial Technology provides new insights on global-local information processing in autism spectrum disorders.

PubMed

Johnson, Shannon A; Blaha, Leslie M; Houpt, Joseph W; Townsend, James T

2010-02-01

Previous studies of global-local processing in autism spectrum disorders (ASDs) have indicated mixed findings, with some evidence of a local processing bias, or preference for detail-level information, and other results suggesting typical global advantage, or preference for the whole or gestalt. Findings resulting from this paradigm have been used to argue for or against a detail focused processing bias in ASDs, and thus have important theoretical implications. We applied Systems Factorial Technology, and the associated Double Factorial Paradigm (both defined in the text), to examine information processing characteristics during a divided attention global-local task in high-functioning individuals with an ASD and typically developing controls. Group data revealed global advantage for both groups, contrary to some current theories of ASDs. Information processing models applied to each participant revealed that task performance, although showing no differences at the group level, was supported by different cognitive mechanisms in ASD participants compared to controls. All control participants demonstrated inhibitory parallel processing and the majority demonstrated a minimum-time stopping rule. In contrast, ASD participants showed exhaustive parallel processing with mild facilitatory interactions between global and local information. Thus our results indicate fundamental differences in the stopping rules and channel dependencies in individuals with an ASD.

Children inhibit global information when the forest is dense and local information when the forest is sparse.

PubMed

Krakowski, Claire-Sara; Borst, Grégoire; Vidal, Julie; Houdé, Olivier; Poirel, Nicolas

2018-09-01

Visual environments are composed of global shapes and local details that compete for attentional resources. In adults, the global level is processed more rapidly than the local level, and global information must be inhibited in order to process local information when the local information and global information are in conflict. Compared with adults, children present less of a bias toward global visual information and appear to be more sensitive to the density of local elements that constitute the global level. The current study aimed, for the first time, to investigate the key role of inhibition during global/local processing in children. By including two different conditions of global saliency during a negative priming procedure, the results showed that when the global level was salient (dense hierarchical figures), 7-year-old children and adults needed to inhibit the global level to process the local information. However, when the global level was less salient (sparse hierarchical figures), only children needed to inhibit the local level to process the global information. These results confirm a weaker global bias and the greater impact of saliency in children than in adults. Moreover, the results indicate that, regardless of age, inhibition of the most salient hierarchical level is systematically required to select the less salient but more relevant level. These findings have important implications for future research in this area. Copyright © 2018 Elsevier Inc. All rights reserved.

Zooming into creativity: individual differences in attentional global-local biases are linked to creative thinking.

PubMed

Zmigrod, Sharon; Zmigrod, Leor; Hommel, Bernhard

2015-01-01

While recent studies have investigated how processes underlying human creativity are affected by particular visual-attentional states, we tested the impact of more stable attention-related preferences. These were assessed by means of Navon's global-local task, in which participants respond to the global or local features of large letters constructed from smaller letters. Three standard measures were derived from this task: the sizes of the global precedence effect, the global interference effect (i.e., the impact of incongruent letters at the global level on local processing), and the local interference effect (i.e., the impact of incongruent letters at the local level on global processing). These measures were correlated with performance in a convergent-thinking creativity task (the Remote Associates Task), a divergent-thinking creativity task (the Alternate Uses Task), and a measure of fluid intelligence (Raven's matrices). Flexibility in divergent thinking was predicted by the local interference effect while convergent thinking was predicted by intelligence only. We conclude that a stronger attentional bias to visual information about the "bigger picture" promotes cognitive flexibility in searching for multiple solutions.

Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms

NASA Technical Reports Server (NTRS)

Komjathy, Attila; Sparks, Lawrence; Wilson, Brian D.; Mannucci, Anthony J.

2005-01-01

To take advantage of the vast amount of GPS data, researchers use a number of techniques to estimate satellite and receiver interfrequency biases and the total electron content (TEC) of the ionosphere. Most techniques estimate vertical ionospheric structure and, simultaneously, hardware-related biases treated as nuisance parameters. These methods often are limited to 200 GPS receivers and use a sequential least squares or Kalman filter approach. The biases are later removed from the measurements to obtain unbiased TEC. In our approach to calibrating GPS receiver and transmitter interfrequency biases we take advantage of all available GPS receivers using a new processing algorithm based on the Global Ionospheric Mapping (GIM) software developed at the Jet Propulsion Laboratory. This new capability is designed to estimate receiver biases for all stations. We solve for the instrumental biases by modeling the ionospheric delay and removing it from the observation equation using precomputed GIM maps. The precomputed GIM maps rely on 200 globally distributed GPS receivers to establish the ''background'' used to model the ionosphere at the remaining 800 GPS sites.

Global/local processing style: Explaining the relationship between trait anxiety and binge eating.

PubMed

Becker, Kendra R; Plessow, Franziska; Coniglio, Kathryn A; Tabri, Nassim; Franko, Debra L; Zayas, Lazaro V; Germine, Laura; Thomas, Jennifer J; Eddy, Kamryn T

2017-11-01

Anxiety is a risk factor for disordered eating, but the mechanisms by which anxiety promotes disordered eating are poorly understood. One possibility is local versus global cognitive processing style, defined as a relative tendency to attend to details at the expense of the "big picture." Anxiety may narrow attention, in turn, enhancing local and/or compromising global processing. We examined relationships between global/local processing style, anxiety, and disordered eating behaviors in a transdiagnostic outpatient clinical sample. We hypothesized that local (vs. global) processing bias would mediate the relationship between anxiety and disordered eating behaviors. Ninety-three participants completed the eating disorder examination-questionnaire (EDE-Q), State-Trait Anxiety Inventory (STAI)-trait subscale, and the Navon task (a test of processing style in which large letters are composed of smaller letters both congruent and incongruent with the large letter). The sample was predominantly female (95%) with a mean age of 27.4 years (SD = 12.1 years). Binge eating, but not fasting, purging, or excessive exercise, was correlated with lower levels of global processing style. There was a significant indirect effect between anxiety and binge eating via reduced global level global/local processing. In individuals with disordered eating, being more generally anxious may encourage a detailed-oriented bias, preventing individuals from maintaining the bigger picture and making them more likely to engage in maladaptive behaviors (e.g., binge eating). © 2017 Wiley Periodicals, Inc.

Global/local processing style: Explaining the relationship between trait anxiety and binge eating

PubMed Central

Becker, Kendra R.; Plessow, Franziska; Coniglio, Kathryn A.; Tabri, Nassim; Franko, Debra L; Zayas, Lazaro V.; Germine, Laura; Thomas, Jennifer J.; Eddy, Kamryn T.

2018-01-01

Objective Anxiety is a risk factor for disordered eating, but the mechanisms by which anxiety promotes disordered eating are poorly understood. One possibility is local versus global cognitive processing style, defined as a relative tendency to attend to details at the expense of the “big picture.” Anxiety may narrow attention, in turn, enhancing local and/or compromising global processing. We examined relationships between global/local processing style, anxiety, and disordered eating behaviors in a transdiagnostic outpatient clinical sample. We hypothesized that local (vs. global) processing bias would mediate the relationship between anxiety and disordered eating behaviors. Method Ninety-three participants completed the eating disorder examination—questionnaire (EDE-Q), State-Trait Anxiety Inventory (STAI)—trait subscale, and the Navon task (a test of processing style in which large letters are composed of smaller letters both congruent and incongruent with the large letter). The sample was predominantly female (95%) with a mean age of 27.4 years (SD = 12.1 years). Results Binge eating, but not fasting, purging, or excessive exercise, was correlated with lower levels of global processing style. There was a significant indirect effect between anxiety and binge eating via reduced global level global/local processing. Discussion In individuals with disordered eating, being more generally anxious may encourage a detailed-oriented bias, preventing individuals from maintaining the bigger picture and making them more likely to engage in maladaptive behaviors (e.g., binge eating). PMID:28963792

Weight bias internalization, core self-evaluation, and health in overweight and obese persons.

PubMed

Hilbert, Anja; Braehler, Elmar; Haeuser, Winfried; Zenger, Markus

2014-01-01

Weight bias has strong associations with psychopathology in overweight and obese individuals. However, self-evaluative processes, as conceptualized in the process model of self-stigma, and implications for other health-related outcomes, remain to be clarified. In a representative general population sample of N = 1158 overweight and obese individuals, the impact of core self-evaluation as a mediator between weight bias internalization and mental and global health outcomes as well as between weight bias internalization and health care utilization, was examined using structural equation modeling. In overweight and obese individuals, greater weight bias internalization predicted lower core self-evaluation, which in turn predicted greater depression and anxiety, lower global health, and greater health care utilization. These mediational associations were largely stable in subsample analyses and after controlling for sociodemographic variables. The results show that overweight and obese individuals with internalized weight bias are at risk for impaired health, especially if they experience low core self-evaluation, making them a group with which to target for interventions to reduce self-stigma. Weight bias internalization did not represent a barrier to health care utilization, but predicted greater health care utilization in association with greater health impairments. Copyright © 2013 The Obesity Society.

Cross cultural differences in unconscious knowledge.

PubMed

Kiyokawa, Sachiko; Dienes, Zoltán; Tanaka, Daisuke; Yamada, Ayumi; Crowe, Louise

2012-07-01

Previous studies have indicated cross cultural differences in conscious processes, such that Asians have a global preference and Westerners a more analytical one. We investigated whether these biases also apply to unconscious knowledge. In Experiment 1, Japanese and UK participants memorized strings of large (global) letters made out of small (local) letters. The strings constituted one sequence of letters at a global level and a different sequence at a local level. Implicit learning occurred at the global and not the local level for the Japanese but equally at both levels for the English. In Experiment 2, the Japanese preference for global over local processing persisted even when structure existed only at the local but not global level. In Experiment 3, Japanese and UK participants were asked to attend to just one of the levels, global or local. Now the cultural groups performed similarly, indicating that the bias largely reflects preference rather than ability (although the data left room for residual ability differences). In Experiment 4, the greater global advantage of Japanese rather English was confirmed for strings made of Japanese kana rather than Roman letters. That is, the cultural difference is not due to familiarity of the sequence elements. In sum, we show for the first time that cultural biases strongly affect the type of unconscious knowledge people acquire. Copyright © 2012 Elsevier B.V. All rights reserved.

Unabated global surface temperature warming: evaluating the evidence

NASA Astrophysics Data System (ADS)

Karl, T. R.; Arguez, A.

2015-12-01

New insights related to time-dependent bias corrections in global surface temperatures have led to higher rates of warming over the past few decades than previously reported in the IPCC Fifth Assessment Report (2014). Record high global temperatures in the past few years have also contributed to larger trends. The combination of these factors and new analyses of the rate of temperature change show unabated global warming since at least the mid-Twentieth Century. New time-dependent bias corrections account for: (1) differences in temperatures measured from ships and drifting buoys; (2) improved corrections to ship measured temperatures; and (3) the larger rates of warming in polar regions (particularly the Arctic). Since 1951, the period over which IPCC (2014) attributes over half of the observed global warming to human causes, it is shown that there has been a remarkably robust and sustained warming, punctuated with inter-annual and decadal variability. This finding is confirmed through simple trend analysis and Empirical Mode Decomposition (EMD). Trend analysis however, especially for decadal trends, is sensitive to selection bias of beginning and ending dates. EMD has no selection bias. Additionally, it can highlight both short- and long-term processes affecting the global temperature times series since it addresses both non-linear and non-stationary processes. For the new NOAA global temperature data set, our analyses do not support the notion of a hiatus or slowing of long-term global warming. However, sub-decadal periods of little (or no warming) and rapid warming can also be found, clearly showing the impact of inter-annual and decadal variability that previously has been attributed to both natural and human-induced non-greenhouse forcings.

Improved simulation of tropospheric ozone by a global-multi-regional two-way coupling model system

NASA Astrophysics Data System (ADS)

Yan, Yingying; Lin, Jintai; Chen, Jinxuan; Hu, Lu

2016-02-01

Small-scale nonlinear chemical and physical processes over pollution source regions affect the tropospheric ozone (O3), but these processes are not captured by current global chemical transport models (CTMs) and chemistry-climate models that are limited by coarse horizontal resolutions (100-500 km, typically 200 km). These models tend to contain large (and mostly positive) tropospheric O3 biases in the Northern Hemisphere. Here we use the recently built two-way coupling system of the GEOS-Chem CTM to simulate the regional and global tropospheric O3 in 2009. The system couples the global model (at 2.5° long. × 2° lat.) and its three nested models (at 0.667° long. × 0.5° lat.) covering Asia, North America and Europe, respectively. Specifically, the nested models take lateral boundary conditions (LBCs) from the global model, better capture small-scale processes and feed back to modify the global model simulation within the nested domains, with a subsequent effect on their LBCs. Compared to the global model alone, the two-way coupled system better simulates the tropospheric O3 both within and outside the nested domains, as found by evaluation against a suite of ground (1420 sites from the World Data Centre for Greenhouse Gases (WDCGG), the United States National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory Global Monitoring Division (GMD), the Chemical Coordination Centre of European Monitoring and Evaluation Programme (EMEP), and the United States Environmental Protection Agency Air Quality System (AQS)), aircraft (the High-performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) and Measurement of Ozone and Water Vapor by Airbus In- Service Aircraft (MOZAIC)) and satellite measurements (two Ozone Monitoring Instrument (OMI) products). The two-way coupled simulation enhances the correlation in day-to-day variation of afternoon mean surface O3 with the ground measurements from 0.53 to 0.68, and it reduces the mean model bias from 10.8 to 6.7 ppb. Regionally, the coupled system reduces the bias by 4.6 ppb over Europe, 3.9 ppb over North America and 3.1 ppb over other regions. The two-way coupling brings O3 vertical profiles much closer to the HIPPO (for remote areas) and MOZAIC (for polluted regions) data, reducing the tropospheric (0-9 km) mean bias by 3-10 ppb at most MOZAIC sites and by 5.3 ppb for HIPPO profiles. The two-way coupled simulation also reduces the global tropospheric column ozone by 3.0 DU (9.5 %, annual mean), bringing them closer to the OMI data in all seasons. Additionally, the two-way coupled simulation also reduces the global tropospheric mean hydroxyl radical by 5 % with improved estimates of methyl chloroform and methane lifetimes. Simulation improvements are more significant in the Northern Hemisphere, and are mainly driven by improved representation of spatial inhomogeneity in chemistry/emissions. Within the nested domains, the two-way coupled simulation reduces surface ozone biases relative to typical GEOS-Chem one-way nested simulations, due to much improved LBCs. The bias reduction is 1-7 times the bias reduction from the global to the one-way nested simulation. Improving model representations of small-scale processes is important for understanding the global and regional tropospheric chemistry.

Grasp posture alters visual processing biases near the hands

PubMed Central

Thomas, Laura E.

2015-01-01

Observers experience biases in visual processing for objects within easy reach of their hands that may assist them in evaluating items that are candidates for action. I investigated the hypothesis that hand postures affording different types of actions differentially bias vision. Across three experiments, participants performed global motion detection and global form perception tasks while their hands were positioned a) near the display in a posture affording a power grasp, b) near the display in a posture affording a precision grasp, or c) in their laps. Although the power grasp posture facilitated performance on the motion task, the precision grasp posture instead facilitated performance on the form task. These results suggest that the visual system weights processing based on an observer’s current affordances for specific actions: fast and forceful power grasps enhance temporal sensitivity, while detail-oriented precision grasps enhance spatial sensitivity. PMID:25862545

Understanding the effect of an excessive cold tongue bias on projecting the tropical Pacific SST warming pattern in CMIP5 models

NASA Astrophysics Data System (ADS)

Ying, Jun; Huang, Ping; Lian, Tao; Tan, Hongjian

2018-05-01

An excessive cold tongue is a common bias among current climate models, and considered an important source of bias in projections of tropical Pacific climate change under global warming. Specifically, the excessive cold tongue bias is closely related to the tropical Pacific SST warming (TPSW) pattern. In this study, we reveal that two processes are the critical mechanisms by which the excessive cold tongue bias influences the projection of the TPSW pattern, based on 32 models from phase 5 of Coupled Model Intercomparison Projection (CMIP5). On the one hand, by assuming that the shortwave (SW) radiation to SST feedback is linearly correlated to the cold tongue SST, the excessive cold tongue bias can induce an overly weak negative SW-SST feedback in the central Pacific, which can lead to a positive SST warming bias in the central to western Pacific (around 150°E-140°W). Moreover, the overly weak local atmospheric dynamics response to SST is a key process of the overly weak SW-SST feedback, compared with the cloud response to atmospheric dynamics and the SW radiation response to cloud. On the other hand, the overly strong ocean zonal overturning circulation associated with the excessive cold tongue bias results in an overestimation of the ocean dynamical thermostat effect, with enhanced ocean stratification under global warming, leading to a negative SST warming bias in the central and eastern Pacific (around 170°W-120°W). These two processes jointly form a positive SST warming bias in the western Pacific, contributing to a La Niña-like warming bias. Therefore, we suggest a more realistic climatological cold tongue SST is needed for a more reliable projection of the TPSW pattern.

Local and global processing of music in high-functioning persons with autism: beyond central coherence?

PubMed

Mottron, L; Peretz, I; Ménard, E

2000-11-01

A multi-modal abnormality in the integration of parts and whole has been proposed to account for a bias toward local stimuli in individuals with autism (Frith, 1989; Mottron & Belleville, 1993). In the current experiment, we examined the utility of hierarchical models in characterising musical information processing in autistic individuals. Participants were 13 high-functioning individuals with autism and 13 individuals of normal intelligence matched on chronological age, nonverbal IQ, and laterality, and without musical experience. The task consisted of same-different judgements of pairs of melodies. Differential local and global processing was assessed by manipulating the level, local or global, at which modifications occurred. No deficit was found in the two measures of global processing. In contrast, the clinical group performed better than the comparison group in the detection of change in nontransposed, contour-preserved melodies that tap local processing. These findings confirm the existence of a "local bias" in music perception in individuals with autism, but challenge the notion that it is accounted for by a deficit in global music processing. The present study suggests that enhanced processing of elementary physical properties of incoming stimuli, as found previously in the visual modality, may also exist in the auditory modality.

Adaptation to Leftward-Shifting Prisms Reduces the Global Processing Bias of Healthy Individuals

ERIC Educational Resources Information Center

Bultitude, Janet H.; Woods, Jill M.

2010-01-01

When healthy individuals are presented with peripheral figures in which small letters are arranged to form a large letter, they are faster to identify the global- than the local-level information, and have difficulty ignoring global information when identifying the local level. The global reaction time (RT) advantage and global interference effect…

Zooming into creativity: individual differences in attentional global-local biases are linked to creative thinking

PubMed Central

Zmigrod, Sharon; Zmigrod, Leor; Hommel, Bernhard

2015-01-01

While recent studies have investigated how processes underlying human creativity are affected by particular visual-attentional states, we tested the impact of more stable attention-related preferences. These were assessed by means of Navon’s global-local task, in which participants respond to the global or local features of large letters constructed from smaller letters. Three standard measures were derived from this task: the sizes of the global precedence effect, the global interference effect (i.e., the impact of incongruent letters at the global level on local processing), and the local interference effect (i.e., the impact of incongruent letters at the local level on global processing). These measures were correlated with performance in a convergent-thinking creativity task (the Remote Associates Task), a divergent-thinking creativity task (the Alternate Uses Task), and a measure of fluid intelligence (Raven’s matrices). Flexibility in divergent thinking was predicted by the local interference effect while convergent thinking was predicted by intelligence only. We conclude that a stronger attentional bias to visual information about the “bigger picture” promotes cognitive flexibility in searching for multiple solutions. PMID:26579030

Interocular suppression in amblyopia for global orientation processing.

PubMed

Zhou, Jiawei; Huang, Pi-Chun; Hess, Robert F

2013-04-22

We developed a dichoptic global orientation coherence paradigm to quantify interocular suppression in amblyopia. This task is biased towards ventral processing and allows comparison with two other techniques-global motion processing, which is more dorsally biased, and binocular phase combination, which most likely reflects striate function. We found a similar pattern for the relationship between coherence threshold and interocular contrast curves (thresholds vs. interocular contrast ratios or TvRs) in our new paradigm compared with those of the previous dichoptic global motion coherence paradigm. The effective contrast ratios at balance point (where the signals from the two eyes have equal weighting) in our new paradigm were larger than those of the dichoptic global motion coherence paradigm but less than those of the binocular phase combination paradigm. The measured effective contrast ratios in the three paradigms were also positively correlated with each other, with the two global coherence paradigms having the highest correlation. We concluded that: (a) The dichoptic global orientation coherence paradigm is effective in quantifying interocular suppression in amblyopia; and (b) Interocular suppression, while sharing a common suppression mechanism at the early stage in the pathway (e.g., striate cortex), may have additional extra-striate contributions that affect both dorsal and ventral streams differentially.

Biases in GNSS-Data Processing

NASA Astrophysics Data System (ADS)

Schaer, S. C.; Dach, R.; Lutz, S.; Meindl, M.; Beutler, G.

2010-12-01

Within the Global Positioning System (GPS) traditionally different types of pseudo-range measurements (P-code, C/A-code) are available on the first frequency that are tracked by the receivers with different technologies. For that reason, P1-C1 and P1-P2 Differential Code Biases (DCB) need to be considered in a GPS data processing with a mix of different receiver types. Since the Block IIR-M series of GPS satellites also provide C/A-code on the second frequency, P2-C2 DCB need to be added to the list of biases for maintenance. Potential quarter-cycle biases between different phase observables (specifically L2P and L2C) are another issue. When combining GNSS (currently GPS and GLONASS), careful consideration of inter-system biases (ISB) is indispensable, in particular when an adequate combination of individual GLONASS clock correction results from different sources (using, e.g., different software packages) is intended. Facing the GPS and GLONASS modernization programs and the upcoming GNSS, like the European Galileo and the Chinese Compass, an increasing number of types of biases is expected. The Center for Orbit Determination in Europe (CODE) is monitoring these GPS and GLONASS related biases for a long time based on RINEX files of the tracking network of the International GNSS Service (IGS) and in the frame of the data processing as one of the global analysis centers of the IGS. Within the presentation we give an overview on the stability of the biases based on the monitoring. Biases derived from different sources are compared. Finally, we give an outlook on the potential handling of such biases with the big variety of signals and systems expected in the future.

Single-Receiver GPS Phase Bias Resolution

NASA Technical Reports Server (NTRS)

Bertiger, William I.; Haines, Bruce J.; Weiss, Jan P.; Harvey, Nathaniel E.

2010-01-01

Existing software has been modified to yield the benefits of integer fixed double-differenced GPS-phased ambiguities when processing data from a single GPS receiver with no access to any other GPS receiver data. When the double-differenced combination of phase biases can be fixed reliably, a significant improvement in solution accuracy is obtained. This innovation uses a large global set of GPS receivers (40 to 80 receivers) to solve for the GPS satellite orbits and clocks (along with any other parameters). In this process, integer ambiguities are fixed and information on the ambiguity constraints is saved. For each GPS transmitter/receiver pair, the process saves the arc start and stop times, the wide-lane average value for the arc, the standard deviation of the wide lane, and the dual-frequency phase bias after bias fixing for the arc. The second step of the process uses the orbit and clock information, the bias information from the global solution, and only data from the single receiver to resolve double-differenced phase combinations. It is called "resolved" instead of "fixed" because constraints are introduced into the problem with a finite data weight to better account for possible errors. A receiver in orbit has much shorter continuous passes of data than a receiver fixed to the Earth. The method has parameters to account for this. In particular, differences in drifting wide-lane values must be handled differently. The first step of the process is automated, using two JPL software sets, Longarc and Gipsy-Oasis. The resulting orbit/clock and bias information files are posted on anonymous ftp for use by any licensed Gipsy-Oasis user. The second step is implemented in the Gipsy-Oasis executable, gd2p.pl, which automates the entire process, including fetching the information from anonymous ftp

Developmental Changes in the Processing of Hierarchical Shapes Continue into Adolescence.

ERIC Educational Resources Information Center

Mondloch, Catherine J.; Geldart, Sybil; Maurer, Daphne; de Schonen, Scania

2003-01-01

Three experiments obtained same-different judgments from children and adults to trace normal development of local and global processing of hierarchical visual forms. Findings indicated that reaction time was faster on global trials than local trials; bias was stronger in children and diminished to adult levels between ages 10 and 14. Reaction time…

Effects of Age and Attention on Auditory Global-Local Processing in Children with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Foster, Nicholas E. V.; Ouimet, Tia; Tryfon, Ana; Doyle-Thomas, Krissy; Anagnostou, Evdokia; Hyde, Krista L.

2016-01-01

In vision, typically-developing (TD) individuals perceive "global" (whole) before "local" (detailed) features, whereas individuals with autism spectrum disorder (ASD) exhibit a local bias. However, auditory global-local distinctions are less clear in ASD, particularly in terms of age and attention effects. To these aims, here…

Improved simulation of tropospheric ozone by a global-multi-regional two-way coupling model system

NASA Astrophysics Data System (ADS)

Yan, Y.-Y.; Lin, J.-T.; Chen, J.; Hu, L.

2015-09-01

Small-scale nonlinear chemical and physical processes over pollution source regions affect the global ozone (O3) chemistry, but these processes are not captured by current global chemical transport models (CTMs) and chemistry-climate models that are limited by coarse horizontal resolutions (100-500 km, typically 200 km). These models tend to contain large (and mostly positive) tropospheric O3 biases in the Northern Hemisphere. Here we use a recently built two-way coupling system of the GEOS-Chem CTM to simulate the global tropospheric O3 in 2009. The system couples the global model (at 2.5° long. × 2° lat.) and its three nested models (at 0.667° long. × 0.5° lat.) covering Asia, North America and Europe, respectively. Benefiting from the high resolution, the nested models better capture small-scale processes than the global model alone. In the coupling system, the nested models provide results to modify the global model simulation within respective nested domains while taking the lateral boundary conditions from the global model. Due to the "coupling" effects, the two-way system significantly improves the tropospheric O3 simulation upon the global model alone, as found by comparisons with a suite of ground (1420 sites from WDCGG, GMD, EMEP, and AQS), aircraft (HIPPO and MOZAIC), and satellite measurements (two OMI products). Compared to the global model alone, the two-way coupled simulation enhances the correlation in day-to-day variation of afternoon mean O3 with the ground measurements from 0.53 to 0.68, and it reduces the mean model bias from 10.8 to 6.7 ppb in annual average afternoon O3. Regionally, the coupled model reduces the bias by 4.6 ppb over Europe, 3.9 ppb over North America, and 3.1 ppb over other regions. The two-way coupling brings O3 vertical profiles much closer to the HIPPO (for remote areas) and MOZAIC (for polluted regions) data, reducing the tropospheric (0-9 km) mean bias by 3-10 ppb at most MOZAIC sites and by 5.3 ppb for HIPPO profiles. The two-way coupled simulation also reduces the global tropospheric column ozone by 3.0 DU (9.5 %, annual mean), bringing them closer to the OMI data in all seasons. Simulation improvements are more significant in the northern hemisphere, and are primarily a result of improved representation of urban-rural contrast and other small-scale processes. The two-way coupled simulation also reduces the global tropospheric mean hydroxyl radical by 5 % with enhancements by 5 % in the lifetimes of methyl chloroform (from 5.58 to 5.87 yr) and methane (from 9.63 to 10.12 yr), bringing them closer to observation-based estimates. Improving model representations of small-scale processes are a critical step forward to understanding the global tropospheric chemistry.

Caffeine Promotes Global Spatial Processing in Habitual and Non-Habitual Caffeine Consumers

PubMed Central

Giles, Grace E.; Mahoney, Caroline R.; Brunyé, Tad T.; Taylor, Holly A.; Kanarek, Robin B.

2013-01-01

Information processing is generally biased toward global cues, often at the expense of local information. Equivocal extant data suggests that arousal states may accentuate either a local or global processing bias, at least partially dependent on the nature of the manipulation, task, and stimuli. To further differentiate the conditions responsible for such equivocal results we varied caffeine doses to alter physiological arousal states and measured their effect on tasks requiring the retrieval of local versus global spatial knowledge. In a double-blind, repeated-measures design, non-habitual (Experiment 1; N = 36, M = 42.5 ± 28.7 mg/day caffeine) and habitual (Experiment 2; N = 34, M = 579.5 ± 311.5 mg/day caffeine) caffeine consumers completed four test sessions corresponding to each of four caffeine doses (0, 100, 200, 400 mg). During each test session, participants consumed a capsule containing one of the three doses of caffeine or placebo, waited 60 min, and then completed two spatial tasks, one involving memorizing maps and one spatial descriptions. A spatial statement verification task tested local versus global spatial knowledge by differentially probing memory for proximal versus distal landmark relationships. On the map learning task, results indicated that caffeine enhanced memory for distal (i.e., global) compared to proximal (i.e., local) comparisons at 100 (marginal), 200, and 400 mg caffeine in non-habitual consumers, and marginally beginning at 200 mg caffeine in habitual consumers. On the spatial descriptions task, caffeine enhanced memory for distal compared to proximal comparisons beginning at 100 mg in non-habitual but not habitual consumers. We thus provide evidence that caffeine-induced physiological arousal amplifies global spatial processing biases, and these effects are at least partially driven by habitual caffeine consumption. PMID:24146646

The Impact of Parameterized Convection on Climatological Precipitation in Atmospheric Global Climate Models

NASA Astrophysics Data System (ADS)

Maher, Penelope; Vallis, Geoffrey K.; Sherwood, Steven C.; Webb, Mark J.; Sansom, Philip G.

2018-04-01

Convective parameterizations are widely believed to be essential for realistic simulations of the atmosphere. However, their deficiencies also result in model biases. The role of convection schemes in modern atmospheric models is examined using Selected Process On/Off Klima Intercomparison Experiment simulations without parameterized convection and forced with observed sea surface temperatures. Convection schemes are not required for reasonable climatological precipitation. However, they are essential for reasonable daily precipitation and constraining extreme daily precipitation that otherwise develops. Systematic effects on lapse rate and humidity are likewise modest compared with the intermodel spread. Without parameterized convection Kelvin waves are more realistic. An unexpectedly large moist Southern Hemisphere storm track bias is identified. This storm track bias persists without convection schemes, as does the double Intertropical Convergence Zone and excessive ocean precipitation biases. This suggests that model biases originate from processes other than convection or that convection schemes are missing key processes.

Impaired holistic processing in congenital prosopagnosia

PubMed Central

Avidan, Galia; Tanzer, Michal; Behrmann, Marlene

2011-01-01

It has long been argued that face processing requires disproportionate reliance on holistic or configural processing, relative to that required for non-face object recognition, and that a disruption of such holistic processing may be causally implicated in prosopagnosia. Previously, we demonstrated that individuals with congenital prosopagnosia (CP) did not show the normal face inversion effect (better performance for upright compared to inverted faces) and evinced a local (rather than the normal global) bias in a compound letter global/local (GL) task, supporting the claim of disrupted holistic processing in prosopagnosia. Here, we investigate further the nature of holistic processing impairments in CP, first by confirming, in a large sample of CP individuals, the absence of the normal face inversion effect and the presence of the local bias on the GL task, and, second, by employing the composite face paradigm, often regarded as the gold standard for measuring holistic face processing. In this last task, we show that, in contrast with normal individuals, the CP group perform equivalently with aligned and misaligned faces and was impervious to (the normal) interference from the task-irrelevant bottom part of faces. Interestingly, the extent of the local bias evident in the composite task is correlated with the abnormality of performance on diagnostic face processing tasks. Furthermore, there is a significant correlation between the magnitude of the local bias in the GL and performance on the composite task. These results provide further evidence for impaired holistic processing in CP and, moreover, corroborate the critical role of this type of processing for intact face recognition. PMID:21601583

Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling.

PubMed

El-Gabbas, Ahmed; Dormann, Carsten F

2018-02-01

Species distribution modeling (SDM) is an essential method in ecology and conservation. SDMs are often calibrated within one country's borders, typically along a limited environmental gradient with biased and incomplete data, making the quality of these models questionable. In this study, we evaluated how adequate are national presence-only data for calibrating regional SDMs. We trained SDMs for Egyptian bat species at two different scales: only within Egypt and at a species-specific global extent. We used two modeling algorithms: Maxent and elastic net, both under the point-process modeling framework. For each modeling algorithm, we measured the congruence of the predictions of global and regional models for Egypt, assuming that the lower the congruence, the lower the appropriateness of the Egyptian dataset to describe the species' niche. We inspected the effect of incorporating predictions from global models as additional predictor ("prior") to regional models, and quantified the improvement in terms of AUC and the congruence between regional models run with and without priors. Moreover, we analyzed predictive performance improvements after correction for sampling bias at both scales. On average, predictions from global and regional models in Egypt only weakly concur. Collectively, the use of priors did not lead to much improvement: similar AUC and high congruence between regional models calibrated with and without priors. Correction for sampling bias led to higher model performance, whatever prior used, making the use of priors less pronounced. Under biased and incomplete sampling, the use of global bats data did not improve regional model performance. Without enough bias-free regional data, we cannot objectively identify the actual improvement of regional models after incorporating information from the global niche. However, we still believe in great potential for global model predictions to guide future surveys and improve regional sampling in data-poor regions.

A tale of two agnosias: distinctions between form and integrative agnosia.

PubMed

Riddoch, M Jane; Humphreys, Glyn W; Akhtar, Nabeela; Allen, Harriet; Bracewell, R Martyn; Schofield, Andrew J

2008-02-01

The performance of two patients with visual agnosia was compared across a number of tests examining visual processing. The patients were distinguished by having dorsal and medial ventral extrastriate lesions. While inanimate objects were disadvantaged for the patient with a dorsal extrastriate lesion, animate items are disadvantaged for the patient with the medial ventral extrastriate lesion. The patients also showed contrasting patterns of performance on the Navon Test: The patient with a dorsal extrastriate lesion demonstrated a local bias while the patient with a medial ventral extrastriate lesion had a global bias. We propose that the dorsal and medial ventral visual pathways may be characterized at an extrastriate level by differences in local relative to more global visual processing and that this can link to visually based category-specific deficits in processing.

Different Dimensions of Cognitive Style in Typical and Atypical Cognition: New Evidence and a New Measurement Tool.

PubMed

Mealor, Andy D; Simner, Julia; Rothen, Nicolas; Carmichael, Duncan A; Ward, Jamie

2016-01-01

We developed the Sussex Cognitive Styles Questionnaire (SCSQ) to investigate visual and verbal processing preferences and incorporate global/local processing orientations and systemising into a single, comprehensive measure. In Study 1 (N = 1542), factor analysis revealed six reliable subscales to the final 60 item questionnaire: Imagery Ability (relating to the use of visual mental imagery in everyday life); Technical/Spatial (relating to spatial mental imagery, and numerical and technical cognition); Language & Word Forms; Need for Organisation; Global Bias; and Systemising Tendency. Thus, we replicate previous findings that visual and verbal styles are separable, and that types of imagery can be subdivided. We extend previous research by showing that spatial imagery clusters with other abstract cognitive skills, and demonstrate that global/local bias can be separated from systemising. Study 2 validated the Technical/Spatial and Language & Word Forms factors by showing that they affect performance on memory tasks. In Study 3, we validated Imagery Ability, Technical/Spatial, Language & Word Forms, Global Bias, and Systemising Tendency by issuing the SCSQ to a sample of synaesthetes (N = 121) who report atypical cognitive profiles on these subscales. Thus, the SCSQ consolidates research from traditionally disparate areas of cognitive science into a comprehensive cognitive style measure, which can be used in the general population, and special populations.

Different Dimensions of Cognitive Style in Typical and Atypical Cognition: New Evidence and a New Measurement Tool

PubMed Central

Mealor, Andy D.; Simner, Julia; Rothen, Nicolas; Carmichael, Duncan A.; Ward, Jamie

2016-01-01

We developed the Sussex Cognitive Styles Questionnaire (SCSQ) to investigate visual and verbal processing preferences and incorporate global/local processing orientations and systemising into a single, comprehensive measure. In Study 1 (N = 1542), factor analysis revealed six reliable subscales to the final 60 item questionnaire: Imagery Ability (relating to the use of visual mental imagery in everyday life); Technical/Spatial (relating to spatial mental imagery, and numerical and technical cognition); Language & Word Forms; Need for Organisation; Global Bias; and Systemising Tendency. Thus, we replicate previous findings that visual and verbal styles are separable, and that types of imagery can be subdivided. We extend previous research by showing that spatial imagery clusters with other abstract cognitive skills, and demonstrate that global/local bias can be separated from systemising. Study 2 validated the Technical/Spatial and Language & Word Forms factors by showing that they affect performance on memory tasks. In Study 3, we validated Imagery Ability, Technical/Spatial, Language & Word Forms, Global Bias, and Systemising Tendency by issuing the SCSQ to a sample of synaesthetes (N = 121) who report atypical cognitive profiles on these subscales. Thus, the SCSQ consolidates research from traditionally disparate areas of cognitive science into a comprehensive cognitive style measure, which can be used in the general population, and special populations. PMID:27191169

Exploiting Satellite Archives to Estimate Global Glacier Volume Changes

NASA Astrophysics Data System (ADS)

McNabb, R. W.; Nuth, C.; Kääb, A.; Girod, L.

2017-12-01

In the past decade, the availability of, and ability to process, remote sensing data over glaciers has expanded tremendously. Newly opened satellite image archives, combined with new processing techniques as well as increased computing power and storage capacity, have given the glaciological community the ability to observe and investigate glaciological processes and changes on a truly global scale. In particular, the opening of the ASTER archives provides further opportunities to both estimate and monitor glacier elevation and volume changes globally, including potentially on sub-annual timescales. With this explosion of data availability, however, comes the challenge of seeing the forest instead of the trees. The high volume of data available means that automated detection and proper handling of errors and biases in the data becomes critical, in order to properly study the processes that we wish to see. This includes holes and blunders in digital elevation models (DEMs) derived from optical data or penetration of radar signals leading to biases in DEMs derived from radar data, among other sources. Here, we highlight new advances in the ability to sift through high-volume datasets, and apply these techniques to estimate recent glacier volume changes in the Caucasus Mountains, Scandinavia, Africa, and South America. By properly estimating and correcting for these biases, we additionally provide a detailed accounting of the uncertainties in these estimates of volume changes, leading to more reliable results that have applicability beyond the glaciological community.

Sampling Biases in MODIS and SeaWiFS Ocean Chlorophyll Data

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Casey, Nancy W.

2007-01-01

Although modem ocean color sensors, such as MODIS and SeaWiFS are often considered global missions, in reality it takes many days, even months, to sample the ocean surface enough to provide complete global coverage. The irregular temporal sampling of ocean color sensors can produce biases in monthly and annual mean chlorophyll estimates. We quantified the biases due to sampling using data assimilation to create a "truth field", which we then sub-sampled using the observational patterns of MODIS and SeaWiFS. Monthly and annual mean chlorophyll estimates from these sub-sampled, incomplete daily fields were constructed and compared to monthly and annual means from the complete daily fields of the assimilation model, at a spatial resolution of 1.25deg longitude by 0.67deg latitude. The results showed that global annual mean biases were positive, reaching nearly 8% (MODIS) and >5% (SeaWiFS). For perspective the maximum interannual variability in the SeaWiFS chlorophyll record was about 3%. Annual mean sampling biases were low (<3%) in the midlatitudes (between -40deg and 40deg). Low interannual variability in the global annual mean sampling biases suggested that global scale trend analyses were valid. High latitude biases were much higher than the global annual means, up to 20% as a basin annual mean, and over 80% in some months. This was the result of the high solar zenith angle exclusion in the processing algorithms. Only data where the solar angle is <75deg are permitted, in contrast to the assimilation which samples regularly over the entire area and month. High solar zenith angles do not facilitate phytoplankton photosynthesis and consequently low chlorophyll concentrations occurring here are missed by the data sets. Ocean color sensors selectively sample in locations and times of favorable phytoplankton growth, producing overestimates of chlorophyll. The biases derived from lack of sampling in the high latitudes varied monthly, leading to artifacts in the apparent seasonal cycle from ocean color sensors. A false secondary peak in chlorophyll occurred in May-August, which resulted from lack of sampling in the Antarctic.

Toward a Comprehensive Understanding of Executive Cognitive Function in Implicit Racial Bias

PubMed Central

Ito, Tiffany A.; Friedman, Naomi P.; Bartholow, Bruce D.; Correll, Joshua; Loersch, Chris; Altamirano, Lee J.; Miyake, Akira

2014-01-01

Although performance on laboratory-based implicit bias tasks often is interpreted strictly in terms of the strength of automatic associations, recent evidence suggests that such tasks are influenced by higher-order cognitive control processes, so-called executive functions (EFs). However, extant work in this area has been limited by failure to account for the unity and diversity of EFs, focus on only a single measure of bias and/or EF, and relatively small sample sizes. The current study sought to comprehensively model the relation between individual differences in EFs and the expression of racial bias in three commonly used laboratory measures. Participants (N=485) completed a battery of EF tasks (session 1) and three racial bias tasks (session 2), along with numerous individual difference questionnaires. The main findings were as follows: (1) measures of implicit bias were only weakly intercorrelated; (2) EF and estimates of automatic processes both predicted implicit bias and also interacted, such that the relation between automatic processes and bias expression was reduced at higher levels of EF; (3) specific facets of EF were differentially associated with overall task performance and controlled processing estimates across different bias tasks; (4) EF did not moderate associations between implicit and explicit measures of bias; and (5) external, but not internal, motivation to control prejudice depended on EF to reduce bias expression. Findings are discussed in terms of the importance of global and specific EF abilities in determining expression of implicit racial bias. PMID:25603372

A single bout of meditation biases cognitive control but not attentional focusing: Evidence from the global-local task.

PubMed

Colzato, Lorenza S; van der Wel, Pauline; Sellaro, Roberta; Hommel, Bernhard

2016-01-01

Recent studies show that a single bout of meditation can impact information processing. We were interested to see whether this impact extends to attentional focusing and the top-down control over irrelevant information. Healthy adults underwent brief single bouts of either focused attention meditation (FAM), which is assumed to increase top-down control, or open monitoring meditation (OMM), which is assumed to weaken top-down control, before performing a global-local task. While the size of the global-precedence effect (reflecting attentional focusing) was unaffected by type of meditation, the congruency effect (indicating the failure to suppress task-irrelevant information) was considerably larger after OMM than after FAM. Our findings suggest that engaging in particular kinds of meditation creates particular cognitive-control states that bias the individual processing style toward either goal-persistence or cognitive flexibility. Copyright © 2015 Elsevier Inc. All rights reserved.

[Application of an Adaptive Inertia Weight Particle Swarm Algorithm in the Magnetic Resonance Bias Field Correction].

PubMed

Wang, Chang; Qin, Xin; Liu, Yan; Zhang, Wenchao

2016-06-01

An adaptive inertia weight particle swarm algorithm is proposed in this study to solve the local optimal problem with the method of traditional particle swarm optimization in the process of estimating magnetic resonance(MR)image bias field.An indicator measuring the degree of premature convergence was designed for the defect of traditional particle swarm optimization algorithm.The inertia weight was adjusted adaptively based on this indicator to ensure particle swarm to be optimized globally and to avoid it from falling into local optimum.The Legendre polynomial was used to fit bias field,the polynomial parameters were optimized globally,and finally the bias field was estimated and corrected.Compared to those with the improved entropy minimum algorithm,the entropy of corrected image was smaller and the estimated bias field was more accurate in this study.Then the corrected image was segmented and the segmentation accuracy obtained in this research was 10% higher than that with improved entropy minimum algorithm.This algorithm can be applied to the correction of MR image bias field.

Cross Cultural Differences in Unconscious Knowledge

ERIC Educational Resources Information Center

Kiyokawa, Sachiko; Dienes, Zoltan; Tanaka, Daisuke; Yamada, Ayumi; Crowe, Louise

2012-01-01

Previous studies have indicated cross cultural differences in conscious processes, such that Asians have a global preference and Westerners a more analytical one. We investigated whether these biases also apply to unconscious knowledge. In Experiment 1, Japanese and UK participants memorized strings of large (global) letters made out of small…

Improving Subtropical Boundary Layer Cloudiness in the 2011 NCEP GFS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fletcher, J. K.; Bretherton, Christopher S.; Xiao, Heng

2014-09-23

The current operational version of National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) shows significant low cloud bias. These biases also appear in the Coupled Forecast System (CFS), which is developed from the GFS. These low cloud biases degrade seasonal and longer climate forecasts, particularly of short-wave cloud radiative forcing, and affect predicted sea surface temperature. Reducing this bias in the GFS will aid the development of future CFS versions and contributes to NCEP's goal of unified weather and climate modelling. Changes are made to the shallow convection and planetary boundary layer parameterisations to make them more consistentmore » with current knowledge of these processes and to reduce the low cloud bias. These changes are tested in a single-column version of GFS and in global simulations with GFS coupled to a dynamical ocean model. In the single-column model, we focus on changing parameters that set the following: the strength of shallow cumulus lateral entrainment, the conversion of updraught liquid water to precipitation and grid-scale condensate, shallow cumulus cloud top, and the effect of shallow convection in stratocumulus environments. Results show that these changes improve the single-column simulations when compared to large eddy simulations, in particular through decreasing the precipitation efficiency of boundary layer clouds. These changes, combined with a few other model improvements, also reduce boundary layer cloud and albedo biases in global coupled simulations.« less

Toward a comprehensive understanding of executive cognitive function in implicit racial bias.

PubMed

Ito, Tiffany A; Friedman, Naomi P; Bartholow, Bruce D; Correll, Joshua; Loersch, Chris; Altamirano, Lee J; Miyake, Akira

2015-02-01

Although performance on laboratory-based implicit bias tasks often is interpreted strictly in terms of the strength of automatic associations, recent evidence suggests that such tasks are influenced by higher-order cognitive control processes, so-called executive functions (EFs). However, extant work in this area has been limited by failure to account for the unity and diversity of EFs, focus on only a single measure of bias and/or EF, and relatively small sample sizes. The current study sought to comprehensively model the relation between individual differences in EFs and the expression of racial bias in 3 commonly used laboratory measures. Participants (N = 485) completed a battery of EF tasks (Session 1) and 3 racial bias tasks (Session 2), along with numerous individual difference questionnaires. The main findings were as follows: (a) measures of implicit bias were only weakly intercorrelated; (b) EF and estimates of automatic processes both predicted implicit bias and also interacted, such that the relation between automatic processes and bias expression was reduced at higher levels of EF; (c) specific facets of EF were differentially associated with overall task performance and controlled processing estimates across different bias tasks; (d) EF did not moderate associations between implicit and explicit measures of bias; and (e) external, but not internal, motivation to control prejudice depended on EF to reduce bias expression. Findings are discussed in terms of the importance of global and specific EF abilities in determining expression of implicit racial bias. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Improved simulation of tropospheric ozone by a global-multi-regional two-way coupling model system

NASA Astrophysics Data System (ADS)

Yan, Y.; Lin, J.; Hu, L.; Chen, J.

2016-12-01

Small-scale nonlinear chemical and physical processes over pollution source regions affect the tropospheric ozone, but these processes are not captured by current global chemical transport models and chemistry-climate models that are limited by coarse horizontal resolutions. These models tend to contain large (and mostly positive) tropospheric O3 biases in the Northern Hemisphere. Here we use a recently built two-way coupling system of the GEOS-Chem CTM to simulate the regional and global tropospheric O3in 2009. The system couples the global model (at 2.5º long. x 2º lat.) and its three nested models (at 0.667º long. x 0.5º lat.) covering Asia, North America and Europe, respectively. Specifically, the nested models take lateral boundary conditions from the global model, better capture small-scale processes, and feed back to modify the global model simulation within the nested domains, with a subsequent effect on their LBCs. Compared to the global model alone, the two-way coupled system better simulates the tropospheric O3 both within and outside the nested domains, as found by evaluation against a suite of ground (1420 sites from WDCGG, GMD, EMEP, and AQS), aircraft (HIPPO and MOZAIC), and satellite measurements (two OMI products). The two-way coupled simulation enhances the correlation in day-to-day variation of afternoon mean surface O3 with the ground measurements from 0.53 to 0.68, and it reduces the mean model bias from 10.8 to 6.7 ppb. Regionally, the coupled system reduces the bias by 4.6 ppb over Europe, 3.9 ppb over North America, and 3.1 ppb over other regions. The two-way coupling brings O3vertical profiles much closer to the HIPPO (for remote areas) and MOZAIC (for polluted regions) data, reducing the tropospheric mean bias by 3-10 ppb at most MOZAIC sites and by 5.3 ppb for HIPPO profiles. The two-way coupled simulation also reduces the global tropospheric column ozone by 3.0 DU (9.5%, annual mean), bringing them closer to the OMI data in all seasons. Additionally, the two-way coupled simulation also reduces the global tropospheric mean hydroxyl radical by 5% with improved estimates of methyl chloroform and methane lifetimes. Simulation improvements are more significant in the Northern Hemisphere, and are mainly driven by improved representation of spatial inhomogeneity in chemistry/emissions.

Linear Response Path Following: A Molecular Dynamics Method To Simulate Global Conformational Changes of Protein upon Ligand Binding.

PubMed

Tamura, Koichi; Hayashi, Shigehiko

2015-07-14

Molecular functions of proteins are often fulfilled by global conformational changes that couple with local events such as the binding of ligand molecules. High molecular complexity of proteins has, however, been an obstacle to obtain an atomistic view of the global conformational transitions, imposing a limitation on the mechanistic understanding of the functional processes. In this study, we developed a new method of molecular dynamics (MD) simulation called the linear response path following (LRPF) to simulate a protein's global conformational changes upon ligand binding. The method introduces a biasing force based on a linear response theory, which determines a local reaction coordinate in the configuration space that represents linear coupling between local events of ligand binding and global conformational changes and thus provides one with fully atomistic models undergoing large conformational changes without knowledge of a target structure. The overall transition process involving nonlinear conformational changes is simulated through iterative cycles consisting of a biased MD simulation with an updated linear response force and a following unbiased MD simulation for relaxation. We applied the method to the simulation of global conformational changes of the yeast calmodulin N-terminal domain and successfully searched out the end conformation. The atomistically detailed trajectories revealed a sequence of molecular events that properly lead to the global conformational changes and identified key steps of local-global coupling that induce the conformational transitions. The LRPF method provides one with a powerful means to model conformational changes of proteins such as motors and transporters where local-global coupling plays a pivotal role in their functional processes.

Tropospheric ozone simulated by a global-multi-regional two-way coupling model system

NASA Astrophysics Data System (ADS)

Yan, Y.; Lin, J.; Chen, J.; Hu, L.

2015-12-01

Current global chemical transport models are limited by horizontal resolutions (100-500 km), and they cannot capture small-scale processes affecting tropospheric ozone (O3). Here we use a recently built two-way coupling system of GEOS-Chem to simulate the global tropospheric O3 in 2009. The system couples the global model (~ 200 km) and its three nested models (~ 50 km) covering Asia, North America and Europe, respectively. Benefiting from the high resolution, the nested models better capture small-scale processes than the global model alone. In the coupling system, the nested models provide results to modify the global model simulation within respective nested domains while taking the lateral boundary conditions from the global model. Due to the "coupling" effects, the two-way system significantly improves the tropospheric O3 simulation upon the global model alone, as found by comparisons with a suite of ground (1420 sites from WDCGG, GMD, EMEP, and AQS), aircraft (HIPPO and MOZAIC), and satellite measurements (two OMI products). Compared to the global model alone, the two-way coupled simulation enhances the correlation in day-to-day variation of afternoon mean O3 with the ground measurements from 0.53 to 0.68 and reduces the mean model bias from 10.8 to 6.7 ppb. Regionally, the coupled model reduces the bias by 4.6 ppb over Europe, 3.9 ppb over North America, and 3.1 ppb over other regions. The two-way coupling brings O3 vertical profiles much closer to the HIPPO and MOZAIC data, reducing the tropospheric (0-9 km) mean bias by 3-10 ppb at most MOZAIC sites and by 5.3 ppb for HIPPO profiles. The two-way coupled simulation also reduces the global tropospheric column ozone by 3.0 DU (9.5%), bringing them closer to the OMI data in all seasons. Simulation improvements are more significant in the northern hemisphere, and are primarily a result of improved representation of the nonlinear ozone chemistry, including but not limited to urban-rural contrast. The two-way coupled simulation also reduces the global tropospheric mean hydroxyl radical by 5% with enhancements by 5% in lifetimes of methyl chloroform and methane, bringing them closer to observation-based estimates. Therefore improving model representations of small-scale processes are a critical step forward to understanding the global tropospheric chemistry.

Local and Global Processing: Observations from a Remote Culture

ERIC Educational Resources Information Center

Davidoff, Jules; Fonteneau, Elisabeth; Fagot, Joel

2008-01-01

In Experiment 1, a normal adult population drawn from a remote culture (Himba) in northern Namibia made similarity matches to [Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. "Cognitive Psychology", 9, 353-383] hierarchical figures. The Himba showed a local bias stronger than that has been…

Decoupling global biases and local interactions between cell biological variables

PubMed Central

Zaritsky, Assaf; Obolski, Uri; Gan, Zhuo; Reis, Carlos R; Kadlecova, Zuzana; Du, Yi; Schmid, Sandra L; Danuser, Gaudenz

2017-01-01

Analysis of coupled variables is a core concept of cell biological inference, with co-localization of two molecules as a proxy for protein interaction being a ubiquitous example. However, external effectors may influence the observed co-localization independently from the local interaction of two proteins. Such global bias, although biologically meaningful, is often neglected when interpreting co-localization. Here, we describe DeBias, a computational method to quantify and decouple global bias from local interactions between variables by modeling the observed co-localization as the cumulative contribution of a global and a local component. We showcase four applications of DeBias in different areas of cell biology, and demonstrate that the global bias encapsulates fundamental mechanistic insight into cellular behavior. The DeBias software package is freely accessible online via a web-server at https://debias.biohpc.swmed.edu. DOI: http://dx.doi.org/10.7554/eLife.22323.001 PMID:28287393

Intercomparison and Evaluation of Global Aerosol Microphysical Properties Among Aerocom Models of a Range of Complexity

NASA Technical Reports Server (NTRS)

Mann, G. W.; Carslaw, K. S.; Reddington, C. L.; Pringle, K. J.; Schulz, M.; Asmi, A.; Spracklen, D. V.; Ridley, D. A.; Woodhouse, M. T.; Lee, L. A.;

Drawing links between the autism cognitive profile and imagination: Executive function and processing bias in imaginative drawings by children with and without autism.

PubMed

Ten Eycke, Kayla D; Müller, Ulrich

2018-02-01

Little is known about the relation between cognitive processes and imagination and whether this relation differs between neurotypically developing children and children with autism. To address this issue, we administered a cognitive task battery and Karmiloff-Smith's drawing task, which requires children to draw imaginative people and houses. For children with autism, executive function significantly predicted imaginative drawing. In neurotypically developing controls, executive function and cognitive-perceptual processing style predicted imaginative drawing, but these associations were moderated by mental age. In younger (neurotypically developing) children, better executive function and a local processing bias were associated with imagination; in older children, only a global bias was associated with imagination. These findings suggest that (a) with development there are changes in the type of cognitive processes involved in imagination and (b) children with autism employ a unique cognitive strategy in imaginative drawing.

Global processing takes time: A meta-analysis on local-global visual processing in ASD.

PubMed

Van der Hallen, Ruth; Evers, Kris; Brewaeys, Katrien; Van den Noortgate, Wim; Wagemans, Johan

2015-05-01

What does an individual with autism spectrum disorder (ASD) perceive first: the forest or the trees? In spite of 30 years of research and influential theories like the weak central coherence (WCC) theory and the enhanced perceptual functioning (EPF) account, the interplay of local and global visual processing in ASD remains only partly understood. Research findings vary in indicating a local processing bias or a global processing deficit, and often contradict each other. We have applied a formal meta-analytic approach and combined 56 articles that tested about 1,000 ASD participants and used a wide range of stimuli and tasks to investigate local and global visual processing in ASD. Overall, results show no enhanced local visual processing nor a deficit in global visual processing. Detailed analysis reveals a difference in the temporal pattern of the local-global balance, that is, slow global processing in individuals with ASD. Whereas task-dependent interaction effects are obtained, gender, age, and IQ of either participant groups seem to have no direct influence on performance. Based on the overview of the literature, suggestions are made for future research. (c) 2015 APA, all rights reserved).

A Mixed Phase Tale: New Ways of using in-situ cloud observations to reduce climate model biases in Southern Ocean

NASA Astrophysics Data System (ADS)

Gettelman, A.; Stith, J. L.

2014-12-01

Southern ocean clouds are a critical part of the earth's energy budget, and significant biases in the climatology of these clouds exist in models used to predict climate change. We compare in situ measurements of cloud microphysical properties of ice and liquid over the S. Ocean with constrained output from the atmospheric component of an Earth System Model. Observations taken during the HIAPER (the NSF/NCAR G-V aircraft) Pole-to-Pole Observations (HIPPO) multi-year field campaign are compared with simulations from the atmospheric component of the Community Earth System Model (CESM). Remarkably, CESM is able to accurately simulate the locations of cloud formation, and even cloud microphysical properties are comparable between the model and observations. Significantly, the simulations do not predict sufficient supercooled liquid. Altering the model cloud and aerosol processes to better reproduce the observations of supercooled liquid acts to reduce long-standing biases in S. Ocean clouds in CESM, which are typical of other models. Furthermore, sensitivity tests show where better observational constraints on aerosols and cloud microphysics can reduce uncertainty and biases in global models. These results are intended to show how we can connect large scale simulations with field observations in the S. Ocean to better understand Southern Ocean cloud processes and reduce biases in global climate simulations.

The impact of threat of shock on the framing effect and temporal discounting: executive functions unperturbed by acute stress?

PubMed

Robinson, Oliver J; Bond, Rebecca L; Roiser, Jonathan P

2015-01-01

Anxiety and stress-related disorders constitute a large global health burden, but are still poorly understood. Prior work has demonstrated clear impacts of stress upon basic cognitive function: biasing attention toward unexpected and potentially threatening information and instantiating a negative affective bias. However, the impact that these changes have on higher-order, executive, decision-making processes is unclear. In this study, we examined the impact of a translational within-subjects stress induction (threat of unpredictable shock) on two well-established executive decision-making biases: the framing effect (N = 83), and temporal discounting (N = 36). In both studies, we demonstrate (a) clear subjective effects of stress, and (b) clear executive decision-making biases but (c) no impact of stress on these decision-making biases. Indeed, Bayes factor analyses confirmed substantial preference for decision-making models that did not include stress. We posit that while stress may induce subjective mood change and alter low-level perceptual and action processes (Robinson et al., 2013c), some higher-level executive processes remain unperturbed by these impacts. As such, although stress can induce a transient affective biases and altered mood, these need not result in poor financial decision-making.

Holistic processing for other-race faces in chinese participants occurs for upright but not inverted faces.

PubMed

Crookes, Kate; Favelle, Simone; Hayward, William G

2013-01-01

Recent evidence suggests stronger holistic processing for own-race faces may underlie the own-race advantage in face memory. In previous studies Caucasian participants have demonstrated larger holistic processing effects for Caucasian over Asian faces. However, Asian participants have consistently shown similar sized effects for both Asian and Caucasian faces. We investigated two proposed explanations for the holistic processing of other-race faces by Asian participants: (1) greater other-race exposure, (2) a general global processing bias. Holistic processing was tested using the part-whole task. Participants were living in predominantly own-race environments and other-race contact was evaluated. Despite reporting significantly greater contact with own-race than other-race people, Chinese participants displayed strong holistic processing for both Asian and Caucasian upright faces. In addition, Chinese participants showed no evidence of holistic processing for inverted faces arguing against a general global processing bias explanation. Caucasian participants, in line with previous studies, displayed stronger holistic processing for Caucasian than Asian upright faces. For inverted faces there were no race-of-face differences. These results are used to suggest that Asians may make more general use of face-specific mechanisms than Caucasians.

Holistic Processing for Other-Race Faces in Chinese Participants Occurs for Upright but Not Inverted Faces

PubMed Central

Crookes, Kate; Favelle, Simone; Hayward, William G.

2013-01-01

Recent evidence suggests stronger holistic processing for own-race faces may underlie the own-race advantage in face memory. In previous studies Caucasian participants have demonstrated larger holistic processing effects for Caucasian over Asian faces. However, Asian participants have consistently shown similar sized effects for both Asian and Caucasian faces. We investigated two proposed explanations for the holistic processing of other-race faces by Asian participants: (1) greater other-race exposure, (2) a general global processing bias. Holistic processing was tested using the part-whole task. Participants were living in predominantly own-race environments and other-race contact was evaluated. Despite reporting significantly greater contact with own-race than other-race people, Chinese participants displayed strong holistic processing for both Asian and Caucasian upright faces. In addition, Chinese participants showed no evidence of holistic processing for inverted faces arguing against a general global processing bias explanation. Caucasian participants, in line with previous studies, displayed stronger holistic processing for Caucasian than Asian upright faces. For inverted faces there were no race-of-face differences. These results are used to suggest that Asians may make more general use of face-specific mechanisms than Caucasians. PMID:23386840

Widespread inhibition of day-time ecosystem respiration and implications for eddy-covariance flux partitioning

NASA Astrophysics Data System (ADS)

Keenan, T. F.

2017-12-01

Global terrestrial ecosystems absorb about a third of anthropogenic emissions each year, due to the difference between two key processes: photosynthesis and respiration. Despite the importance of these two processes at the global scale, no direct measurement exists of either. Eddy-covariance (EC) measurements have been widely used as the closest `quasi-direct' observation, and the resulting estimates have been used to produce global budgets of photosynthesis and respiration. Recent research, however, suggests that current estimates may be biased by up to 25%, as the methods used to partition observed net carbon fluxes to photosynthesis and respiration do not take into account any inhibition of leaf respiration in light. Yet the prevalence of light-inhibition of leaf respiration remains debated, and impacts on global estimates of photosynthesis and respiration unquantified. Here, we use novel approaches to estimate the extent of light-inhibition across the global FLUXNET EC network, and find strong evidence for an inhibition effect on ecosystem respiration, which varies by season and plant functional type. We develop partitioning methods that allow for inhibition, and find that that diurnal patterns of ecosystem respiration might be markedly different than previously thought. The results call for the reevaluation of global terrestrial carbon cycle models, and also suggest that current global budgets of photosynthesis and respiration may be biased on the order of magnitude of anthropogenic fossil fuel emissions.

Attention Orienting in Response to Non-conscious Hierarchical Arrows: Individuals with Higher Autistic Traits Differ in Their Global/Local Bias.

PubMed

Laycock, Robin; Chan, Daniel; Crewther, Sheila G

2017-01-01

One aspect of the social communication impairments that characterize autism spectrum disorder (ASD) include reduced use of often subtle non-verbal social cues. People with ASD, and those with self-reported sub-threshold autistic traits, also show impairments in rapid visual processing of stimuli unrelated to social or emotional properties. Hence, this study sought to investigate whether perceptually non-conscious visual processing is related to autistic traits. A neurotypical sample of thirty young adults completed the Subthreshold Autism Trait Questionnaire and a Posner-like attention cueing task. Continuous Flash Suppression (CFS) was employed to render incongruous hierarchical arrow cues perceptually invisible prior to consciously presented targets. This was achieved via a 10 Hz masking stimulus presented to the dominant eye that suppressed information presented to the non-dominant eye. Non-conscious arrows consisted of local arrow elements pointing in one direction, and forming a global arrow shape pointing in the opposite direction. On each trial, the cue provided either a valid or invalid cue for the spatial location of the subsequent target, depending on which level (global or local) received privileged attention. A significant autism-trait group by global cue validity interaction indicated a difference in the extent of non-conscious local/global cueing between groups. Simple effect analyses revealed that whilst participants with lower autistic traits showed a global arrow cueing effect, those with higher autistic traits demonstrated a small local arrow cueing effect. These results suggest that non-conscious processing biases in local/global attention may be related to individual differences in autistic traits.

HESS Opinions "Should we apply bias correction to global and regional climate model data?"

NASA Astrophysics Data System (ADS)

Ehret, U.; Zehe, E.; Wulfmeyer, V.; Warrach-Sagi, K.; Liebert, J.

2012-04-01

Despite considerable progress in recent years, output of both Global and Regional Circulation Models is still afflicted with biases to a degree that precludes its direct use, especially in climate change impact studies. This is well known, and to overcome this problem bias correction (BC), i.e. the correction of model output towards observations in a post processing step for its subsequent application in climate change impact studies has now become a standard procedure. In this paper we argue that bias correction, which has a considerable influence on the results of impact studies, is not a valid procedure in the way it is currently used: it impairs the advantages of Circulation Models which are based on established physical laws by altering spatiotemporal field consistency, relations among variables and by violating conservation principles. Bias correction largely neglects feedback mechanisms and it is unclear whether bias correction methods are time-invariant under climate change conditions. Applying bias correction increases agreement of Climate Model output with observations in hind casts and hence narrows the uncertainty range of simulations and predictions without, however, providing a satisfactory physical justification. This is in most cases not transparent to the end user. We argue that this masks rather than reduces uncertainty, which may lead to avoidable forejudging of end users and decision makers. We present here a brief overview of state-of-the-art bias correction methods, discuss the related assumptions and implications, draw conclusions on the validity of bias correction and propose ways to cope with biased output of Circulation Models in the short term and how to reduce the bias in the long term. The most promising strategy for improved future Global and Regional Circulation Model simulations is the increase in model resolution to the convection-permitting scale in combination with ensemble predictions based on sophisticated approaches for ensemble perturbation. With this article, we advocate communicating the entire uncertainty range associated with climate change predictions openly and hope to stimulate a lively discussion on bias correction among the atmospheric and hydrological community and end users of climate change impact studies.

Global-mean BC lifetime as an indicator of model skill? Constraining the vertical aerosol distribution using aircraft observations

NASA Astrophysics Data System (ADS)

Lund, M. T.; Samset, B. H.; Skeie, R. B.; Berntsen, T.

2017-12-01

Several recent studies have used observations from the HIPPO flight campaigns to constrain the modeled vertical distribution of black carbon (BC) over the Pacific. Results indicate a relatively linear relationship between global-mean atmospheric BC residence time, or lifetime, and bias in current models. A lifetime of less than 5 days is necessary for models to reasonably reproduce these observations. This is shorter than what many global models predict, which will in turn affect their estimates of BC climate impacts. Here we use the chemistry-transport model OsloCTM to examine whether this relationship between global BC lifetime and model skill also holds for a broader a set of flight campaigns from 2009-2013 covering both remote marine and continental regions at a range of latitudes. We perform four sets of simulations with varying scavenging efficiency to obtain a spread in the modeled global BC lifetime and calculate the model error and bias for each campaign and region. Vertical BC profiles are constructed using an online flight simulator, as well by averaging and interpolating monthly mean model output, allowing us to quantify sampling errors arising when measurements are compared with model output at different spatial and temporal resolutions. Using the OsloCTM coupled with a microphysical aerosol parameterization, we investigate the sensitivity of modeled BC vertical distribution to uncertainties in the aerosol aging and scavenging processes in more detail. From this, we can quantify how model uncertainties in the BC life cycle propagate into uncertainties in its climate impacts. For most campaigns and regions, a short global-mean BC lifetime corresponds with the lowest model error and bias. On an aggregated level, sampling errors appear to be small, but larger differences are seen in individual regions. However, we also find that model-measurement discrepancies in BC vertical profiles cannot be uniquely attributed to uncertainties in a single process or parameter, at least in this model. Model development therefore needs to focus on improvements to individual processes, supported by a broad range of observational and experimental data, rather than tuning individual, effective parameters such as global BC lifetime.

Visuospatial Processing in Children with Autism: No Evidence for (Training-Resistant) Abnormalities

ERIC Educational Resources Information Center

Chabani, Ellahe; Hommel, Bernhard

2014-01-01

Individuals with autism spectrum disorders (ASDs) have been assumed to show evidence of abnormal visuospatial processing, which has been attributed to a failure to integrate local features into coherent global Gestalts and/or to a bias towards local processing. As the available data are based on baseline performance only, which does not provide…

Persistent states in vision break universality and time invariance

PubMed Central

Wexler, Mark; Duyck, Marianne; Mamassian, Pascal

2015-01-01

Studies of perception usually emphasize processes that are largely universal across observers and—except for short-term fluctuations—stationary over time. Here we test the universality and stationarity assumptions with two families of ambiguous visual stimuli. Each stimulus can be perceived in two different ways, parameterized by two opposite directions from a continuous circular variable. A large-sample study showed that almost all observers have preferred directions or biases, with directions lying within 90 degrees of the bias direction nearly always perceived and opposite directions almost never perceived. The biases differ dramatically from one observer to the next, and although nearly every bias direction occurs in the population, the population distributions of the biases are nonuniform, featuring asymmetric peaks in the cardinal directions. The biases for the two families of stimuli are independent and have distinct population distributions. Following external perturbations and spontaneous fluctuations, the biases decay over tens of seconds toward their initial values. Persistent changes in the biases are found on time scales of several minutes to 1 hour. On scales of days to months, the biases undergo a variety of dynamical processes such as drifts, jumps, and oscillations. The global statistics of a majority of these long-term time series are well modeled as random walk processes. The measurable fluctuations of these hitherto unknown degrees of freedom show that the assumptions of universality and stationarity in perception may be unwarranted and that models of perception must include both directly observable variables as well as covert, persistent states. PMID:26627250

Abnormalities in the Visual Processing of Viewing Complex Visual Stimuli Amongst Individuals With Body Image Concern.

PubMed

Duncum, A J F; Atkins, K J; Beilharz, F L; Mundy, M E

2016-01-01

Individuals with body dysmorphic disorder (BDD) and clinically concerning body-image concern (BIC) appear to possess abnormalities in the way they perceive visual information in the form of a bias towards local visual processing. As inversion interrupts normal global processing, forcing individuals to process locally, an upright-inverted stimulus discrimination task was used to investigate this phenomenon. We examined whether individuals with nonclinical, yet high levels of BIC would show signs of this bias, in the form of reduced inversion effects (i.e., increased local processing). Furthermore, we assessed whether this bias appeared for general visual stimuli or specifically for appearance-related stimuli, such as faces and bodies. Participants with high-BIC (n = 25) and low-BIC (n = 30) performed a stimulus discrimination task with upright and inverted faces, scenes, objects, and bodies. Unexpectedly, the high-BIC group showed an increased inversion effect compared to the low-BIC group, indicating perceptual abnormalities may not be present as local processing biases, as originally thought. There was no significant difference in performance across stimulus types, signifying that any visual processing abnormalities may be general rather than appearance-based. This has important implications for whether visual processing abnormalities are predisposing factors for BDD or develop throughout the disorder.

Correcting surface solar radiation of two data assimilation systems against FLUXNET observations in North America

NASA Astrophysics Data System (ADS)

Zhao, Lei; Lee, Xuhui; Liu, Shoudong

2013-09-01

Solar radiation at the Earth's surface is an important driver of meteorological and ecological processes. The objective of this study is to evaluate the accuracy of the reanalysis solar radiation produced by NARR (North American Regional Reanalysis) and MERRA (Modern-Era Retrospective Analysis for Research and Applications) against the FLUXNET measurements in North America. We found that both assimilation systems systematically overestimated the surface solar radiation flux on the monthly and annual scale, with an average bias error of +37.2 Wm-2 for NARR and of +20.2 Wm-2 for MERRA. The bias errors were larger under cloudy skies than under clear skies. A postreanalysis algorithm consisting of empirical relationships between model bias, a clearness index, and site elevation was proposed to correct the model errors. Results show that the algorithm can remove the systematic bias errors for both FLUXNET calibration sites (sites used to establish the algorithm) and independent validation sites. After correction, the average annual mean bias errors were reduced to +1.3 Wm-2 for NARR and +2.7 Wm-2 for MERRA. Applying the correction algorithm to the global domain of MERRA brought the global mean surface incoming shortwave radiation down by 17.3 W m-2 to 175.5 W m-2. Under the constraint of the energy balance, other radiation and energy balance terms at the Earth's surface, estimated from independent global data products, also support the need for a downward adjustment of the MERRA surface solar radiation.

Estimation of satellite position, clock and phase bias corrections

NASA Astrophysics Data System (ADS)

Henkel, Patrick; Psychas, Dimitrios; Günther, Christoph; Hugentobler, Urs

2018-05-01

Precise point positioning with integer ambiguity resolution requires precise knowledge of satellite position, clock and phase bias corrections. In this paper, a method for the estimation of these parameters with a global network of reference stations is presented. The method processes uncombined and undifferenced measurements of an arbitrary number of frequencies such that the obtained satellite position, clock and bias corrections can be used for any type of differenced and/or combined measurements. We perform a clustering of reference stations. The clustering enables a common satellite visibility within each cluster and an efficient fixing of the double difference ambiguities within each cluster. Additionally, the double difference ambiguities between the reference stations of different clusters are fixed. We use an integer decorrelation for ambiguity fixing in dense global networks. The performance of the proposed method is analysed with both simulated Galileo measurements on E1 and E5a and real GPS measurements of the IGS network. We defined 16 clusters and obtained satellite position, clock and phase bias corrections with a precision of better than 2 cm.

Validation and Expected Error Estimation of Suomi-NNP VIIRS Aerosol Optical Thickness and Angstrom Exponent with AERONET

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Kondragunta, Shobha; Laszlo, Istvan; Liu, Hongqing; Remer, Lorraine A.; Zhang, Hai; Superczynski, Stephen; Ciren, Pubu; Holben, Brent N.; Petrenko, Maksym

2016-01-01

The new-generation polar-orbiting operational environmental sensor, the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite, provides critical daily global aerosol observations. As older satellite sensors age out, the VIIRS aerosol product will become the primary observational source for global assessments of aerosol emission and transport, aerosol meteorological and climatic effects, air quality monitoring, and public health. To prove their validity and to assess their maturity level, the VIIRS aerosol products were compared to the spatiotemporally matched Aerosol Robotic Network (AERONET)measurements. Over land, the VIIRS aerosol optical thickness (AOT) environmental data record (EDR) exhibits an overall global bias against AERONET of 0.0008 with root-mean-square error(RMSE) of the biases as 0.12. Over ocean, the mean bias of VIIRS AOT EDR is 0.02 with RMSE of the biases as 0.06.The mean bias of VIIRS Ocean Angstrom Exponent (AE) EDR is 0.12 with RMSE of the biases as 0.57. The matchups between each product and its AERONET counterpart allow estimates of expected error in each case. Increased uncertainty in the VIIRS AOT and AE products is linked to specific regions, seasons, surface characteristics, and aerosol types, suggesting opportunity for future modifications as understanding of algorithm assumptions improves. Based on the assessment, the VIIRS AOT EDR over land reached Validated maturity beginning 23 January 2013; the AOT EDR and AE EDR over ocean reached Validated maturity beginning 2 May 2012, excluding the processing error period 15 October to 27 November 2012. These findings demonstrate the integrity and usefulness of the VIIRS aerosol products that will transition from S-NPP to future polar-orbiting environmental satellites in the decades to come and become the standard global aerosol data set as the previous generations missions come to an end.

Spatial Frequency Priming of Scene Perception in Adolescents with and without ASD

ERIC Educational Resources Information Center

Vanmarcke, Steven; Noens, Ilse; Steyaert, Jean; Wagemans, Johan

2017-01-01

While most typically developing (TD) participants have a coarse-to-fine processing style, people with autism spectrum disorder (ASD) seem to be less globally and more locally biased when processing visual information. The stimulus-specific spatial frequency content might be directly relevant to determine this temporal hierarchy of visual…

The Rubber Hand Illusion Reveals Proprioceptive and Sensorimotor Differences in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Paton, Bryan; Hohwy, Jakob; Enticott, Peter G.

2012-01-01

Autism spectrum disorder (ASD) is characterised by differences in unimodal and multimodal sensory and proprioceptive processing, with complex biases towards local over global processing. Many of these elements are implicated in versions of the rubber hand illusion (RHI), which were therefore studied in high-functioning individuals with ASD and a…

Effects of Inventory Bias on Landslide Susceptibility Calculations

NASA Technical Reports Server (NTRS)

Stanley, T. A.; Kirschbaum, D. B.

2017-01-01

Many landslide inventories are known to be biased, especially inventories for large regions such as Oregon's SLIDO or NASA's Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modeling landslide susceptibility with heavily biased inventories.

Effects of Inventory Bias on Landslide Susceptibility Calculations

NASA Technical Reports Server (NTRS)

Stanley, Thomas; Kirschbaum, Dalia B.

2017-01-01

Many landslide inventories are known to be biased, especially inventories for large regions such as Oregons SLIDO or NASAs Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modelling landslide susceptibility with heavily biased inventories.

Who Learns More? Cultural Differences in Implicit Sequence Learning

PubMed Central

Fu, Qiufang; Dienes, Zoltan; Shang, Junchen; Fu, Xiaolan

2013-01-01

Background It is well documented that East Asians differ from Westerners in conscious perception and attention. However, few studies have explored cultural differences in unconscious processes such as implicit learning. Methodology/Principal Findings The global-local Navon letters were adopted in the serial reaction time (SRT) task, during which Chinese and British participants were instructed to respond to global or local letters, to investigate whether culture influences what people acquire in implicit sequence learning. Our results showed that from the beginning British expressed a greater local bias in perception than Chinese, confirming a cultural difference in perception. Further, over extended exposure, the Chinese learned the target regularity better than the British when the targets were global, indicating a global advantage for Chinese in implicit learning. Moreover, Chinese participants acquired greater unconscious knowledge of an irrelevant regularity than British participants, indicating that the Chinese were more sensitive to contextual regularities than the British. Conclusions/Significance The results suggest that cultural biases can profoundly influence both what people consciously perceive and unconsciously learn. PMID:23940773

The Role of Musical Experience in Hemispheric Lateralization of Global and Local Auditory Processing.

PubMed

Black, Emily; Stevenson, Jennifer L; Bish, Joel P

2017-08-01

The global precedence effect is a phenomenon in which global aspects of visual and auditory stimuli are processed before local aspects. Individuals with musical experience perform better on all aspects of auditory tasks compared with individuals with less musical experience. The hemispheric lateralization of this auditory processing is less well-defined. The present study aimed to replicate the global precedence effect with auditory stimuli and to explore the lateralization of global and local auditory processing in individuals with differing levels of musical experience. A total of 38 college students completed an auditory-directed attention task while electroencephalography was recorded. Individuals with low musical experience responded significantly faster and more accurately in global trials than in local trials regardless of condition, and significantly faster and more accurately when pitches traveled in the same direction (compatible condition) than when pitches traveled in two different directions (incompatible condition) consistent with a global precedence effect. In contrast, individuals with high musical experience showed less of a global precedence effect with regards to accuracy, but not in terms of reaction time, suggesting an increased ability to overcome global bias. Further, a difference in P300 latency between hemispheres was observed. These findings provide a preliminary neurological framework for auditory processing of individuals with differing degrees of musical experience.

Precocious realists: perceptual and cognitive characteristics associated with drawing talent in non-autistic children

PubMed Central

Drake, Jennifer E.; Winner, Ellen

2009-01-01

A local processing bias in the block design task and in drawing strategy has been used to account for realistic drawing skill in individuals with autism. We investigated whether the same kind of local processing bias is seen in typically developing children with unusual skill in realistic graphic representation. Forty-three 5–11-year-olds who drew a still life completed a version of the block design task in both standard and segmented form, were tested for their memory for the block design items, and were given the Kaufmann Brief Intelligence Test-II. Children were classified as gifted, moderately gifted or typical on the basis of the level of realism in their drawings. Similar to autistic individuals, the gifted group showed a local processing bias in the block design task. But unlike autistic individuals, the gifted group showed a global advantage in the visual memory task and did not use a local drawing strategy; in addition, their graphic realism skill was related to verbal IQ. Differences in the extent of local processing bias in autistic and typically developing children with drawing talent are discussed. PMID:19528030

An Observation-based Assessment of Instrument Requirements for a Future Precipitation Process Observing System

NASA Astrophysics Data System (ADS)

Nelson, E.; L'Ecuyer, T. S.; Wood, N.; Smalley, M.; Kulie, M.; Hahn, W.

2017-12-01

Global models exhibit substantial biases in the frequency, intensity, duration, and spatial scales of precipitation systems. Much of this uncertainty stems from an inadequate representation of the processes by which water is cycled between the surface and atmosphere and, in particular, those that govern the formation and maintenance of cloud systems and their propensity to form the precipitation. Progress toward improving precipitation process models requires observing systems capable of quantifying the coupling between the ice content, vertical mass fluxes, and precipitation yield of precipitating cloud systems. Spaceborne multi-frequency, Doppler radar offers a unique opportunity to address this need but the effectiveness of such a mission is heavily dependent on its ability to actually observe the processes of interest in the widest possible range of systems. Planning for a next generation precipitation process observing system should, therefore, start with a fundamental evaluation of the trade-offs between sensitivity, resolution, sampling, cost, and the overall potential scientific yield of the mission. Here we provide an initial assessment of the scientific and economic trade-space by evaluating hypothetical spaceborne multi-frequency radars using a combination of current real-world and model-derived synthetic observations. Specifically, we alter the field of view, vertical resolution, and sensitivity of a hypothetical Ka- and W-band radar system and propagate those changes through precipitation detection and intensity retrievals. The results suggest that sampling biases introduced by reducing sensitivity disproportionately affect the light rainfall and frozen precipitation regimes that are critical for warm cloud feedbacks and ice sheet mass balance, respectively. Coarser spatial resolution observations introduce regime-dependent biases in both precipitation occurrence and intensity that depend on cloud regime, with even the sign of the bias varying within a single storm system. It is suggested that the next generation spaceborne radar have a minimum sensitivity of -5 dBZ and spatial resolution of at least 3 km at all frequencies to adequately sample liquid and ice phase precipitation processes globally.

Time determination for spacecraft users of the Navstar Global Positioning System /GPS/

NASA Technical Reports Server (NTRS)

Grenchik, T. J.; Fang, B. T.

1977-01-01

Global Positioning System (GPS) navigation is performed by time measurements. A description is presented of a two body model of spacecraft motion. Orbit determination is the process of inferring the position, velocity, and clock offset of the user from measurements made of the user motion in the Newtonian coordinate system. To illustrate the effect of clock errors and the accuracy with which the user spacecraft time and orbit may be determined, a low-earth-orbit spacecraft (Seasat) as tracked by six Phase I GPS space vehicles is considered. The obtained results indicate that in the absence of unmodeled dynamic parameter errors clock biases may be determined to the nanosecond level. There is, however, a high correlation between the clock bias and the uncertainty in the gravitational parameter GM, i.e., the product of the universal gravitational constant and the total mass of the earth. It is, therefore, not possible to determine clock bias to better than 25 nanosecond accuracy in the presence of a gravitational error of one part per million.

Level set segmentation of medical images based on local region statistics and maximum a posteriori probability.

PubMed

Cui, Wenchao; Wang, Yi; Lei, Tao; Fan, Yangyu; Feng, Yan

2013-01-01

This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Bayes' rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.

Intercomparison and validation of the mixed layer depth fields of global ocean syntheses

NASA Astrophysics Data System (ADS)

Toyoda, Takahiro; Fujii, Yosuke; Kuragano, Tsurane; Kamachi, Masafumi; Ishikawa, Yoichi; Masuda, Shuhei; Sato, Kanako; Awaji, Toshiyuki; Hernandez, Fabrice; Ferry, Nicolas; Guinehut, Stéphanie; Martin, Matthew J.; Peterson, K. Andrew; Good, Simon A.; Valdivieso, Maria; Haines, Keith; Storto, Andrea; Masina, Simona; Köhl, Armin; Zuo, Hao; Balmaseda, Magdalena; Yin, Yonghong; Shi, Li; Alves, Oscar; Smith, Gregory; Chang, You-Soon; Vernieres, Guillaume; Wang, Xiaochun; Forget, Gael; Heimbach, Patrick; Wang, Ou; Fukumori, Ichiro; Lee, Tong

2017-08-01

Intercomparison and evaluation of the global ocean surface mixed layer depth (MLD) fields estimated from a suite of major ocean syntheses are conducted. Compared with the reference MLDs calculated from individual profiles, MLDs calculated from monthly mean and gridded profiles show negative biases of 10-20 m in early spring related to the re-stratification process of relatively deep mixed layers. Vertical resolution of profiles also influences the MLD estimation. MLDs are underestimated by approximately 5-7 (14-16) m with the vertical resolution of 25 (50) m when the criterion of potential density exceeding the 10-m value by 0.03 kg m-3 is used for the MLD estimation. Using the larger criterion (0.125 kg m-3) generally reduces the underestimations. In addition, positive biases greater than 100 m are found in wintertime subpolar regions when MLD criteria based on temperature are used. Biases of the reanalyses are due to both model errors and errors related to differences between the assimilation methods. The result shows that these errors are partially cancelled out through the ensemble averaging. Moreover, the bias in the ensemble mean field of the reanalyses is smaller than in the observation-only analyses. This is largely attributed to comparably higher resolutions of the reanalyses. The robust reproduction of both the seasonal cycle and interannual variability by the ensemble mean of the reanalyses indicates a great potential of the ensemble mean MLD field for investigating and monitoring upper ocean processes.

Processing of musical structure by high-functioning adolescents with autism spectrum disorders.

PubMed

Quintin, Eve-Marie; Bhatara, Anjali; Poissant, Hélène; Fombonne, Eric; Levitin, Daniel J

2013-01-01

Enhanced pitch perception and memory have been cited as evidence of a local processing bias in autism spectrum disorders (ASD). This bias is argued to account for enhanced perceptual functioning ( Mottron & Burack, 2001 ; Mottron, Dawson, Soulières, Hubert, & Burack, 2006 ) and central coherence theories of ASD ( Frith, 1989 ; Happé & Frith, 2006 ). A local processing bias confers a different cognitive style to individuals with ASD ( Happé, 1999 ), which accounts in part for their good visuospatial and visuoconstructive skills. Here, we present analogues in the auditory domain, audiotemporal or audioconstructive processing, which we assess using a novel experimental task: a musical puzzle. This task evaluates the ability of individuals with ASD to process temporal sequences of musical events as well as various elements of musical structure and thus indexes their ability to employ a global processing style. Musical structures created and replicated by children and adolescents with ASD (10-19 years old) and typically developing children and adolescents (7-17 years old) were found to be similar in global coherence. Presenting a musical template for reference increased accuracy equally for both groups, with performance associated to performance IQ and short-term auditory memory. The overall pattern of performance was similar for both groups; some puzzles were easier than others and this was the case for both groups. Task performance was further found to be correlated with the ability to perceive musical emotions, more so for typically developing participants. Findings are discussed in light of the empathizing-systemizing theory of ASD ( Baron-Cohen, 2009 ) and the importance of describing the strengths of individuals with ASD ( Happé, 1999 ; Heaton, 2009 ).

Tuning a climate model using nudging to reanalysis.

NASA Astrophysics Data System (ADS)

Cheedela, S. K.; Mapes, B. E.

2014-12-01

Tuning a atmospheric general circulation model involves a daunting task of adjusting non-observable parameters to adjust the mean climate. These parameters arise from necessity to describe unresolved flow through parametrizations. Tuning a climate model is often done with certain set of priorities, such as global mean temperature, net top of the atmosphere radiation. These priorities are hard enough to reach let alone reducing systematic biases in the models. The goal of currently study is to explore alternate ways to tune a climate model to reduce some systematic biases that can be used in synergy with existing efforts. Nudging a climate model to a known state is a poor man's inverse of tuning process described above. Our approach involves nudging the atmospheric model to state of art reanalysis fields thereby providing a balanced state with respect to the global mean temperature and winds. The tendencies derived from nudging are negative of errors from physical parametrizations as the errors from dynamical core would be small. Patterns of nudging are compared to the patterns of different physical parametrizations to decipher the cause for certain biases in relation to tuning parameters. This approach might also help in understanding certain compensating errors that arise from tuning process. ECHAM6 is a comprehensive general model, also used in recent Coupled Model Intercomparision Project(CMIP5). The approach used to tune it and effect of certain parameters that effect its mean climate are reported clearly, hence it serves as a benchmark for our approach. Our planned experiments include nudging ECHAM6 atmospheric model to European Center Reanalysis (ERA-Interim) and reanalysis from National Center for Environmental Prediction (NCEP) and decipher choice of certain parameters that lead to systematic biases in its simulations. Of particular interest are reducing long standing biases related to simulation of Asian summer monsoon.

The effect of sadness on global-local processing.

PubMed

von Mühlenen, Adrian; Bellaera, Lauren; Singh, Amrendra; Srinivasan, Narayanan

2018-05-04

Gable and Harmon-Jones (Psychological Science, 21(2), 211-215, 2010) reported that sadness broadens attention in a global-local letter task. This finding provided the key test for their motivational intensity account, which states that the level of spatial processing is not determined by emotional valence, but by motivational intensity. However, their finding is at odds with several other studies, showing no effect, or even a narrowing effect of sadness on attention. This paper reports two attempts to replicate the broadening effect of sadness on attention. Both experiments used a global-local letter task, but differed in terms of emotion induction: Experiment 1 used the same pictures as Gable and Harmon-Jones, taken from the IAPS dataset; Experiment 2 used a sad video underlaid with sad music. Results showed a sadness-specific global advantage in the error rates, but not in the reaction times. The same null results were also found in a South-Asian sample in both experiments, showing that effects on global/local processing were not influenced by a culturally related processing bias.

Attentional states influence early neural responses associated with motivational processes: local vs. global attentional scope and N1 amplitude to appetitive stimuli.

PubMed

Gable, Philip A; Harmon-Jones, Eddie

2011-05-01

Positive affects vary in the degree with which they are associated with approach motivation, the drive to approach an object or a goal. High approach-motivated positive affects cause a narrowing of attention, whereas low approach-motivated positive affects causes a broadening of attention. The current study was designed to extend this work by examining whether the relationship between motivation and attentional bias was bi-directional. Specifically, the experiment investigated whether a manipulated local attentional scope would cause greater approach motivational processing than a global attentional scope as measured by neural processes as early as 100 ms. As compared to a global attentional scope, a local attentional scope caused greater neural processing associated with approach motivation as measured by the N1 to appetitive pictures. Copyright © 2011 Elsevier B.V. All rights reserved.

Omens of coupled model biases in the CMIP5 AMIP simulations

NASA Astrophysics Data System (ADS)

Găinuşă-Bogdan, Alina; Hourdin, Frédéric; Traore, Abdoul Khadre; Braconnot, Pascale

2018-02-01

Despite decades of efforts and improvements in the representation of processes as well as in model resolution, current global climate models still suffer from a set of important, systematic biases in sea surface temperature (SST), not much different from the previous generation of climate models. Many studies have looked at errors in the wind field, cloud representation or oceanic upwelling in coupled models to explain the SST errors. In this paper we highlight the relationship between latent heat flux (LH) biases in forced atmospheric simulations and the SST biases models develop in coupled mode, at the scale of the entire intertropical domain. By analyzing 22 pairs of forced atmospheric and coupled ocean-atmosphere simulations from the CMIP5 database, we show a systematic, negative correlation between the spatial patterns of these two biases. This link between forced and coupled bias patterns is also confirmed by two sets of dedicated sensitivity experiments with the IPSL-CM5A-LR model. The analysis of the sources of the atmospheric LH bias pattern reveals that the near-surface wind speed bias dominates the zonal structure of the LH bias and that the near-surface relative humidity dominates the east-west contrasts.

Using Ensemble Short-Term Initialized Coupled NASA GEOS5 Climate Model Integrations to Study Convective Bias Growth

NASA Technical Reports Server (NTRS)

Cohen, Charlie; Robertson, Franklin; Molod, Andrea

2014-01-01

The representation of convective processes, particularly deep convection in the tropics, remains a persistent problem in climate models. In fact structural biases in the distribution of tropical rainfall in the CMIP5 models is hardly different than that of the CMIP3 versions. Given that regional climate change at higher latitudes is sensitive to the configuration of tropical forcing, this persistent bias is a major issue for the credibility of climate change projections. In this study we use model output from integrations of the NASA Global Earth Observing System Five (GEOS5) climate modeling system to study the evolution of biases in the location and intensity of convective processes. We take advantage of a series of hindcast experiments done in support of the US North American Multi-Model Ensemble (NMME) initiative. For these experiments a nine-month forecast using a coupled model configuration is made approximately every five days over the past 30 years. Each forecast is started with an updated analysis of the ocean, atmosphere and land states. For a given calendar month we have approximately 180 forecasts with daily means of various quantities. These forecasts can be averaged to essentially remove "weather scales" and highlight systematic errors as they evolve. Our primary question is to ask how the spatial structure of daily mean precipitation over the tropics evolves from the initial state and what physical processes are involved. Errors in parameterized convection, various water and energy fluxes and the divergent circulation are found to set up on fast time scales (order five days) compared to errors in the ocean, although SST changes can be non-negligible over that time. For the month of June the difference between forecast day five versus day zero precipitation looks quite similar to the difference between the June precipitation climatology and that from the Global Precipitation Climatology Project (GPCP). We focus much of our analysis on the influence of SST gradients, associated PBL baroclinicity enabled by turbulent mixing, the ensuing PBL moisture convergence, and how changes in these processes relate to convective precipitation bias growth over this short period.

Using Ensemble Short-Term Initialized Coupled NASA GEOS5 Climate Model Integrations to Study Convective Bias Growth

NASA Astrophysics Data System (ADS)

Robertson, F. R.; Cohen, C.

2014-12-01

The representation of convective processes, particularly deep convection in the tropics, remains a persistent problem in climate models. In fact structural biases in the distribution of tropical rainfall in the CMIP5 models is hardly different than that of the CMIP3 versions. Given that regional climate change at higher latitudes is sensitive to the configuration of tropical forcing, this persistent bias is a major issue for the credibility of climate change projections. In this study we use model output from integrations of the NASA Global Earth Observing System Five (GEOS5) climate modeling system to study the evolution of biases in the location and intensity of convective processes. We take advantage of a series of hindcast experiments done in support of the US North American Multi-Model Ensemble (NMME) initiative. For these experiments a nine-month forecast using a coupled model configuration is made approximately every five days over the past 30 years. Each forecast is started with an updated analysis of the ocean, atmosphere and land states. For a given calendar month we have approximately 180 forecasts with daily means of various quantities. These forecasts can be averaged to essentially remove "weather scales" and highlight systematic errors as they evolve. Our primary question is to ask how the spatial structure of daily mean precipitation over the tropics evolves from the initial state and what physical processes are involved. Errors in parameterized convection, various water and energy fluxes and the divergent circulation are found to set up on fast time scales (order five days) compared to errors in the ocean, although SST changes can be non-negligible over that time. For the month of June the difference between forecast day five versus day zero precipitation looks quite similar to the difference between the June precipitation climatology and that from the Global Precipitation Climatology Project (GPCP). We focus much of our analysis on the influence of SST gradients, associated PBL baroclinicity enabled by turbulent mixing, the ensuing PBL moisture convergence, and how changes in these processes relate to convective precipitation bias growth over this short period.

Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

NASA Technical Reports Server (NTRS)

Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

2015-01-01

Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

EMC Global Climate And Weather Modeling Branch Personnel

Science.gov Websites

Comparison Statistics which includes: NCEP Raw and Bias-Corrected Ensemble Domain Averaged Bias NCEP Raw and Bias-Corrected Ensemble Domain Averaged Bias Reduction (Percents) CMC Raw and Bias-Corrected Control Forecast Domain Averaged Bias CMC Raw and Bias-Corrected Control Forecast Domain Averaged Bias Reduction

Working memory, perceptual priming, and the perception of hierarchical forms: opposite effects of priming and working memory without memory refreshing.

PubMed

Kim, Jeong-Im; Humphreys, Glyn W

2010-08-01

Previous research has shown that stimuli held in working memory (WM) can influence spatial attention. Using Navon stimuli, we explored whether and how items in WM affect the perception of visual targets at local and global levels in compound letters. Participants looked for a target letter presented at a local or global level while holding a regular block letter as a memory item. An effect of holding the target's identity in WM was found. When memory items and targets were the same, performance was better than in a neutral condition when the memory item did not appear in the hierarchical letter (a benefit from valid cuing). When the memory item matched the distractor in the hierarchical stimulus, performance was worse than in the neutral baseline (a cost on invalid trials). These effects were greatest when the WM cue matched the global level of the hierarchical stimulus, suggesting that WM biases attention to the global level of form. Interestingly, in a no-memory priming condition, target perception was faster in the invalid condition than in the neutral baseline, reversing the effect in the WM condition. A further control experiment ruled out the effects of WM being due to participants' refreshing their memory from the hierarchical stimulus display. The data show that information in WM biases the selection of hierarchical forms, whereas priming does not. Priming alters the perceptual processing of repeated stimuli without biasing attention.

Evaluation of four global reanalysis products using in situ observations in the Amundsen Sea Embayment, Antarctica

NASA Astrophysics Data System (ADS)

Jones, R. W.; Renfrew, I. A.; Orr, A.; Webber, B. G. M.; Holland, D. M.; Lazzara, M. A.

2016-06-01

The glaciers within the Amundsen Sea Embayment (ASE), West Antarctica, are amongst the most rapidly retreating in Antarctica. Meteorological reanalysis products are widely used to help understand and simulate the processes causing this retreat. Here we provide an evaluation against observations of four of the latest global reanalysis products within the ASE region—the European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-I), Japanese 55-year Reanalysis (JRA-55), Climate Forecast System Reanalysis (CFSR), and Modern Era Retrospective-Analysis for Research and Applications (MERRA). The observations comprise data from four automatic weather stations (AWSs), three research vessel cruises, and a new set of 38 radiosondes all within the period 2009-2014. All four reanalyses produce 2 m temperature fields that are colder than AWS observations, with the biases varying from approximately -1.8°C (ERA-I) to -6.8°C (MERRA). Over the Amundsen Sea, spatially averaged summertime biases are between -0.4°C (JRA-55) and -2.1°C (MERRA) with notably larger cold biases close to the continent (up to -6°C) in all reanalyses. All four reanalyses underestimate near-surface wind speed at high wind speeds (>15 m s-1) and exhibit dry biases and relatively large root-mean-square errors (RMSE) in specific humidity. A comparison to the radiosonde soundings shows that the cold, dry bias at the surface extends into the lower troposphere; here ERA-I and CFSR reanalyses provide the most accurate profiles. The reanalyses generally contain larger temperature and humidity biases, (and RMSE) when a temperature inversion is observed, and contain larger wind speed biases (~2 to 3 m s-1), when a low-level jet is observed.

A review of earth observation using mobile personal communication devices

NASA Astrophysics Data System (ADS)

Ferster, Colin J.; Coops, Nicholas C.

2013-02-01

Earth observation using mobile personal communication devices (MPCDs) is a recent advance with considerable promise for acquiring important and timely measurements. Globally, over 5 billion people have access to mobile phones, with an increasing proportion having access to smartphones with capabilities such as a camera, microphone, global positioning system (GPS), data storage, and networked data transfer. Scientists can view these devices as embedded sensors with the potential to take measurements of the Earth's surface and processes. To advance the state of Earth observation using MPCDs, scientists need to consider terms and concepts, from a broad range of disciplines including citizen science, image analysis, and computer vision. In this paper, as a result of our literature review, we identify a number of considerations for Earth observation using MPCDs such as methods of field collection, collecting measurements over broad areas, errors and biases, data processing, and accessibility of data. Developing effective frameworks for mobile data collection with public participation and strategies for minimizing bias, in combination with advancements in image processing techniques, will offer opportunities to collect Earth sensing data across a range of scales and perspectives, complimenting airborne and spaceborne remote sensing measurements.

Phasic alertness enhances processing of face and non-face stimuli in congenital prosopagnosia.

PubMed

Tanzer, Michal; Weinbach, Noam; Mardo, Elite; Henik, Avishai; Avidan, Galia

2016-08-01

Congenital prosopagnosia (CP) is a severe face processing impairment that occurs in the absence of any obvious brain damage and has often been associated with a more general deficit in deriving holistic relations between facial features or even between non-face shape dimensions. Here we further characterized this deficit and examined a potential way to ameliorate it. To this end we manipulated phasic alertness using alerting cues previously shown to modulate attention and enhance global processing of visual stimuli in normal observers. Specifically, we first examined whether individuals with CP, similarly to controls, would show greater global processing when exposed to an alerting cue in the context of a non-facial task (Navon global/local task). We then explored the effect of an alerting cue on face processing (upright/inverted face discrimination). Confirming previous findings, in the absence of alerting cues, controls showed a typical global bias in the Navon task and an inversion effect indexing holistic processing in the upright/inverted task, while CP failed to show these effects. Critically, when alerting cues preceded the experimental trials, both groups showed enhanced global interference and a larger inversion effect. These results suggest that phasic alertness may modulate visual processing and consequently, affect global/holistic perception. Hence, these findings further reinforce the notion that global/holistic processing may serve as a possible mechanism underlying the face processing deficit in CP. Moreover, they imply a possible route for enhancing face processing in individuals with CP and thus shed new light on potential amelioration of this disorder. Copyright © 2016 Elsevier Ltd. All rights reserved.

Global longitudinal strain software upgrade: Implications for intervendor consistency and longitudinal imaging studies.

PubMed

Castel, Anne-Laure; Menet, Aymeric; Ennezat, Pierre-Vladimir; Delelis, François; Le Goffic, Caroline; Binda, Camille; Guerbaai, Raphaëlle-Ashley; Levy, Franck; Graux, Pierre; Tribouilloy, Christophe; Maréchaux, Sylvestre

2016-01-01

Speckle tracking can be used to measure left ventricular global longitudinal strain (GLS). To study the effect of speckle tracking software product upgrades on GLS values and intervendor consistency. Subjects (patients or healthy volunteers) underwent systematic echocardiography with equipment from Philips and GE, without a change in their position. Off-line post-processing for GLS assessment was performed with the former and most recent upgrades from these two vendors (Philips QLAB 9.0 and 10.2; GE EchoPAC 12.1 and 13.1.1). GLS was obtained in three myocardial layers with EchoPAC 13.1.1. Intersoftware and intervendor consistency was assessed. Interobserver variability was tested in a subset of patients. Among 73 subjects (65 patients and 8 healthy volunteers), absolute values of GLS were higher with QLAB 10.2 compared with 9.0 (intraclass correlation coefficient [ICC]: 0.88; bias: 2.2%). Agreement between EchoPAC 13.1.1 and 12.1 varied by myocardial layer (13.1.1 only): midwall (ICC: 0.95; bias: -1.1%), endocardium (ICC: 0.93; bias: 1.6%) and epicardial (ICC: 0.80; bias: -3.3%). Although GLS was comparable for QLAB 9.0 versus EchoPAC 12.1 (ICC: 0.95; bias: 0.5%), the agreement was lower between QLAB 10.2 and EchoPAC 13.1.1 endocardial (ICC: 0.91; bias: 1.1%), midwall (ICC: 0.73; bias: 3.9%) and epicardial (ICC: 0.54; bias: 6.0%). Interobserver variability of all software products in a subset of 20 patients was excellent (ICC: 0.97-0.99; bias: -0.8 to 1.0%). Upgrades of speckle tracking software may be associated with significant changes in GLS values, which could affect intersoftware and intervendor consistency. This finding has important clinical implications for the longitudinal follow-up of patients with speckle tracking echocardiography. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Stimulus- and state-dependence of systematic bias in spatial attention: additive effects of stimulus-size and time-on-task.

PubMed

Benwell, Christopher S Y; Harvey, Monika; Gardner, Stephanie; Thut, Gregor

2013-03-01

Systematic biases in spatial attention are a common finding. In the general population, a systematic leftward bias is typically observed (pseudoneglect), possibly as a consequence of right hemisphere dominance for visuospatial attention. However, this leftward bias can cross-over to a systematic rightward bias with changes in stimulus and state factors (such as line length and arousal). The processes governing these changes are still unknown. Here we tested models of spatial attention as to their ability to account for these effects. To this end, we experimentally manipulated both stimulus and state factors, while healthy participants performed a computerized version of a landmark task. State was manipulated by time-on-task (>1 h) leading to increased fatigue and a reliable left- to rightward shift in spatial bias. Stimulus was manipulated by presenting either long or short lines which was associated with a shift of subjective midpoint from a reliable leftward bias for long to a more rightward bias for short lines. Importantly, we found time-on-task and line length effects to be additive suggesting a common denominator for line bisection across all conditions, which is in disagreement with models that assume that bisection decisions in long and short lines are governed by distinct processes (Magnitude estimation vs Global/local distinction). Our findings emphasize the dynamic rather than static nature of spatial biases in midline judgement. They are best captured by theories of spatial attention positing that spatial bias is flexibly modulated, and subject to inter-hemispheric balance which can change over time or conditions to accommodate task demands or reflect fatigue. Copyright © 2012 Elsevier Ltd. All rights reserved.

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

NASA Astrophysics Data System (ADS)

Fan, Tianyi; Liu, Xiaohong; Ma, Po-Lun; Zhang, Qiang; Li, Zhanqing; Jiang, Yiquan; Zhang, Fang; Zhao, Chuanfeng; Yang, Xin; Wu, Fang; Wang, Yuying

2018-02-01

Global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results are compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22-28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be -5.02, -18.47, and 13.45 W m-2, respectively, over eastern China, which are enhanced by -0.91, -3.48, and 2.57 W m-2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.

Global high-resolution simulations of tropospheric nitrogen dioxide using CHASER V4.0

NASA Astrophysics Data System (ADS)

Sekiya, Takashi; Miyazaki, Kazuyuki; Ogochi, Koji; Sudo, Kengo; Takigawa, Masayuki

2018-03-01

We evaluate global tropospheric nitrogen dioxide (NO2) simulations using the CHASER V4.0 global chemical transport model (CTM) at horizontal resolutions of 0.56, 1.1, and 2.8°. Model evaluation was conducted using satellite tropospheric NO2 retrievals from the Ozone Monitoring Instrument (OMI) and the Global Ozone Monitoring Experiment-2 (GOME-2) and aircraft observations from the 2014 Front Range Air Pollution and Photochemistry Experiment (FRAPPÉ). Agreement against satellite retrievals improved greatly at 1.1 and 0.56° resolutions (compared to 2.8° resolution) over polluted and biomass burning regions. The 1.1° simulation generally captured the regional distribution of the tropospheric NO2 column well, whereas 0.56° resolution was necessary to improve the model performance over areas with strong local sources, with mean bias reductions of 67 % over Beijing and 73 % over San Francisco in summer. Validation using aircraft observations indicated that high-resolution simulations reduced negative NO2 biases below 700 hPa over the Denver metropolitan area. These improvements in high-resolution simulations were attributable to (1) closer spatial representativeness between simulations and observations and (2) better representation of large-scale concentration fields (i.e., at 2.8°) through the consideration of small-scale processes. Model evaluations conducted at 0.5 and 2.8° bin grids indicated that the contributions of both these processes were comparable over most polluted regions, whereas the latter effect (2) made a larger contribution over eastern China and biomass burning areas. The evaluations presented in this paper demonstrate the potential of using a high-resolution global CTM for studying megacity-scale air pollutants across the entire globe, potentially also contributing to global satellite retrievals and chemical data assimilation.

Implications of holistic face processing in autism and schizophrenia

PubMed Central

Watson, Tamara L.

2013-01-01

People with autism and schizophrenia have been shown to have a local bias in sensory processing and face recognition difficulties. A global or holistic processing strategy is known to be important when recognizing faces. Studies investigating face recognition in these populations are reviewed and show that holistic processing is employed despite lower overall performance in the tasks used. This implies that holistic processing is necessary but not sufficient for optimal face recognition and new avenues for research into face recognition based on network models of autism and schizophrenia are proposed. PMID:23847581

Calibration of the clock-phase biases of GNSS networks: the closure-ambiguity approach

NASA Astrophysics Data System (ADS)

Lannes, A.; Prieur, J.-L.

2013-08-01

In global navigation satellite systems (GNSS), the problem of retrieving clock-phase biases from network data has a basic rank defect. We analyse the different ways of removing this rank defect, and define a particular strategy for obtaining these phase biases in a standard form. The minimum-constrained problem to be solved in the least-squares (LS) sense depends on some integer vector which can be fixed in an arbitrary manner. We propose to solve the problem via an undifferenced approach based on the notion of closure ambiguity. We present a theoretical justification of this closure-ambiguity approach (CAA), and the main elements for a practical implementation. The links with other methods are also established. We analyse all those methods in a unified interpretative framework, and derive functional relations between the corresponding solutions and our CAA solution. This could be interesting for many GNSS applications like real-time kinematic PPP for instance. To compare the methods providing LS estimates of clock-phase biases, we define a particular solution playing the role of reference solution. For this solution, when a phase bias is estimated for the first time, its fractional part is confined to the one-cycle width interval centred on zero; the integer-ambiguity set is modified accordingly. Our theoretical study is illustrated with some simple and generic examples; it could have applications in data processing of most GNSS networks, and particularly global networks using GPS, Glonass, Galileo, or BeiDou/Compass satellites.

Analyzing Source Apportioned Methane in Northern California During DISCOVER-AQ-CA Using Airborne Measurements and Model Simulations

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.

2014-01-01

This study analyzes source apportioned methane (CH4) emissions and atmospheric concentrations in northern California during the Discover-AQ-CA field campaign using airborne measurement data and model simulations. Source apportioned CH4 emissions from the Emissions Database for Global Atmospheric Research (EDGAR) version 4.2 were applied in the 3-D chemical transport model GEOS-Chem and analyzed using airborne measurements taken as part of the Alpha Jet Atmospheric eXperiment over the San Francisco Bay Area (SFBA) and northern San Joaquin Valley (SJV). During the time period of the Discover-AQ-CA field campaign EDGAR inventory CH4 emissions were 5.30 Gg/day (Gg 1.0 109 grams) (equating to 1.9 103 Gg/yr) for all of California. According to EDGAR, the SFBA and northern SJV region contributes 30 of total emissions from California. Source apportionment analysis during this study shows that CH4 concentrations over this area of northern California are largely influenced by global emissions from wetlands and local/global emissions from gas and oil production and distribution, waste treatment processes, and livestock management. Model simulations, using EDGAR emissions, suggest that the model under-estimates CH4 concentrations in northern California (average normalized mean bias (NMB) -5 and linear regression slope 0.25). The largest negative biases in the model were calculated on days when hot spots of local emission sources were measured and atmospheric CH4 concentrations reached values 3.0 parts per million (model NMB -10). Sensitivity emission studies conducted during this research suggest that local emissions of CH4 from livestock management processes are likely the primary source of the negative model bias. These results indicate that a variety, and larger quantity, of measurement data needs to be obtained and additional research is necessary to better quantify source apportioned CH4 emissions in California and further the understanding of the physical processes controlling them.

The impact of climatological model biases in the North Atlantic jet on predicted future circulation change

NASA Astrophysics Data System (ADS)

Simpson, I.

2015-12-01

A long standing bias among global climate models (GCMs) is their incorrect representation of the wintertime circulation of the North Atlantic region. Specifically models tend to exhibit a North Atlantic jet (and associated storm track) that is too zonal, extending across central Europe, when it should tilt northward toward Scandinavia. GCM's consistently predict substantial changes in the large scale circulation in this region, consisting of a localized anti-cyclonic circulation, centered over the Mediterranean and accompanied by increased aridity there and increased storminess over Northern Europe.Here, we present preliminary results from experiments that are designed to address the question of what the impact of the climatological circulation biases might be on this predicted future response. Climate change experiments will be compared in two versions of the Community Earth System Model: the first is a free running version of the model, as typically used in climate prediction; the second is a bias corrected version of the model in which a seasonally varying cycle of bias correction tendencies are applied to the wind and temperature fields. These bias correction tendencies are designed to account for deficiencies in the fast parameterized processes, with an aim to push the model toward a more realistic climatology.While these experiments come with the caveat that they assume the bias correction tendencies will remain constant with time, they allow for an initial assessment, through controlled experiments, of the impact that biases in the climatological circulation can have on future predictions in this region. They will also motivate future work that can make use of the bias correction tendencies to understand the underlying physical processes responsible for the incorrect tilt of the jet.

Improvement of Systematic Bias of mean state and the intraseasonal variability of CFSv2 through superparameterization and revised cloud-convection-radiation parameterization

NASA Astrophysics Data System (ADS)

Mukhopadhyay, P.; Phani Murali Krishna, R.; Goswami, Bidyut B.; Abhik, S.; Ganai, Malay; Mahakur, M.; Khairoutdinov, Marat; Dudhia, Jimmy

2016-05-01

Inspite of significant improvement in numerical model physics, resolution and numerics, the general circulation models (GCMs) find it difficult to simulate realistic seasonal and intraseasonal variabilities over global tropics and particularly over Indian summer monsoon (ISM) region. The bias is mainly attributed to the improper representation of physical processes. Among all the processes, the cloud and convective processes appear to play a major role in modulating model bias. In recent times, NCEP CFSv2 model is being adopted under Monsoon Mission for dynamical monsoon forecast over Indian region. The analyses of climate free run of CFSv2 in two resolutions namely at T126 and T382, show largely similar bias in simulating seasonal rainfall, in capturing the intraseasonal variability at different scales over the global tropics and also in capturing tropical waves. Thus, the biases of CFSv2 indicate a deficiency in model's parameterization of cloud and convective processes. Keeping this in background and also for the need to improve the model fidelity, two approaches have been adopted. Firstly, in the superparameterization, 32 cloud resolving models each with a horizontal resolution of 4 km are embedded in each GCM (CFSv2) grid and the conventional sub-grid scale convective parameterization is deactivated. This is done to demonstrate the role of resolving cloud processes which otherwise remain unresolved. The superparameterized CFSv2 (SP-CFS) is developed on a coarser version T62. The model is integrated for six and half years in climate free run mode being initialised from 16 May 2008. The analyses reveal that SP-CFS simulates a significantly improved mean state as compared to default CFS. The systematic bias of lesser rainfall over Indian land mass, colder troposphere has substantially been improved. Most importantly the convectively coupled equatorial waves and the eastward propagating MJO has been found to be simulated with more fidelity in SP-CFS. The reason of such betterment in model mean state has been found to be due to the systematic improvement in moisture field, temperature profile and moist instability. The model also has better simulated the cloud and rainfall relation. This initiative demonstrates the role of cloud processes on the mean state of coupled GCM. As the superparameterization approach is computationally expensive, so in another approach, the conventional Simplified Arakawa Schubert (SAS) scheme is replaced by a revised SAS scheme (RSAS) and also the old and simplified cloud scheme of Zhao-Karr (1997) has been replaced by WSM6 in CFSV2 (hereafter CFS-CR). The primary objective of such modifications is to improve the distribution of convective rain in the model by using RSAS and the grid-scale or the large scale nonconvective rain by WSM6. The WSM6 computes the tendency of six class (water vapour, cloud water, ice, snow, graupel, rain water) hydrometeors at each of the model grid and contributes in the low, middle and high cloud fraction. By incorporating WSM6, for the first time in a global climate model, we are able to show a reasonable simulation of cloud ice and cloud liquid water distribution vertically and spatially as compared to Cloudsat observations. The CFS-CR has also showed improvement in simulating annual rainfall cycle and intraseasonal variability over the ISM region. These improvements in CFS-CR are likely to be associated with improvement of the convective and stratiform rainfall distribution in the model. These initiatives clearly address a long standing issue of resolving the cloud processes in climate model and demonstrate that the improved cloud and convective process paramterizations can eventually reduce the systematic bias and improve the model fidelity.

Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deng, Yi

2014-11-24

DOE-GTRC-05596 11/24/2104 Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate PI: Dr. Yi Deng (PI) School of Earth and Atmospheric Sciences Georgia Institute of Technology 404-385-1821, yi.deng@eas.gatech.edu El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The projection of future changes in the ENSO and AM variability, however, remains highly uncertain with the state-of-the-science climate models. This project conducted a process-resolving, quantitative evaluations of the ENSO and AM variability in the modern reanalysis observationsmore » and in climate model simulations. The goal is to identify and understand the sources of uncertainty and biases in models’ representation of ENSO and AM variability. Using a feedback analysis method originally formulated by one of the collaborative PIs, we partitioned the 3D atmospheric temperature anomalies and surface temperature anomalies associated with ENSO and AM variability into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. In the past 4 years, the research conducted at Georgia Tech under the support of this project has led to 15 peer-reviewed publications and 9 conference/workshop presentations. Two graduate students and one postdoctoral fellow also received research training through participating the project activities. This final technical report summarizes key scientific discoveries we made and provides also a list of all publications and conference presentations resulted from research activities at Georgia Tech. The main findings include: 1) the distinctly different roles played by atmospheric dynamical processes in establishing surface temperature response to ENSO at tropics and extratropics (i.e., atmospheric dynamics disperses energy out of tropics during ENSO warm events and modulate surface temperature at mid-, high-latitudes through controlling downward longwave radiation); 2) the representations of ENSO-related temperature response in climate models fail to converge at the process-level particularly over extratropics (i.e., models produce the right temperature responses to ENSO but with wrong reasons); 3) water vapor feedback contributes substantially to the temperature anomalies found over U.S. during different phases of the Northern Annular Mode (NAM), which adds new insight to the traditional picture that cold/warm advective processes are the main drivers of local temperature responses to the NAM; 4) the overall land surface temperature biases in the latest NCAR model (CESM1) are caused by biases in surface albedo while the surface temperature biases over ocean are related to multiple factors including biases in model albedo, cloud and oceanic dynamics, and the temperature biases over different ocean basins are also induced by different process biases. These results provide a detailed guidance for process-level model turning and improvement, and thus contribute directly to the overall goal of reducing model uncertainty in projecting future changes in the Earth’s climate system, especially in the ENSO and AM variability.« less

Is the global mean temperature trend too low?

NASA Astrophysics Data System (ADS)

Venema, Victor; Lindau, Ralf

2015-04-01

The global mean temperature trend may be biased due to similar technological and economic developments worldwide. In this study we want to present a number of recent results that suggest that the global mean temperature trend might be steeper as generally thought. In the Global Historical Climate Network version 3 (GHCNv3) the global land surface temperature is estimated to have increased by about 0.8°C between 1880 and 2012. In the raw temperature record, the increase is 0.6°C; the 0.2°C difference is due to homogenization adjustments. Given that homogenization can only reduce biases, this 0.2°C stems from a partial correction of bias errors and it seems likely that the real non-climatic trend bias will be larger. Especially in regions with sparser networks, homogenization will not be able to improve the trend much. Thus if the trend bias in these regions is similar to the bias for more dense networks (industrialized countries), one would expect the real bias to be larger. Stations in sparse networks are representative for a larger region and are given more weight in the computation of the global mean temperature. If all stations are given equal weight, the homogenization adjustments of the GHCNv3 dataset are about 0.4°C per century. In the subdaily HadISH dataset one break with mean size 0.12°C is found every 15 years for the period 1973-2013. That would be a trend bias of 0.78°C per century on a station by station basis. Unfortunately, these estimates strongly focus on Western countries having more stations. It is known from the literature that rich countries have a (statistically insignificant) stronger trend in the global datasets. Regional datasets can be better homogenized than global ones, the main reason being that global datasets do not contain all stations known to the weather services. Furthermore, global datasets use automatic homogenization methods and have less or no metadata. Thus while regional data can be biased themselves, comparing them with global datasets can provide some indication on biases. Compared to the global BEST dataset for the same countries, the national datasets of Austria, Italy and Switzerland have a 0.36°C per century stronger trend since 1901. For the trend since 1960 we can also take Australia, France and Slovenia into account and find a trend bias of 0.40°C per century. Relative to CRUCY the trend biases are smaller and only statistically significant for the period since 1980. The most direct way to study biases in the temperature records is by making parallel measurements with historical measurement set-ups. Several recent parallel data studies for the transition to Stevenson screens suggest larger biases: Austria 0.2°C, Spain 0.5 & 0.6°C. As well as older tropical ones: India 0.42°C and Sri Lanka 0.37°C. The smaller values from the Parker (1994) review mainly stem from parallel measurements from North-West Europe, which may have less problems with exposure. Furthermore, the influence of many historical transitions, especially the ones that could cause an artificial smaller trend, have not been studied in detail yet. We urgently need to study improvements of exposure (especially in the (sub-)tropics), increases in watering and irrigation, mechanical ventilation, better paints, relocations to airports, and relocations to suburbs of stations that started in the cities and from village centers to pasture, for example. Our current understanding surprisingly suggests that the more recent period may have the largest biases, but it could also be that even the best datasets are unable to improve earlier data sufficiently. If the temperature trend were actually larger it would reduce discrepancies between studies for a number of problems in climatology. For example, the estimates of transient climate sensitivity using instrumental data are lower as the one using climate models, volcanic eruptions or paleo data. Furthermore, several changes observed in the climate system are larger than expected. On the other hand, a large trend in the land surface temperature would make the discrepancy with the tropospheric temperature even larger (radiosondes and satellites) and it would introduce a larger difference between land and sea temperature trends. Concluding, at the moment there is no strong evidence yet that the temperature trend is underestimated. However, we do have a considerable amount of evidence that suggests that there is a moderate, but climatologically important bias that we should study with urgency. As far as we know there are no estimates for the remaining uncertainty in the global mean trend after homogenization. Also studies into the causes of cooling biases are a pressing need. (Many have contributed to this study, but it is not clear at this moment who would be official collaborators; they will be added later.)

A new unified approach to determine geocentre motion using space geodetic and GRACE gravity data

NASA Astrophysics Data System (ADS)

Wu, Xiaoping; Kusche, Jürgen; Landerer, Felix W.

2017-06-01

Geocentre motion between the centre-of-mass of the Earth system and the centre-of-figure of the solid Earth surface is a critical signature of degree-1 components of global surface mass transport process that includes sea level rise, ice mass imbalance and continental-scale hydrological change. To complement GRACE data for complete-spectrum mass transport monitoring, geocentre motion needs to be measured accurately. However, current methods of geodetic translational approach and global inversions of various combinations of geodetic deformation, simulated ocean bottom pressure and GRACE data contain substantial biases and systematic errors. Here, we demonstrate a new and more reliable unified approach to geocentre motion determination using a recently formed satellite laser ranging based geocentric displacement time-series of an expanded geodetic network of all four space geodetic techniques and GRACE gravity data. The unified approach exploits both translational and deformational signatures of the displacement data, while the addition of GRACE's near global coverage significantly reduces biases found in the translational approach and spectral aliasing errors in the inversion.

Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model

NASA Astrophysics Data System (ADS)

Mann, G. W.; Carslaw, K. S.; Spracklen, D. V.; Ridley, D. A.; Manktelow, P. T.; Chipperfield, M. P.; Pickering, S. J.; Johnson, C. E.

2010-10-01

A new version of the Global Model of Aerosol Processes (GLOMAP) is described, which uses a two-moment pseudo-modal aerosol dynamics approach rather than the original two-moment bin scheme. GLOMAP-mode simulates the multi-component global aerosol, resolving sulfate, sea-salt, dust, black carbon (BC) and particulate organic matter (POM), the latter including primary and biogenic secondary POM. Aerosol processes are simulated in a size-resolved manner including primary emissions, secondary particle formation by binary homogeneous nucleation of sulfuric acid and water, particle growth by coagulation, condensation and cloud-processing and removal by dry deposition, in-cloud and below-cloud scavenging. A series of benchmark observational datasets are assembled against which the skill of the model is assessed in terms of normalised mean bias (b) and correlation coefficient (R). Overall, the model performs well against the datasets in simulating concentrations of aerosol precursor gases, chemically speciated particle mass, condensation nuclei (CN) and cloud condensation nuclei (CCN). Surface sulfate, sea-salt and dust mass concentrations are all captured well, while BC and POM are biased low (but correlate well). Surface CN concentrations compare reasonably well in free troposphere and marine sites, but are underestimated at continental and coastal sites related to underestimation of either primary particle emissions or new particle formation. The model compares well against a compilation of CCN observations covering a range of environments and against vertical profiles of size-resolved particle concentrations over Europe. The simulated global burden, lifetime and wet removal of each of the simulated aerosol components is also examined and each lies close to multi-model medians from the AEROCOM model intercomparison exercise.

Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model

NASA Astrophysics Data System (ADS)

Mann, G. W.; Carslaw, K. S.; Spracklen, D. V.; Ridley, D. A.; Manktelow, P. T.; Chipperfield, M. P.; Pickering, S. J.; Johnson, C. E.

2010-05-01

A new version of the Global Model of Aerosol Processes (GLOMAP) is described, which uses a two-moment modal aerosol scheme rather than the original two-moment bin scheme. GLOMAP-mode simulates the multi-component global aerosol, resolving sulphate, sea-salt, dust, black carbon (BC) and particulate organic matter (POM), the latter including primary and biogenic secondary POM. Aerosol processes are simulated in a size-resolved manner including primary emissions, secondary particle formation by binary homogeneous nucleation of sulphuric acid and water, particle growth by coagulation, condensation and cloud-processing and removal by dry deposition, in-cloud and below-cloud scavenging. A series of benchmark observational datasets are assembled against which the skill of the model is assessed in terms of normalised mean bias (b) and correlation coefficient (R). Overall, the model performs well against the datasets in simulating concentrations of aerosol precursor gases, chemically speciated particle mass, condensation nuclei (CN) and cloud condensation nuclei (CCN). Surface sulphate, sea-salt and dust mass concentrations are all captured well, while BC and POM are biased low (but correlate well). Surface CN concentrations compare reasonably well in free troposphere and marine sites, but are underestimated at continental and coastal sites related to underestimation of either primary particle emissions or new particle formation. The model compares well against a compilation of CCN observations covering a range of environments and against vertical profiles of size-resolved particle concentrations over Europe. The simulated global burden, lifetime and wet removal of each of the simulated aerosol components is also examined and each lies close to multi-model medians from the AEROCOM model intercomparison exercise.

Sex differences in the Kimchi-Palmer task revisited: Global reaction times, but not number of global choices differ between adult men and women.

PubMed

Scheuringer, Andrea; Pletzer, Belinda

2016-10-15

Research, directly assessing sex-dependent differences in global versus local processing is sparse, but predominantly suggesting that men show a stronger global processing bias than women. Utilizing the Kimchi-Palmer task however, sex differences in the number of global choices can only be found in children, but not in adults. In the current study 52 men and 46 women completed a computerized version of the Kimchi Palmer task, in order to investigate whether sex-differences in global-local processing in the Kimchi-Palmer task are reflected in choice reaction times rather than choices per se. While no sex differences were found in the number of global choices, we found that especially women are faster in making local choices than men, while men are faster in making global choices than women. We did not find support for the assumption that this sex difference was modulated by menstrual cycle phase of women, since the difference between reaction times to global and local choices was consistent across the menstrual cycle of women. Accordingly there was no relationship between progesterone and global-local processing in the Kimchi-Palmer task. However, like in studies utilizing the Navon task, testosterone was positively related to the number of global choices in both men and women. To our knowledge, this is the first study including reaction times as outcome measure in a Kimchi Palmer paradigm and also the first study demonstrating sex differences in the Kimchi Palmer task in adults. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

On improving cold region hydrological processes in the Canadian Land Surface Scheme

NASA Astrophysics Data System (ADS)

Ganji, Arman; Sushama, Laxmi; Verseghy, Diana; Harvey, Richard

2017-01-01

Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the treatment of frozen water in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis (ERA-Interim) for the 1990-2001 period over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration and therefore soil moisture during the snowmelt season for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS over most of the study domain. The simulated spring peaks and their timing in this simulation are also in better agreement to those observed. This study thus demonstrates the importance of treatment of frozen water for realistic simulation of streamflows.

A global call for action to include gender in research impact assessment.

PubMed

Ovseiko, Pavel V; Greenhalgh, Trisha; Adam, Paula; Grant, Jonathan; Hinrichs-Krapels, Saba; Graham, Kathryn E; Valentine, Pamela A; Sued, Omar; Boukhris, Omar F; Al Olaqi, Nada M; Al Rahbi, Idrees S; Dowd, Anne-Maree; Bice, Sara; Heiden, Tamika L; Fischer, Michael D; Dopson, Sue; Norton, Robyn; Pollitt, Alexandra; Wooding, Steven; Balling, Gert V; Jakobsen, Ulla; Kuhlmann, Ellen; Klinge, Ineke; Pololi, Linda H; Jagsi, Reshma; Smith, Helen Lawton; Etzkowitz, Henry; Nielsen, Mathias W; Carrion, Carme; Solans-Domènech, Maite; Vizcaino, Esther; Naing, Lin; Cheok, Quentin H N; Eckelmann, Baerbel; Simuyemba, Moses C; Msiska, Temwa; Declich, Giovanna; Edmunds, Laurel D; Kiparoglou, Vasiliki; Buchan, Alison M J; Williamson, Catherine; Lord, Graham M; Channon, Keith M; Surender, Rebecca; Buchan, Alastair M

2016-07-19

Global investment in biomedical research has grown significantly over the last decades, reaching approximately a quarter of a trillion US dollars in 2010. However, not all of this investment is distributed evenly by gender. It follows, arguably, that scarce research resources may not be optimally invested (by either not supporting the best science or by failing to investigate topics that benefit women and men equitably). Women across the world tend to be significantly underrepresented in research both as researchers and research participants, receive less research funding, and appear less frequently than men as authors on research publications. There is also some evidence that women are relatively disadvantaged as the beneficiaries of research, in terms of its health, societal and economic impacts. Historical gender biases may have created a path dependency that means that the research system and the impacts of research are biased towards male researchers and male beneficiaries, making it inherently difficult (though not impossible) to eliminate gender bias. In this commentary, we - a group of scholars and practitioners from Africa, America, Asia and Europe - argue that gender-sensitive research impact assessment could become a force for good in moving science policy and practice towards gender equity. Research impact assessment is the multidisciplinary field of scientific inquiry that examines the research process to maximise scientific, societal and economic returns on investment in research. It encompasses many theoretical and methodological approaches that can be used to investigate gender bias and recommend actions for change to maximise research impact. We offer a set of recommendations to research funders, research institutions and research evaluators who conduct impact assessment on how to include and strengthen analysis of gender equity in research impact assessment and issue a global call for action.

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Tianyi; Liu, Xiaohong; Ma, Po -Lun

Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results aremore » compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be –5.02, –18.47, and 13.45 W m –2, respectively, over eastern China, which are enhanced by –0.91, –3.48, and 2.57 W m –2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.« less

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

DOE PAGES

Fan, Tianyi; Liu, Xiaohong; Ma, Po -Lun; ...

2018-02-01

Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results aremore » compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be –5.02, –18.47, and 13.45 W m –2, respectively, over eastern China, which are enhanced by –0.91, –3.48, and 2.57 W m –2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.« less

Numerical Uncertainties in the Simulation of Reversible Isentropic Processes and Entropy Conservation.

NASA Astrophysics Data System (ADS)

Johnson, Donald R.; Lenzen, Allen J.; Zapotocny, Tom H.; Schaack, Todd K.

2000-11-01

A challenge common to weather, climate, and seasonal numerical prediction is the need to simulate accurately reversible isentropic processes in combination with appropriate determination of sources/sinks of energy and entropy. Ultimately, this task includes the distribution and transport of internal, gravitational, and kinetic energies, the energies of water substances in all forms, and the related thermodynamic processes of phase changes involved with clouds, including condensation, evaporation, and precipitation processes.All of the processes noted above involve the entropies of matter, radiation, and chemical substances, conservation during transport, and/or changes in entropies by physical processes internal to the atmosphere. With respect to the entropy of matter, a means to study a model's accuracy in simulating internal hydrologic processes is to determine its capability to simulate the appropriate conservation of potential and equivalent potential temperature as surrogates of dry and moist entropy under reversible adiabatic processes in which clouds form, evaporate, and precipitate. In this study, a statistical strategy utilizing the concept of `pure error' is set forth to assess the numerical accuracies of models to simulate reversible processes during 10-day integrations of the global circulation corresponding to the global residence time of water vapor. During the integrations, the sums of squared differences between equivalent potential temperature e numerically simulated by the governing equations of mass, energy, water vapor, and cloud water and a proxy equivalent potential temperature te numerically simulated as a conservative property are monitored. Inspection of the differences of e and te in time and space and the relative frequency distribution of the differences details bias and random errors that develop from nonlinear numerical inaccuracies in the advection and transport of potential temperature and water substances within the global atmosphere.A series of nine global simulations employing various versions of Community Climate Models CCM2 and CCM3-all Eulerian spectral numerics, all semi-Lagrangian numerics, mixed Eulerian spectral, and semi-Lagrangian numerics-and the University of Wisconsin-Madison (UW) isentropic-sigma gridpoint model provides an interesting comparison of numerical accuracies in the simulation of reversibility. By day 10, large bias and random differences were identified in the simulation of reversible processes in all of the models except for the UW isentropic-sigma model. The CCM2 and CCM3 simulations yielded systematic differences that varied zonally, vertically, and temporally. Within the comparison, the UW isentropic-sigma model was superior in transporting water vapor and cloud water/ice and in simulating reversibility involving the conservation of dry and moist entropy. The only relative frequency distribution of differences that appeared optimal, in that the distribution remained unbiased and equilibrated with minimal variance as it remained statistically stationary, was the distribution from the UW isentropic-sigma model. All other distributions revealed nonstationary characteristics with spreading and/or shifting of the maxima as the biases and variances of the numerical differences of e and te amplified.

Minimizing the wintertime low bias of Northern Hemisphere carbon monoxide in global model simulations

NASA Astrophysics Data System (ADS)

Stein, Olaf; Schultz, Martin G.; Bouarar, Idir; Clark, Hannah; Huijnen, Vincent; Gaudel, Audrey; George, Maya; Clerbaux, Cathy

2015-04-01

Carbon monoxide (CO) is a product of incomplete combustion and is also produced from oxidation of volatile organic compounds (VOC) in the atmosphere. It is of interest as an indirect greenhouse gas and an air pollutant causing health effects and is thus subject to emission restrictions. CO acts as a major sink for the OH radical and as a precursor for tropospheric ozone and affects the oxidizing capacity of the atmosphere as well as regional air quality. Despite the developments in the global modelling of chemistry and of the parameterization of the physical processes, CO concentrations remain underestimated during NH winter by most state-of-the-art chemical transport models. The resulting model bias can in principle originate from either an underestimation of CO sources or an overestimation of its sinks. We address both the role of sources and sinks with a series of MOZART chemistry transport model sensitivity simulations for the year 2008 and compare our results to observational data from ground-based stations, satellite observations, and from MOZAIC tropospheric profile measurements on passenger aircraft. Our base case simulation using the MACCity emission inventory (Granier et al. 2011) underestimates the near-surface Northern Hemispheric CO mixing ratios by more than 20 ppb from December to April with a maximal bias of 40 ppb in January. The bias is strongest for the European region (up to 75 ppb in January). From our sensitivity studies the mismatch between observed and modelled atmospheric CO concentrations can be explained by a combination of the following emission inventory shortcuts: (i) missing anthropogenic wintertime CO emissions from traffic or other combustion processes, (ii) missing anthropogenic VOC emissions, (iii) an exaggerated downward trend in the RCP8.5 scenario underlying the MACCity inventory, (iv) a lack of knowledge about the seasonality of emissions. Deficiencies in the parameterization of the dry deposition velocities can also lead to underestimations of Northern Hemisphere wintertime CO concentrations which are in the same order than those from the current emission inventories. A methane lifetime of 9.7 yr for our basic model and 9.8 yr for the optimized simulation agrees well with current estimates of global OH, but we cannot fully exclude a potential effect from errors in the geographical and seasonal distribution of OH concentrations on the modelled CO. References: Granier C. et al., Evolution of anthropogenic and biomass burning emissions of air pollutants at global and regional scales during the 1980-2010 period, Climatic Change, doi:10.1007/s10584-011-0154-1, 2011. Stein, O., Schultz, M. G., Bouarar, I., Clark, H., Huijnen, V., Gaudel, A., George, M., and Clerbaux, C.: On the wintertime low bias of Northern Hemisphere carbon monoxide found in global model simulations, Atmos. Chem. Phys., doi:10.5194/acp-14-9295-2014, 2014.

A basis for bias in geographical judgments.

PubMed

Friedman, Alinda; Brown, Norman R; McGaffey, Aaron P

2002-03-01

To determine why North Americans tend to locate European cities south of North American cities at similar latitudes (Tversky, 1981), we had observers provide bearing estimates between cities in the U.S. and Europe. Earlier research using latitude estimates of these cities has indicated that each continent has several subjective regions (Friedman & Brown, 2000a). Participants judged cities from two subjectively northern regions (Milwaukee-Munich), two subjectively southern regions (Memphis-Lisbon), and the two "crossed" regions (Albuquerque-Geneva; Minneapolis-Rome). Estimates were biased only when cities from the subjectively northern regions of North America were paired with cities from the subjectively southern region of Europe. In contrast to the view that biases are derived from distorted or aligned map-like representations, the data provide evidence that the subjective representation of global geography is principally categorical. Biases in numerical location estimates of individual cities and in bearing estimates between city pairs are derived from plausible reasoning processes operating on the same categorical representations.

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

NASA Astrophysics Data System (ADS)

Brogniez, Helene; English, Stephen; Mahfouf, Jean-Francois; Behrendt, Andreas; Berg, Wesley; Boukabara, Sid; Buehler, Stefan Alexander; Chambon, Philippe; Gambacorta, Antonia; Geer, Alan; Ingram, William; Kursinski, E. Robert; Matricardi, Marco; Odintsova, Tatyana A.; Payne, Vivienne H.; Thorne, Peter W.; Tretyakov, Mikhail Yu.; Wang, Junhong

2016-05-01

Several recent studies have observed systematic differences between measurements in the 183.31 GHz water vapor line by space-borne sounders and calculations using radiative transfer models, with inputs from either radiosondes (radiosonde observations, RAOBs) or short-range forecasts by numerical weather prediction (NWP) models. This paper discusses all the relevant categories of observation-based or model-based data, quantifies their uncertainties and separates biases that could be common to all causes from those attributable to a particular cause. Reference observations from radiosondes, Global Navigation Satellite System (GNSS) receivers, differential absorption lidar (DIAL) and Raman lidar are thus overviewed. Biases arising from their calibration procedures, NWP models and data assimilation, instrument biases and radiative transfer models (both the models themselves and the underlying spectroscopy) are presented and discussed. Although presently no single process in the comparisons seems capable of explaining the observed structure of bias, recommendations are made in order to better understand the causes.

Uncontrolled eating in adolescents: The role of impulsivity and automatic approach bias for food.

PubMed

Booth, Charlotte; Spronk, Desiree; Grol, Maud; Fox, Elaine

2018-01-01

Obesity is a global problem reaching epidemic proportions and can be explained by unhealthy eating and sedentary lifestyles. Understanding the psychological processes underlying unhealthy eating behaviour is crucial for the development of effective obesity prevention programmes. Dual-process models implicate the interplay between impaired cognitive control and enhanced automatic responsivity to rewarding food cues as key risk factors. The current study assessed the influence of four different components of trait impulsivity (reflecting impaired cognitive control) and automatic approach bias for food (reflecting automatic responsivity to food) on uncontrolled eating in a large sample (N = 504) of young adolescents. Of the four impulsivity factors, negative urgency was found to be the strongest predictor of uncontrolled eating. Interestingly, we found that lack of premeditation was a key risk factor for uncontrolled eating, but only when approach bias for food was high, supporting a dual-process model. Lack of perseverance showed a similar interactive pattern to a lesser degree and sensation-seeking did not predict uncontrolled eating. Together, our results show that distinct components of trait impulsivity are differentially associated with uncontrolled eating behaviour in adolescents, and that automatic processing of food cues may be an important factor in modulating this relationship. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Space, color, and direction of movement: how do they affect attention?

PubMed

Verghese, Ashika; Anderson, Andrew J; Vidyasagar, Trichur R

2013-07-19

Paying attention improves performance, but is this improvement regardless of what we attend to? We explored the differences in performance between attending to a location and attending to a feature when perceiving global motion. Attention was first cued to one of four locations that had coherently moving dots, while the remaining three had randomly moving distracter dots. Participants then viewed a colored display, wherein the color of the coherently moving dots was cued instead of location. In the third task, participants identified the location that had a particular cued direction of motion. Most observers reported reductions of motion threshold in all three tasks compared to when no cue was provided. However, the attentional bias generated by location cues was significantly larger than the bias resulting from feature cues of direction or color. This effect is consistent with the idea that attention is largely controlled by a fronto-parietal network where spatial relations are preferentially processed. On the other hand, color could not be used as a cue to focus attention and integrate motion. This finding suggests that color relies heavily on processing by ventral temporal cortical areas, which may have little control over the global motion areas in the dorsal part of the brain.

Mountain-climbing bears protect cherry species from global warming through vertical seed dispersal.

PubMed

Naoe, Shoji; Tayasu, Ichiro; Sakai, Yoichiro; Masaki, Takashi; Kobayashi, Kazuki; Nakajima, Akiko; Sato, Yoshikazu; Yamazaki, Koji; Kiyokawa, Hiroki; Koike, Shinsuke

2016-04-25

In a warming climate, temperature-sensitive plants must move toward colder areas, that is, higher latitude or altitude, by seed dispersal [1]. Considering that the temperature drop with increasing altitude (-0.65°C per 100 m altitude) is one hundred to a thousand times larger than that of the equivalent latitudinal distance [2], vertical seed dispersal is probably a key process for plant escape from warming temperatures. In fact, plant geographical distributions are tracking global warming altitudinally rather than latitudinally, and the extent of tracking is considered to be large in plants with better-dispersed traits (e.g., lighter seeds in wind-dispersed plants) [1]. However, no study has evaluated vertical seed dispersal itself due to technical difficulty or high cost. Here, we show using a stable oxygen isotope that black bears disperse seeds of wild cherry over several hundred meters vertically, and that the dispersal direction is heavily biased towards the mountain tops. Mountain climbing by bears following spring-to-summer plant phenology is likely the cause of this biased seed dispersal. These results suggest that spring- and summer-fruiting plants dispersed by animals may have high potential to escape global warming. Our results also indicate that the direction of vertical seed dispersal can be unexpectedly biased, and highlight the importance of considering seed dispersal direction to understand plant responses to past and future climate change. Copyright © 2016 Elsevier Ltd. All rights reserved.

Climate model biases in seasonality of continental water storage revealed by satellite gravimetry

USGS Publications Warehouse

Swenson, Sean; Milly, P.C.D.

2006-01-01

Satellite gravimetric observations of monthly changes in continental water storage are compared with outputs from five climate models. All models qualitatively reproduce the global pattern of annual storage amplitude, and the seasonal cycle of global average storage is reproduced well, consistent with earlier studies. However, global average agreements mask systematic model biases in low latitudes. Seasonal extrema of low‐latitude, hemispheric storage generally occur too early in the models, and model‐specific errors in amplitude of the low‐latitude annual variations are substantial. These errors are potentially explicable in terms of neglected or suboptimally parameterized water stores in the land models and precipitation biases in the climate models.

Application and Evaluation of an Explicit Prognostic Cloud-Cover Scheme in GRAPES Global Forecast System

NASA Astrophysics Data System (ADS)

Ma, Zhanshan; Liu, Qijun; Zhao, Chuanfeng; Shen, Xueshun; Wang, Yuan; Jiang, Jonathan H.; Li, Zhe; Yung, Yuk

2018-03-01

An explicit prognostic cloud-cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle-range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud-cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large-scale stratiform condensation processes. Our simulation results show that clouds in mid-high latitudes arise mainly from large-scale stratiform condensation processes, while cumulus convection and large-scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA-Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud-cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.

An object-based visual attention model for robotic applications.

PubMed

Yu, Yuanlong; Mann, George K I; Gosine, Raymond G

2010-10-01

By extending integrated competition hypothesis, this paper presents an object-based visual attention model, which selects one object of interest using low-dimensional features, resulting that visual perception starts from a fast attentional selection procedure. The proposed attention model involves seven modules: learning of object representations stored in a long-term memory (LTM), preattentive processing, top-down biasing, bottom-up competition, mediation between top-down and bottom-up ways, generation of saliency maps, and perceptual completion processing. It works in two phases: learning phase and attending phase. In the learning phase, the corresponding object representation is trained statistically when one object is attended. A dual-coding object representation consisting of local and global codings is proposed. Intensity, color, and orientation features are used to build the local coding, and a contour feature is employed to constitute the global coding. In the attending phase, the model preattentively segments the visual field into discrete proto-objects using Gestalt rules at first. If a task-specific object is given, the model recalls the corresponding representation from LTM and deduces the task-relevant feature(s) to evaluate top-down biases. The mediation between automatic bottom-up competition and conscious top-down biasing is then performed to yield a location-based saliency map. By combination of location-based saliency within each proto-object, the proto-object-based saliency is evaluated. The most salient proto-object is selected for attention, and it is finally put into the perceptual completion processing module to yield a complete object region. This model has been applied into distinct tasks of robots: detection of task-specific stationary and moving objects. Experimental results under different conditions are shown to validate this model.

Streamflow Bias Correction for Climate Change Impact Studies: Harmless Correction or Wrecking Ball?

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chegwidden, O.

2017-12-01

Projections of the hydrologic impacts of climate change rely on a modeling chain that includes estimates of future greenhouse gas emissions, global climate models, and hydrologic models. The resulting streamflow time series are used in turn as input to impact studies. While these flows can sometimes be used directly in these impact studies, many applications require additional post-processing to remove model errors. Water resources models and regulation studies are a prime example of this type of application. These models rely on specific flows and reservoir levels to trigger reservoir releases and diversions and do not function well if the unregulated streamflow inputs are significantly biased in time and/or amount. This post-processing step is typically referred to as bias-correction, even though this step corrects not just the mean but the entire distribution of flows. Various quantile-mapping approaches have been developed that adjust the modeled flows to match a reference distribution for some historic period. Simulations of future flows are then post-processed using this same mapping to remove hydrologic model errors. These streamflow bias-correction methods have received far less scrutiny than the downscaling and bias-correction methods that are used for climate model output, mostly because they are less widely used. However, some of these methods introduce large artifacts in the resulting flow series, in some cases severely distorting the climate change signal that is present in future flows. In this presentation, we discuss our experience with streamflow bias-correction methods as part of a climate change impact study in the Columbia River basin in the Pacific Northwest region of the United States. To support this discussion, we present a novel way to assess whether a streamflow bias-correction method is merely a harmless correction or is more akin to taking a wrecking ball to the climate change signal.

Strongly-motivated positive affects induce faster responses to local than global information of visual stimuli: an approach using large-size Navon letters.

PubMed

Noguchi, Yasuki; Tomoike, Kouta

2016-01-12

Recent studies argue that strongly-motivated positive emotions (e.g. desire) narrow a scope of attention. This argument is mainly based on an observation that, while humans normally respond faster to global than local information of a visual stimulus (global advantage), positive affects eliminated the global advantage by selectively speeding responses to local (but not global) information. In other words, narrowing of attentional scope was indirectly evidenced by the elimination of global advantage (the same speed of processing between global and local information). No study has directly shown that strongly-motivated positive affects induce faster responses to local than global information while excluding a bias for global information (global advantage) in a baseline (emotionally-neutral) condition. In the present study, we addressed this issue by eliminating the global advantage in a baseline (neutral) state. Induction of positive affects under this state resulted in faster responses to local than global information. Our results provided direct evidence that positive affects in high motivational intensity narrow a scope of attention.

Strength and coherence of binocular rivalry depends on shared stimulus complexity.

PubMed

Alais, David; Melcher, David

2007-01-01

Presenting incompatible images to the eyes results in alternations of conscious perception, a phenomenon known as binocular rivalry. We examined rivalry using either simple stimuli (oriented gratings) or coherent visual objects (faces, houses etc). Two rivalry characteristics were measured: Depth of rivalry suppression and coherence of alternations. Rivalry between coherent visual objects exhibits deep suppression and coherent rivalry, whereas rivalry between gratings exhibits shallow suppression and piecemeal rivalry. Interestingly, rivalry between a simple and a complex stimulus displays the same characteristics (shallow and piecemeal) as rivalry between two simple stimuli. Thus, complex stimuli fail to rival globally unless the fellow stimulus is also global. We also conducted a face adaptation experiment. Adaptation to rivaling faces improved subsequent face discrimination (as expected), but adaptation to a rivaling face/grating pair did not. To explain this, we suggest rivalry must be an early and local process (at least initially), instigated by the failure of binocular fusion, which can then become globally organized by feedback from higher-level areas when both rivalry stimuli are global, so that rivalry tends to oscillate coherently. These globally assembled images then flow through object processing areas, with the dominant image gaining in relative strength in a form of 'biased competition', therefore accounting for the deeper suppression of global images. In contrast, when only one eye receives a global image, local piecemeal suppression from the fellow eye overrides the organizing effects of global feedback to prevent coherent image formation. This indicates the primacy of local over global processes in rivalry.

Time scale bias in erosion rates of glaciated landscapes

PubMed Central

Ganti, Vamsi; von Hagke, Christoph; Scherler, Dirk; Lamb, Michael P.; Fischer, Woodward W.; Avouac, Jean-Philippe

2016-01-01

Deciphering erosion rates over geologic time is fundamental for understanding the interplay between climate, tectonic, and erosional processes. Existing techniques integrate erosion over different time scales, and direct comparison of such rates is routinely done in earth science. On the basis of a global compilation, we show that erosion rate estimates in glaciated landscapes may be affected by a systematic averaging bias that produces higher estimated erosion rates toward the present, which do not reflect straightforward changes in erosion rates through time. This trend can result from a heavy-tailed distribution of erosional hiatuses (that is, time periods where no or relatively slow erosion occurs). We argue that such a distribution can result from the intermittency of erosional processes in glaciated landscapes that are tightly coupled to climate variability from decadal to millennial time scales. In contrast, we find no evidence for a time scale bias in spatially averaged erosion rates of landscapes dominated by river incision. We discuss the implications of our findings in the context of the proposed coupling between climate and tectonics, and interpreting erosion rate estimates with different averaging time scales through geologic time. PMID:27713925

Time scale bias in erosion rates of glaciated landscapes.

PubMed

Ganti, Vamsi; von Hagke, Christoph; Scherler, Dirk; Lamb, Michael P; Fischer, Woodward W; Avouac, Jean-Philippe

2016-10-01

Deciphering erosion rates over geologic time is fundamental for understanding the interplay between climate, tectonic, and erosional processes. Existing techniques integrate erosion over different time scales, and direct comparison of such rates is routinely done in earth science. On the basis of a global compilation, we show that erosion rate estimates in glaciated landscapes may be affected by a systematic averaging bias that produces higher estimated erosion rates toward the present, which do not reflect straightforward changes in erosion rates through time. This trend can result from a heavy-tailed distribution of erosional hiatuses (that is, time periods where no or relatively slow erosion occurs). We argue that such a distribution can result from the intermittency of erosional processes in glaciated landscapes that are tightly coupled to climate variability from decadal to millennial time scales. In contrast, we find no evidence for a time scale bias in spatially averaged erosion rates of landscapes dominated by river incision. We discuss the implications of our findings in the context of the proposed coupling between climate and tectonics, and interpreting erosion rate estimates with different averaging time scales through geologic time.

The tree to the left, the forest to the right: political attitude and perceptual bias.

PubMed

Caparos, Serge; Fortier-St-Pierre, Simon; Gosselin, Jérémie; Blanchette, Isabelle; Brisson, Benoit

2015-01-01

A prominent model suggests that individuals to the right of the political spectrum are more cognitively rigid and less tolerant of ambiguity than individuals to the left. On the basis of this model, we predicted that a psychological mechanism linked to the resolution of visual ambiguity--perceptual bias--would be linked to political attitude. Perceptual bias causes western individuals to favour a global interpretation when scrutinizing ambiguous hierarchical displays (e.g., alignment of trees) that can be perceived either in terms of their local elements (e.g., several trees) or in terms of their global structure (e.g., a forest). Using three tasks (based on Navon-like hierarchical figures or on the Ebbinghaus illusion), we demonstrate (1) that right-oriented Westerners present a stronger bias towards global perception than left-oriented Westerners and (2) that this stronger bias is linked to higher cognitive rigidity. This study establishes for the first time that political ideology, a high-level construct, is directly reflected in low-level perception. Right- and left-oriented individuals actually see the world differently. Copyright © 2014 Elsevier B.V. All rights reserved.

Seasat scatterometer versus scanning multichannel microwave radiometer wind speeds: A comparison on a global scale

NASA Astrophysics Data System (ADS)

Boutin, J.; Etcheto, J.

1990-12-01

The wind speeds obtained from the Seasat A scatterometer system (SASS) and scanning multichannel microwave radiometer (SMMR) using two different algorithms were compared on a global scale. The temperature dependence of the sea surface emissivity was shown to be incorrectly modelled. After correcting this effect, regional differences up to ± 3 m s-1 are still observed between both instruments, even though they balance in global averaging, resulting in no bias between the global data sets. Validation experiments of satellite wind speeds should take into account this possibility of regional biases and insure the validity of the measurements everywhere in the global ocean.

Impact of Gulf Stream SST biases on the global atmospheric circulation

NASA Astrophysics Data System (ADS)

Lee, Robert W.; Woollings, Tim J.; Hoskins, Brian J.; Williams, Keith D.; O'Reilly, Christopher H.; Masato, Giacomo

2018-02-01

The UK Met Office Unified Model in the Global Coupled 2 (GC2) configuration has a warm bias of up to almost 7 K in the Gulf Stream SSTs in the winter season, which is associated with surface heat flux biases and potentially related to biases in the atmospheric circulation. The role of this SST bias is examined with a focus on the tropospheric response by performing three sensitivity experiments. The SST biases are imposed on the atmosphere-only configuration of the model over a small and medium section of the Gulf Stream, and also the wider North Atlantic. Here we show that the dynamical response to this anomalous Gulf Stream heating (and associated shifting and changing SST gradients) is to enhance vertical motion in the transient eddies over the Gulf Stream, rather than balance the heating with a linear dynamical meridional wind or meridional eddy heat transport. Together with the imposed Gulf Stream heating bias, the response affects the troposphere not only locally but also in remote regions of the Northern Hemisphere via a planetary Rossby wave response. The sensitivity experiments partially reproduce some of the differences in the coupled configuration of the model relative to the atmosphere-only configuration and to the ERA-Interim reanalysis. These biases may have implications for the ability of the model to respond correctly to variability or changes in the Gulf Stream. Better global prediction therefore requires particular focus on reducing any large western boundary current SST biases in these regions of high ocean-atmosphere interaction.

Weak central coherence in weight-restored adolescent anorexia nervosa: Characteristics and remediation.

PubMed

Weinbach, Noam; Perry, Amit; Sher, Helene; Lock, James D; Henik, Avishai

2017-08-01

Weak central coherence (WCC) refers to a bias towards processing details (local processing) at the expense of paying attention to the bigger picture (global processing). Multiple studies reported WCC in adults with anorexia nervosa (AN). Evidence for WCC in adolescents with AN has been inconsistent. The current study characterizes WCC in weight-restored adolescents with AN (WR-AN) using a direct measure of WCC, and examines whether WCC can be remediated by increasing alertness level-a manipulation that was found useful in enhancing global processing in healthy individuals and clinical populations. 40 adolescents (18 WR-AN and 22 healthy adolescents) performed a global/local processing task (Navon task). Auditory alerting cues that elevate alertness level were integrated into the task. Both groups processed global information faster than local information. However, compared with controls, adolescents with WR-AN were better at ignoring an irrelevant bigger picture while attending to details (smaller global interference) and had greater difficulty ignoring irrelevant details while attending to the bigger picture (larger local interference). These differences were attenuated when adolescents with WR-AN were under a state of high alertness. Additionally, the local interference effect was positively correlated with three independent self-report questionnaires assessing eating disorders symptomatology. This study suggests that abnormal interference by irrelevant global and local information is a central characteristic of WCC in adolescents with WR-AN that cannot be accounted for by enduring illness or malnourishment. Additionally, this study demonstrates that WCC can be temporarily remediated by encouraging a state of high alertness. © 2017 Wiley Periodicals, Inc.

Assessing the quality of life history information in publicly available databases.

PubMed

Thorson, James T; Cope, Jason M; Patrick, Wesley S

2014-01-01

Single-species life history parameters are central to ecological research and management, including the fields of macro-ecology, fisheries science, and ecosystem modeling. However, there has been little independent evaluation of the precision and accuracy of the life history values in global and publicly available databases. We therefore develop a novel method based on a Bayesian errors-in-variables model that compares database entries with estimates from local experts, and we illustrate this process by assessing the accuracy and precision of entries in FishBase, one of the largest and oldest life history databases. This model distinguishes biases among seven life history parameters, two types of information available in FishBase (i.e., published values and those estimated from other parameters), and two taxa (i.e., bony and cartilaginous fishes) relative to values from regional experts in the United States, while accounting for additional variance caused by sex- and region-specific life history traits. For published values in FishBase, the model identifies a small positive bias in natural mortality and negative bias in maximum age, perhaps caused by unacknowledged mortality caused by fishing. For life history values calculated by FishBase, the model identified large and inconsistent biases. The model also demonstrates greatest precision for body size parameters, decreased precision for values derived from geographically distant populations, and greatest between-sex differences in age at maturity. We recommend that our bias and precision estimates be used in future errors-in-variables models as a prior on measurement errors. This approach is broadly applicable to global databases of life history traits and, if used, will encourage further development and improvements in these databases.

An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5: Ensemble 3DCVA and Its Application

DOE PAGES

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2016-01-05

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemblemore » forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.« less

An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5: Ensemble 3DCVA and Its Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemblemore » forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.« less

Investigating Dry Deposition of Ozone to Vegetation

NASA Astrophysics Data System (ADS)

Silva, Sam J.; Heald, Colette L.

2018-01-01

Atmospheric ozone loss through dry deposition to vegetation is a critically important process for both air quality and ecosystem health. The majority of atmospheric chemistry models calculate dry deposition using a resistance-in-series parameterization by Wesely (1989), which is dependent on many environmental variables and lookup table values. The uncertainties contained within this parameterization have not been fully explored, ultimately challenging our ability to understand global scale biosphere-atmosphere interactions. In this work, we evaluate the GEOS-Chem model simulation of ozone dry deposition using a globally distributed suite of observations. We find that simulated daytime deposition velocities generally reproduce the magnitude of observations to within a factor of 1.4. When correctly accounting for differences in land class between the observations and model, these biases improve, most substantially over the grasses and shrubs land class. These biases do not impact the global ozone burden substantially; however, they do lead to local absolute changes of up to 4 ppbv and relative changes of 15% in summer surface concentrations. We use MERRA meteorology from 1979 to 2008 to assess that the interannual variability in simulated annual mean ozone dry deposition due to model input meteorology is small (generally less than 5% over vegetated surfaces). Sensitivity experiments indicate that the simulation is most sensitive to the stomatal and ground surface resistances, as well as leaf area index. To improve ozone dry deposition models, more measurements are necessary over rainforests and various crop types, alongside constraints on individual depositional pathways and other in-canopy ozone loss processes.

Analyzing source apportioned methane in northern California during Discover-AQ-CA using airborne measurements and model simulations

NASA Astrophysics Data System (ADS)

Johnson, Matthew S.; Yates, Emma L.; Iraci, Laura T.; Loewenstein, Max; Tadić, Jovan M.; Wecht, Kevin J.; Jeong, Seongeun; Fischer, Marc L.

2014-12-01

This study analyzes source apportioned methane (CH4) emissions and atmospheric mixing ratios in northern California during the Discover-AQ-CA field campaign using airborne measurement data and model simulations. Source apportioned CH4 emissions from the Emissions Database for Global Atmospheric Research (EDGAR) version 4.2 were applied in the 3-D chemical transport model GEOS-Chem and analyzed using airborne measurements taken as part of the Alpha Jet Atmospheric eXperiment over the San Francisco Bay Area (SFBA) and northern San Joaquin Valley (SJV). During the time period of the Discover-AQ-CA field campaign EDGAR inventory CH4 emissions were ∼5.30 Gg day-1 (Gg = 1.0 × 109 g) (equating to ∼1.90 × 103 Gg yr-1) for all of California. According to EDGAR, the SFBA and northern SJV region contributes ∼30% of total CH4 emissions from California. Source apportionment analysis during this study shows that CH4 mixing ratios over this area of northern California are largely influenced by global emissions from wetlands and local/global emissions from gas and oil production and distribution, waste treatment processes, and livestock management. Model simulations, using EDGAR emissions, suggest that the model under-estimates CH4 mixing ratios in northern California (average normalized mean bias (NMB) = -5.2% and linear regression slope = 0.20). The largest negative biases in the model were calculated on days when large amounts of CH4 were measured over local emission sources and atmospheric CH4 mixing ratios reached values >2.5 parts per million. Sensitivity emission studies conducted during this research suggest that local emissions of CH4 from livestock management processes are likely the primary source of the negative model bias. These results indicate that a variety, and larger quantity, of measurement data needs to be obtained and additional research is necessary to better quantify source apportioned CH4 emissions in California.

Inference of quantitative models of bacterial promoters from time-series reporter gene data.

PubMed

Stefan, Diana; Pinel, Corinne; Pinhal, Stéphane; Cinquemani, Eugenio; Geiselmann, Johannes; de Jong, Hidde

2015-01-01

The inference of regulatory interactions and quantitative models of gene regulation from time-series transcriptomics data has been extensively studied and applied to a range of problems in drug discovery, cancer research, and biotechnology. The application of existing methods is commonly based on implicit assumptions on the biological processes under study. First, the measurements of mRNA abundance obtained in transcriptomics experiments are taken to be representative of protein concentrations. Second, the observed changes in gene expression are assumed to be solely due to transcription factors and other specific regulators, while changes in the activity of the gene expression machinery and other global physiological effects are neglected. While convenient in practice, these assumptions are often not valid and bias the reverse engineering process. Here we systematically investigate, using a combination of models and experiments, the importance of this bias and possible corrections. We measure in real time and in vivo the activity of genes involved in the FliA-FlgM module of the E. coli motility network. From these data, we estimate protein concentrations and global physiological effects by means of kinetic models of gene expression. Our results indicate that correcting for the bias of commonly-made assumptions improves the quality of the models inferred from the data. Moreover, we show by simulation that these improvements are expected to be even stronger for systems in which protein concentrations have longer half-lives and the activity of the gene expression machinery varies more strongly across conditions than in the FliA-FlgM module. The approach proposed in this study is broadly applicable when using time-series transcriptome data to learn about the structure and dynamics of regulatory networks. In the case of the FliA-FlgM module, our results demonstrate the importance of global physiological effects and the active regulation of FliA and FlgM half-lives for the dynamics of FliA-dependent promoters.

Analyzing source apportioned methane in northern California during Discover-AQ-CA using airborne measurements and model simulations

DOE PAGES

Johnson, Matthew S.; Yates, Emma L.; Iraci, Laura T.; ...

2014-12-01

This study analyzes source apportioned methane (CH 4) emissions and atmospheric mixing ratios in northern California during the Discover-AQ-CA field campaign using airborne measurement data and model simulations. Source apportioned CH 4 emissions from the Emissions Database for Global Atmospheric Research (EDGAR) version 4.2 were applied in the 3-D chemical transport model GEOS-Chem and analyzed using airborne measurements taken as part of the Alpha Jet Atmospheric eXperiment over the San Francisco Bay Area (SFBA) and northern San Joaquin Valley (SJV). During the time period of the Discover-AQ-CA field campaign EDGAR inventory CH 4 emissions were ~5.30 Gg day –1 (Ggmore » = 1.0 × 10 9 g) (equating to ~1.90 × 10 3 Gg yr –1) for all of California. According to EDGAR, the SFBA and northern SJV region contributes ~30% of total CH 4 emissions from California. Source apportionment analysis during this study shows that CH 4 mixing ratios over this area of northern California are largely influenced by global emissions from wetlands and local/global emissions from gas and oil production and distribution, waste treatment processes, and livestock management. Model simulations, using EDGAR emissions, suggest that the model under-estimates CH 4 mixing ratios in northern California (average normalized mean bias (NMB) = –5.2% and linear regression slope = 0.20). The largest negative biases in the model were calculated on days when large amounts of CH 4 were measured over local emission sources and atmospheric CH 4 mixing ratios reached values >2.5 parts per million. Sensitivity emission studies conducted during this research suggest that local emissions of CH 4 from livestock management processes are likely the primary source of the negative model bias. These results indicate that a variety, and larger quantity, of measurement data needs to be obtained and additional research is necessary to better quantify source apportioned CH 4 emissions in California.« less

Verification bias: an under-recognized source of error in assessing the efficacy of MRI of the meniscii.

PubMed

Richardson, Michael L; Petscavage, Jonelle M

2011-11-01

The sensitivity and specificity of magnetic resonance imaging (MRI) for diagnosis of meniscal tears has been studied extensively, with tears usually verified by surgery. However, surgically unverified cases are often not considered in these studies, leading to verification bias, which can falsely increase the sensitivity and decrease the specificity estimates. Our study suggests that such bias may be very common in the meniscal MRI literature, and illustrates techniques to detect and correct for such bias. PubMed was searched for articles estimating sensitivity and specificity of MRI for meniscal tears. These were assessed for verification bias, deemed potentially present if a study included any patients whose MRI findings were not surgically verified. Retrospective global sensitivity analysis (GSA) was performed when possible. Thirty-nine of the 314 studies retrieved from PubMed specifically dealt with meniscal tears. All 39 included unverified patients, and hence, potential verification bias. Only seven articles included sufficient information to perform GSA. Of these, one showed definite verification bias, two showed no bias, and four others showed bias within certain ranges of disease prevalence. Only 9 of 39 acknowledged the possibility of verification bias. Verification bias is underrecognized and potentially common in published estimates of the sensitivity and specificity of MRI for the diagnosis of meniscal tears. When possible, it should be avoided by proper study design. If unavoidable, it should be acknowledged. Investigators should tabulate unverified as well as verified data. Finally, verification bias should be estimated; if present, corrected estimates of sensitivity and specificity should be used. Our online web-based calculator makes this process relatively easy. Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.

Assessment of Global Annual Atmospheric Energy Balance from Satellite Observations

NASA Technical Reports Server (NTRS)

Lin, Bing; Stackhouse, Paul; Minnis, Patrick; Wielicki, Bruce A.; Hu, Yongxiang; Sun, Wenbo; Fan, Tai-Fang (Alice); Hinkelman, Laura

2008-01-01

Global atmospheric energy balance is one of the fundamental processes for the earth's climate system. This study uses currently available satellite data sets of radiative energy at the top of atmosphere (TOA) and surface and latent and sensible heat over oceans for the year 2000 to assess the global annual energy budget. Over land, surface radiation data are used to constrain assimilated results and to force the radiation, turbulent heat, and heat storage into balance due to a lack of observation-based turbulent heat flux estimations. Global annual means of the TOA net radiation obtained from both direct measurements and calculations are close to zero. The net radiative energy fluxes into the surface and the surface latent heat transported into the atmosphere are about 113 and 86 Watts per square meter, respectively. The estimated atmospheric and surface heat imbalances are about -8 9 Watts per square meter, values that are within the uncertainties of surface radiation and sea surface turbulent flux estimates and likely systematic biases in the analyzed observations. The potential significant additional absorption of solar radiation within the atmosphere suggested by previous studies does not appear to be required to balance the energy budget the spurious heat imbalances in the current data are much smaller (about half) than those obtained previously and debated at about a decade ago. Progress in surface radiation and oceanic turbulent heat flux estimations from satellite measurements significantly reduces the bias errors in the observed global energy budgets of the climate system.

FIP BIAS EVOLUTION IN A DECAYING ACTIVE REGION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, D.; Yardley, S. L.; Driel-Gesztelyi, L. van

Solar coronal plasma composition is typically characterized by first ionization potential (FIP) bias. Using spectra obtained by Hinode’s EUV Imaging Spectrometer instrument, we present a series of large-scale, spatially resolved composition maps of active region (AR)11389. The composition maps show how FIP bias evolves within the decaying AR during the period 2012 January 4–6. Globally, FIP bias decreases throughout the AR. We analyzed areas of significant plasma composition changes within the decaying AR and found that small-scale evolution in the photospheric magnetic field is closely linked to the FIP bias evolution observed in the corona. During the AR’s decay phase,more » small bipoles emerging within supergranular cells reconnect with the pre-existing AR field, creating a pathway along which photospheric and coronal plasmas can mix. The mixing timescales are shorter than those of plasma enrichment processes. Eruptive activity also results in shifting the FIP bias closer to photospheric in the affected areas. Finally, the FIP bias still remains dominantly coronal only in a part of the AR’s high-flux density core. We conclude that in the decay phase of an AR’s lifetime, the FIP bias is becoming increasingly modulated by episodes of small-scale flux emergence, i.e., decreasing the AR’s overall FIP bias. Our results show that magnetic field evolution plays an important role in compositional changes during AR development, revealing a more complex relationship than expected from previous well-known Skylab results showing that FIP bias increases almost linearly with age in young ARs.« less

Assessment of Bias in the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Reanalysis Radar-Only Estimate

NASA Astrophysics Data System (ADS)

Nelson, B. R.; Prat, O. P.; Stevens, S. E.; Seo, D. J.; Zhang, J.; Howard, K.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is nearly completed for the period covering from 2001 to 2012. Reanalysis data are available at 1-km and 5-minute resolution. An important step in generating the best possible precipitation data is to assess the bias in the radar-only product. In this work, we use data from a combination of rain gauge networks to assess the bias in the NMQ reanalysis. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network Daily (GHCN-D) are combined for use in the assessment. These rain gauge networks vary in spatial density and temporal resolution. The challenge hence is to optimally utilize them to assess the bias at the finest resolution possible. For initial assessment, we propose to subset the CONUS data in climatologically representative domains, and perform bias assessment using information in the Q2 dataset on precipitation type and phase.

Sensitivity of the atmospheric water cycle to corrections of the sea surface temperature bias over southern Africa in a regional climate model

NASA Astrophysics Data System (ADS)

Weber, Torsten; Haensler, Andreas; Jacob, Daniela

2017-12-01

Regional climate models (RCMs) have been used to dynamically downscale global climate projections at high spatial and temporal resolution in order to analyse the atmospheric water cycle. In southern Africa, precipitation pattern were strongly affected by the moisture transport from the southeast Atlantic and southwest Indian Ocean and, consequently, by their sea surface temperatures (SSTs). However, global ocean models often have deficiencies in resolving regional to local scale ocean currents, e.g. in ocean areas offshore the South African continent. By downscaling global climate projections using RCMs, the biased SSTs from the global forcing data were introduced to the RCMs and affected the results of regional climate projections. In this work, the impact of the SST bias correction on precipitation, evaporation and moisture transport were analysed over southern Africa. For this analysis, several experiments were conducted with the regional climate model REMO using corrected and uncorrected SSTs. In these experiments, a global MPI-ESM-LR historical simulation was downscaled with the regional climate model REMO to a high spatial resolution of 50 × 50 km2 and of 25 × 25 km2 for southern Africa using a double-nesting method. The results showed a distinct impact of the corrected SST on the moisture transport, the meridional vertical circulation and on the precipitation pattern in southern Africa. Furthermore, it was found that the experiment with the corrected SST led to a reduction of the wet bias over southern Africa and to a better agreement with observations as without SST bias corrections.

Precise orbit determination of Multi-GNSS constellation including GPS GLONASS BDS and GALIEO

NASA Astrophysics Data System (ADS)

Dai, Xiaolei

2014-05-01

In addition to the existing American global positioning system (GPS) and the Russian global navigation satellite system (GLONASS), the new generation of GNSS is emerging and developing, such as the Chinese BeiDou satellite navigation system (BDS) and the European GALILEO system. Multi-constellation is expected to contribute to more accurate and reliable positioning and navigation service. However, the application of multi-constellation challenges the traditional precise orbit determination (POD) strategy that was designed usually for single constellation. In this contribution, we exploit a more rigorous multi-constellation POD strategy for the ongoing IGS multi-GNSS experiment (MGEX) where the common parameters are identical for each system, and the frequency- and system-specified parameters are employed to account for the inter-frequency and inter-system biases. Since the authorized BDS attitude model is not yet released, different BDS attitude model are implemented and their impact on orbit accuracy are studied. The proposed POD strategy was implemented in the PANDA (Position and Navigation Data Analyst) software and can process observations from GPS, GLONASS, BDS and GALILEO together. The strategy is evaluated with the multi-constellation observations from about 90 MGEX stations and BDS observations from the BeiDou experimental tracking network (BETN) of Wuhan University (WHU). Of all the MGEX stations, 28 stations record BDS observation, and about 80 stations record GALILEO observations. All these data were processed together in our software, resulting in the multi-constellation POD solutions. We assessed the orbit accuracy for GPS and GLONASS by comparing our solutions with the IGS final orbit, and for BDS and GALILEO by overlapping our daily orbit solution. The stability of inter-frequency bias of GLONASS and inter-system biases w.r.t. GPS for GLONASS, BDS and GALILEO were investigated. At last, we carried out precise point positioning (PPP) using the multi-constellation POD orbit and clock products, and analyzed the contribution of these POD products to PPP. Keywords: Multi-GNSS, Precise Orbit Determination, Inter-frequency bias, Inter-system bias, Precise Point Positioning

Humidity Bias and Effect on Simulated Aerosol Optical Properties during the Ganges Valley Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Yan; Cadeddu, M.; Kotamarthi, V. R.

2016-07-10

The radiosonde humidity profiles available during the Ganges Valley Experiment were compared to those simulated from the regional Weather Research and Forecasting (WRF) model coupled with a chemistry module (WRF -Chern) and the global reanalysis datasets. Large biases were revealed. On a monthly mean basis at Nainital, located in northern India, the WRFChern model simulates a large moist bias in the free troposphere (up to +20%) as well as a large dry bias in the boundary layer (up to -30%). While the overall pattern of the biases is similar, the magnitude of the biases varies from time to time andmore » from one location to another. At Thiruvananthapuram, the magnitude of the dry bias is smaller, and in contrast to Nainital, the higher-resolution regional WRF -Chern model generates larger moist biases in the upper troposphere than the global reanalysis data. Furthermore, the humidity biases in the upper troposphere, while significant, have little impact on the model estimation of column aerosol optical depth (AOD). The frequent occurrences of the dry boundary-layer bias simulated by the large-scale models tend to lead to the underestimation of AOD. It is thus important to quantify the humidity vertical profiles for aerosol simulations over South Asia.« less

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

Link between the double-Intertropical Convergence Zone problem and cloud biases over the Southern Ocean

PubMed Central

Hwang, Yen-Ting; Frierson, Dargan M. W.

2013-01-01

The double-Intertropical Convergence Zone (ITCZ) problem, in which excessive precipitation is produced in the Southern Hemisphere tropics, which resembles a Southern Hemisphere counterpart to the strong Northern Hemisphere ITCZ, is perhaps the most significant and most persistent bias of global climate models. In this study, we look to the extratropics for possible causes of the double-ITCZ problem by performing a global energetic analysis with historical simulations from a suite of global climate models and comparing with satellite observations of the Earth’s energy budget. Our results show that models with more energy flux into the Southern Hemisphere atmosphere (at the top of the atmosphere and at the surface) tend to have a stronger double-ITCZ bias, consistent with recent theoretical studies that suggest that the ITCZ is drawn toward heating even outside the tropics. In particular, we find that cloud biases over the Southern Ocean explain most of the model-to-model differences in the amount of excessive precipitation in Southern Hemisphere tropics, and are suggested to be responsible for this aspect of the double-ITCZ problem in most global climate models. PMID:23493552

Retrieval of temperature profiles from CHAMP for climate monitoring: intercomparison with Envisat MIPAS and GOMOS and different atmospheric analyses

NASA Astrophysics Data System (ADS)

Gobiet, A.; Kirchengast, G.; Manney, G. L.; Borsche, M.; Retscher, C.; Stiller, G.

2007-02-01

This study describes and evaluates a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval scheme particularly aimed at delivering bias-free atmospheric parameters for climate monitoring and research. The focus of the retrieval is on the sensible use of a priori information for careful high-altitude initialisation in order to maximise the usable altitude range. The RO retrieval scheme has been meanwhile applied to more than five years of data (September 2001 to November 2006) from the German CHAllenging Minisatellite Payload for geoscientific research (CHAMP) satellite. In this study it was validated against various correlative datasets including the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Global Ozone Monitoring for Occultation of Stars (GOMOS) sensors on Envisat, five different atmospheric analyses, and the operational CHAMP retrieval product from GeoForschungsZentrum (GFZ) Potsdam. In the global mean within 10 to 30 km altitude we find that the present validation observationally constrains the potential RO temperature bias to be <0.2 K. Latitudinally resolved analyses show biases to be observationally constrained to <0.2-0.5 K up to 35 km in most cases, and up to 30 km in any case, even if severely biased (about 10 K or more) a priori information is used in the high altitude initialisation of the retrieval. No evidence is found for the 10-35 km altitude range of RO bias sources other than those potentially propagated downward from initialisation, indicating that the widely quoted RO promise of "unbiasedness and long-term stability due to intrinsic self-calibration" can indeed be realized given care in the data processing to strictly limit structural uncertainty. The results demonstrate that an adequate high-altitude initialisation technique is crucial for accurate stratospheric RO retrievals and that still common methods of initialising the involved hydrostatic integral with an upper boundary temperature or pressure value derived from meteorological analyses is prone to introduce biases from the initialisation data to the retrieved temperatures down to below 25 km. Above 30 to 35 km, GNSS RO delivers a considerable amount of observed information up to around 40 km, which is particularly interesting for numerical weather prediction (NWP) systems, where direct assimilation of non-initialized (a priori-free) observed RO bending angles is thus the method of choice. The results underline the value of RO for climate applications.

Retrieval of temperature profiles from CHAMP for climate monitoring: intercomparison with Envisat MIPAS and GOMOS and different atmospheric analyses

NASA Astrophysics Data System (ADS)

Gobiet, A.; Kirchengast, G.; Manney, G. L.; Borsche, M.; Retscher, C.; Stiller, G.

2007-07-01

This study describes and evaluates a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval scheme particularly aimed at delivering bias-free atmospheric parameters for climate monitoring and research. The focus of the retrieval is on the sensible use of a priori information for careful high-altitude initialisation in order to maximise the usable altitude range. The RO retrieval scheme has been meanwhile applied to more than five years of data (September 2001 to present) from the German CHAllenging Minisatellite Payload for geoscientific research (CHAMP) satellite. In this study it was validated against various correlative datasets including the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Global Ozone Monitoring for Occultation of Stars (GOMOS) sensors on Envisat, five different atmospheric analyses, and the operational CHAMP retrieval product from GeoForschungsZentrum (GFZ) Potsdam. In the global mean within 10 to 30 km altitude we find that the present validation observationally constrains the potential RO temperature bias to be <0.2 K. Latitudinally resolved analyses show biases to be observationally constrained to <0.2-0.5 K up to 35 km in most cases, and up to 30 km in any case, even if severely biased (about 10 K or more) a priori information is used in the high altitude initialisation of the retrieval. No evidence is found for the 10-35 km altitude range of residual RO bias sources other than those potentially propagated downward from initialisation, indicating that the widely quoted RO promise of "unbiasedness and long-term stability due to intrinsic self-calibration" can indeed be realised given care in the data processing to strictly limit structural uncertainty. The results thus reinforce that adequate high-altitude initialisation is crucial for accurate stratospheric RO retrievals. The common method of initialising, at some altitude in the upper stratosphere, the hydrostatic integral with an upper boundary temperature or pressure value derived from meteorological analyses is prone to introduce biases from the upper boundary down to below 25 km. Also above 30 to 35 km, GNSS RO delivers a considerable amount of observed information up to around 40 km, which is particularly interesting for numerical weather prediction (NWP) systems, where direct assimilation of non-initialised observed RO bending angles (free of a priori) is thus the method of choice. The results underline the value of RO for climate applications.

Impact of bias-corrected reanalysis-derived lateral boundary conditions on WRF simulations

NASA Astrophysics Data System (ADS)

Moalafhi, Ditiro Benson; Sharma, Ashish; Evans, Jason Peter; Mehrotra, Rajeshwar; Rocheta, Eytan

2017-08-01

Lateral and lower boundary conditions derived from a suitable global reanalysis data set form the basis for deriving a dynamically consistent finer resolution downscaled product for climate and hydrological assessment studies. A problem with this, however, is that systematic biases have been noted to be present in the global reanalysis data sets that form these boundaries, biases which can be carried into the downscaled simulations thereby reducing their accuracy or efficacy. In this work, three Weather Research and Forecasting (WRF) model downscaling experiments are undertaken to investigate the impact of bias correcting European Centre for Medium range Weather Forecasting Reanalysis ERA-Interim (ERA-I) atmospheric temperature and relative humidity using Atmospheric Infrared Sounder (AIRS) satellite data. The downscaling is performed over a domain centered over southern Africa between the years 2003 and 2012. The sample mean and the mean as well as standard deviation at each grid cell for each variable are used for bias correction. The resultant WRF simulations of near-surface temperature and precipitation are evaluated seasonally and annually against global gridded observational data sets and compared with ERA-I reanalysis driving field. The study reveals inconsistencies between the impact of the bias correction prior to downscaling and the resultant model simulations after downscaling. Mean and standard deviation bias-corrected WRF simulations are, however, found to be marginally better than mean only bias-corrected WRF simulations and raw ERA-I reanalysis-driven WRF simulations. Performances, however, differ when assessing different attributes in the downscaled field. This raises questions about the efficacy of the correction procedures adopted.

Gender differences in global-local perception? Evidence from orientation and shape judgments.

PubMed

Kimchi, Ruth; Amishav, Rama; Sulitzeanu-Kenan, Anat

2009-01-01

Direct examinations of gender differences in global-local processing are sparse, and the results are inconsistent. We examined this issue with a visuospatial judgment task and with a shape judgment task. Women and men were presented with hierarchical stimuli that varied in closure (open or closed shape) or in line orientation (oblique or horizontal/vertical) at the global or local level. The task was to classify the stimuli on the basis of the variation at the global level (global classification) or at the local level (local classification). Women's classification by closure (global or local) was more accurate than men's for stimuli that varied in closure on both levels, suggesting a female advantage in discriminating shape properties. No gender differences were observed in global-local processing bias. Women and men exhibited a global advantage, and they did not differ in their speed of global or local classification, with only one exception. Women were slower than men in local classification by orientation when the to-be-classified lines were embedded in a global line with a different orientation. This finding suggests that women are more distracted than men by misleading global oriented context when performing local orientation judgments, perhaps because women and men differ in their ability to use cognitive schemes to compensate for the distracting effects of the global context. Our findings further suggest that whether or not gender differences arise depends not only on the nature of the visual task but also on the visual context.

The lure of global branding.

PubMed

Aaker, D A; Joachimsthaler, E

1999-01-01

As more and more companies begin to see the world as their market, brand builders look with envy upon those businesses that appear to have created global brands--brands whose positioning, advertising strategy, personality, look, and feel are in most respects the same from one country to another. Attracted by such high-profile examples of success, these companies want to globalize their own brands. But that's a risky path to follow, according to David Aaker and Erich Joachimsthaler. Why? Because creating strong global brands takes global brand leadership. It can't be done simply by edict from on high. Specifically, companies must use organizational structures, processes, and cultures to allocate brand-building resources globally, to create global synergies, and to develop a global brand strategy that coordinates and leverages country brand strategies. Aaker and Joachimsthaler offer four prescriptions for companies seeking to achieve global brand leadership. First, companies must stimulate the sharing of insights and best practices across countries--a system in which "it won't work here" attitudes can be overcome. Second, companies should support a common global brand-planning process, one that is consistent across markets and products. Third, they should assign global managerial responsibility for brands in order to create cross-country synergies and to fight local bias. And fourth, they need to execute brilliant brand-building strategies. Before stampeding blindly toward global branding, companies need to think through the systems they have in place. Otherwise, any success they achieve is likely to be random--and that's a fail-safe recipe for mediocrity.

Effects of Model Resolution and Ocean Mixing on Forced Ice-Ocean Physical and Biogeochemical Simulations Using Global and Regional System Models

NASA Astrophysics Data System (ADS)

Jin, Meibing; Deal, Clara; Maslowski, Wieslaw; Matrai, Patricia; Roberts, Andrew; Osinski, Robert; Lee, Younjoo J.; Frants, Marina; Elliott, Scott; Jeffery, Nicole; Hunke, Elizabeth; Wang, Shanlin

2018-01-01

The current coarse-resolution global Community Earth System Model (CESM) can reproduce major and large-scale patterns but is still missing some key biogeochemical features in the Arctic Ocean, e.g., low surface nutrients in the Canada Basin. We incorporated the CESM Version 1 ocean biogeochemical code into the Regional Arctic System Model (RASM) and coupled it with a sea-ice algal module to investigate model limitations. Four ice-ocean hindcast cases are compared with various observations: two in a global 1° (40˜60 km in the Arctic) grid: G1deg and G1deg-OLD with/without new sea-ice processes incorporated; two on RASM's 1/12° (˜9 km) grid R9km and R9km-NB with/without a subgrid scale brine rejection parameterization which improves ocean vertical mixing under sea ice. Higher-resolution and new sea-ice processes contributed to lower model errors in sea-ice extent, ice thickness, and ice algae. In the Bering Sea shelf, only higher resolution contributed to lower model errors in salinity, nitrate (NO3), and chlorophyll-a (Chl-a). In the Arctic Basin, model errors in mixed layer depth (MLD) were reduced 36% by brine rejection parameterization, 20% by new sea-ice processes, and 6% by higher resolution. The NO3 concentration biases were caused by both MLD bias and coarse resolution, because of excessive horizontal mixing of high NO3 from the Chukchi Sea into the Canada Basin in coarse resolution models. R9km showed improvements over G1deg on NO3, but not on Chl-a, likely due to light limitation under snow and ice cover in the Arctic Basin.

A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments

NASA Astrophysics Data System (ADS)

Schepen, Andrew; Zhao, Tongtiegang; Wang, Quan J.; Robertson, David E.

2018-03-01

Rainfall forecasts are an integral part of hydrological forecasting systems at sub-seasonal to seasonal timescales. In seasonal forecasting, global climate models (GCMs) are now the go-to source for rainfall forecasts. For hydrological applications however, GCM forecasts are often biased and unreliable in uncertainty spread, and calibration is therefore required before use. There are sophisticated statistical techniques for calibrating monthly and seasonal aggregations of the forecasts. However, calibration of seasonal forecasts at the daily time step typically uses very simple statistical methods or climate analogue methods. These methods generally lack the sophistication to achieve unbiased, reliable and coherent forecasts of daily amounts and seasonal accumulated totals. In this study, we propose and evaluate a Rainfall Post-Processing method for Seasonal forecasts (RPP-S), which is based on the Bayesian joint probability modelling approach for calibrating daily forecasts and the Schaake Shuffle for connecting the daily ensemble members of different lead times. We apply the method to post-process ACCESS-S forecasts for 12 perennial and ephemeral catchments across Australia and for 12 initialisation dates. RPP-S significantly reduces bias in raw forecasts and improves both skill and reliability. RPP-S forecasts are also more skilful and reliable than forecasts derived from ACCESS-S forecasts that have been post-processed using quantile mapping, especially for monthly and seasonal accumulations. Several opportunities to improve the robustness and skill of RPP-S are identified. The new RPP-S post-processed forecasts will be used in ensemble sub-seasonal to seasonal streamflow applications.

Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 2. Biases and homogenization

NASA Astrophysics Data System (ADS)

Kennedy, J. J.; Rayner, N. A.; Smith, R. O.; Parker, D. E.; Saunby, M.

2011-07-01

Changes in instrumentation and data availability have caused time-varying biases in estimates of global and regional average sea surface temperature. The size of the biases arising from these changes are estimated and their uncertainties evaluated. The estimated biases and their associated uncertainties are largest during the period immediately following the Second World War, reflecting the rapid and incompletely documented changes in shipping and data availability at the time. Adjustments have been applied to reduce these effects in gridded data sets of sea surface temperature and the results are presented as a set of interchangeable realizations. Uncertainties of estimated trends in global and regional average sea surface temperature due to bias adjustments since the Second World War are found to be larger than uncertainties arising from the choice of analysis technique, indicating that this is an important source of uncertainty in analyses of historical sea surface temperatures. Despite this, trends over the twentieth century remain qualitatively consistent.

Assessment of bias correction under transient climate change

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Vannitsem, Stéphane

2015-04-01

Calibration of climate simulations is necessary since large systematic discrepancies are generally found between the model climate and the observed climate. Recent studies have cast doubt upon the common assumption of the bias being stationary when the climate changes. This led to the development of new methods, mostly based on linear sensitivity of the biases as a function of time or forcing (Kharin et al. 2012). However, recent studies uncovered more fundamental problems using both low-order systems (Vannitsem 2011) and climate models, showing that the biases may display complicated non-linear variations under climate change. This last analysis focused on biases derived from the equilibrium climate sensitivity, thereby ignoring the effect of the transient climate sensitivity. Based on the linear response theory, a general method of bias correction is therefore proposed that can be applied on any climate forcing scenario. The validity of the method is addressed using twin experiments with a climate model of intermediate complexity LOVECLIM (Goosse et al., 2010). We evaluate to what extent the bias change is sensitive to the structure (frequency) of the applied forcing (here greenhouse gases) and whether the linear response theory is valid for global and/or local variables. To answer these question we perform large-ensemble simulations using different 300-year scenarios of forced carbon-dioxide concentrations. Reality and simulations are assumed to differ by a model error emulated as a parametric error in the wind drag or in the radiative scheme. References [1] H. Goosse et al., 2010: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603-633. [2] S. Vannitsem, 2011: Bias correction and post-processing under climate change, Nonlin. Processes Geophys., 18, 911-924. [3] V.V. Kharin, G. J. Boer, W. J. Merryfield, J. F. Scinocca, and W.-S. Lee, 2012: Statistical adjustment of decadal predictions in a changing climate, Geophys. Res. Lett., 39, L19705.

Biases in field measurements of ice nuclei concentrations

NASA Astrophysics Data System (ADS)

Garimella, S.; Voigtländer, J.; Kulkarni, G.; Stratmann, F.; Cziczo, D. J.

2015-12-01

Ice nuclei (IN) play an important role in the climate system by influencing cloud properties, precipitation, and radiative transfer. Despite their importance, there are significant uncertainties in estimating IN concentrations because of the complexities of atmospheric ice nucleation processes. Field measurements of IN concentrations with Continuous Flow Diffusion Chamber (CFDC) IN counters have been vital to constrain IN number concentrations and have led to various parameterizations of IN number vs. temperature and particle concentration. These parameterizations are used in many global climate models, which are very sensitive to the treatment of cloud microphysics. However, due to non-idealities in CFDC behavior, especially at high relative humidity, many of these measurements are likely biased too low. In this study, the extent of this low bias is examined with laboratory experiments at a variety of instrument conditions using the SPectrometer for Ice Nucleation, a commercially-available CFDC-style chamber. These laboratory results are compared to theoretical calculations and computational fluid dynamics models to map the variability of this bias as a function of chamber temperature and relative humidity.

Threat bias, not negativity bias, underpins differences in political ideology.

PubMed

Lilienfeld, Scott O; Latzman, Robert D

2014-06-01

Although disparities in political ideology are rooted partly in dispositional differences, Hibbing et al.'s analysis paints with an overly broad brush. Research on the personality correlates of liberal-conservative differences points not to global differences in negativity bias, but to differences in threat bias, probably emanating from differences in fearfulness. This distinction bears implications for etiological research and persuasion efforts.

Multiple measures of dispositional global/local bias predict attentional blink magnitude.

PubMed

Dale, Gillian; Arnell, Karen M

2015-07-01

When the second of two targets (T2) is presented temporally close to the first target (T1) in a rapid serial visual presentation stream, accuracy to identify T2 is markedly reduced-an attentional blink (AB). While most individuals show an AB, Dale and Arnell (Atten Percept Psychophys 72(3):602-606, 2010) demonstrated that individual differences in dispositional attentional focus predicted AB performance, such that individuals who showed a natural bias toward the global level of Navon letter stimuli were less susceptible to the AB and showed a smaller AB effect. For the current study, we extended the findings of Dale and Arnell (Atten Percept Psychophys 72(3):602-606, 2010) through two experiments. In Experiment 1, we examined the relationship between dispositional global/local bias and the AB using a highly reliable hierarchical shape task measure. In Experiment 2, we examined whether three distinct global/local measures could predict AB performance. In both experiments, performance on the global/local tasks predicted subsequent AB performance, such that individuals with a greater preference for the global information showed a reduced AB. This supports previous findings, as well as recent models which discuss the role of attentional breadth in selective attention.

Embedded Figures Detection in Autism and Typical Development: Preliminary Evidence of a Double Dissociation in Relationships with Visual Search

ERIC Educational Resources Information Center

Jarrold, Christopher; Gilchrist, Iain D.; Bender, Alison

2005-01-01

Individuals with autism show relatively strong performance on tasks that require them to identify the constituent parts of a visual stimulus. This is assumed to be the result of a bias towards processing the local elements in a display that follows from a weakened ability to integrate information at the global level. The results of the current…

Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global Cloud-Permiting Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Chidong

Motivated by the success of the AMIE/DYNAMO field campaign, which collected unprecedented observations of cloud and precipitation from the tropical Indian Ocean in Octber 2011 – March 2012, this project explored how such observations can be applied to assist the development of global cloud-permitting models through evaluating and correcting model biases in cloud statistics. The main accomplishment of this project were made in four categories: generating observational products for model evaluation, using AMIE/DYNAMO observations to validate global model simulations, using AMIE/DYNAMO observations in numerical studies of cloud-permitting models, and providing leadership in the field. Results from this project provide valuablemore » information for building a seamless bridge between DOE ASR program’s component on process level understanding of cloud processes in the tropics and RGCM focus on global variability and regional extremes. In particular, experience gained from this project would be directly applicable to evaluation and improvements of ACME, especially as it transitions to a non-hydrostatic variable resolution model.« less

Global Sensitivity Analysis for Process Identification under Model Uncertainty

NASA Astrophysics Data System (ADS)

Ye, M.; Dai, H.; Walker, A. P.; Shi, L.; Yang, J.

2015-12-01

The environmental system consists of various physical, chemical, and biological processes, and environmental models are always built to simulate these processes and their interactions. For model building, improvement, and validation, it is necessary to identify important processes so that limited resources can be used to better characterize the processes. While global sensitivity analysis has been widely used to identify important processes, the process identification is always based on deterministic process conceptualization that uses a single model for representing a process. However, environmental systems are complex, and it happens often that a single process may be simulated by multiple alternative models. Ignoring the model uncertainty in process identification may lead to biased identification in that identified important processes may not be so in the real world. This study addresses this problem by developing a new method of global sensitivity analysis for process identification. The new method is based on the concept of Sobol sensitivity analysis and model averaging. Similar to the Sobol sensitivity analysis to identify important parameters, our new method evaluates variance change when a process is fixed at its different conceptualizations. The variance considers both parametric and model uncertainty using the method of model averaging. The method is demonstrated using a synthetic study of groundwater modeling that considers recharge process and parameterization process. Each process has two alternative models. Important processes of groundwater flow and transport are evaluated using our new method. The method is mathematically general, and can be applied to a wide range of environmental problems.

Comparative assessment of several post-processing methods for correcting evapotranspiration forecasts derived from TIGGE datasets.

NASA Astrophysics Data System (ADS)

Tian, D.; Medina, H.

2017-12-01

Post-processing of medium range reference evapotranspiration (ETo) forecasts based on numerical weather prediction (NWP) models has the potential of improving the quality and utility of these forecasts. This work compares the performance of several post-processing methods for correcting ETo forecasts over the continental U.S. generated from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database using data from Europe (EC), the United Kingdom (MO), and the United States (NCEP). The pondered post-processing techniques are: simple bias correction, the use of multimodels, the Ensemble Model Output Statistics (EMOS, Gneitting et al., 2005) and the Bayesian Model Averaging (BMA, Raftery et al., 2005). ETo estimates based on quality-controlled U.S. Regional Climate Reference Network measurements, and computed with the FAO 56 Penman Monteith equation, are adopted as baseline. EMOS and BMA are generally the most efficient post-processing techniques of the ETo forecasts. Nevertheless, the simple bias correction of the best model is commonly much more rewarding than using multimodel raw forecasts. Our results demonstrate the potential of different forecasting and post-processing frameworks in operational evapotranspiration and irrigation advisory systems at national scale.

Unbiased total electron content (UTEC), their fluctuations, and correlation with seismic activity over Japan

NASA Astrophysics Data System (ADS)

Cornely, Pierre-Richard; Hughes, John

2018-02-01

Earthquakes are among the most dangerous events that occur on earth and many scientists have been investigating the underlying processes that take place before earthquakes occur. These investigations are fueling efforts towards developing both single and multiple parameter earthquake forecasting methods based on earthquake precursors. One potential earthquake precursor parameter that has received significant attention within the last few years is the ionospheric total electron content (TEC). Despite its growing popularity as an earthquake precursor, TEC has been under great scrutiny because of the underlying biases associated with the process of acquiring and processing TEC data. Future work in the field will need to demonstrate our ability to acquire TEC data with the least amount of biases possible thereby preserving the integrity of the data. This paper describes a process for removing biases using raw TEC data from the standard Rinex files obtained from any global positioning satellites system. The process is based on developing an unbiased TEC (UTEC) data and model that can be more adaptable to serving as a precursor signal for earthquake forecasting. The model was used during the days and hours leading to the earthquake off the coast of Tohoku, Japan on March 11, 2011 with interesting results. The model takes advantage of the large amount of data available from the GPS Earth Observation Network of Japan to display near real-time UTEC data as the earthquake approaches and for a period of time after the earthquake occurred.

Correlation Dimension Estimates of Global and Local Temperature Data.

NASA Astrophysics Data System (ADS)

Wang, Qiang

1995-11-01

The author has attempted to detect the presence of low-dimensional deterministic chaos in temperature data by estimating the correlation dimension with the Hill estimate that has been recently developed by Mikosch and Wang. There is no convincing evidence of low dimensionality with either global dataset (Southern Hemisphere monthly average temperatures from 1858 to 1984) or local temperature dataset (daily minimums at Auckland, New Zealand). Any apparent reduction in the dimension estimates appears to be due large1y, if not entirely, to effects of statistical bias, but neither is it a purely random stochastic process. The dimension of the climatic attractor may be significantly larger than 10.

How does dynamical downscaling affect model biases and future projections of explosive extratropical cyclones along North America's Atlantic coast?

NASA Astrophysics Data System (ADS)

Seiler, C.; Zwiers, F. W.; Hodges, K. I.; Scinocca, J. F.

2018-01-01

Explosive extratropical cyclones (EETCs) are rapidly intensifying low pressure systems that generate severe weather along North America's Atlantic coast. Global climate models (GCMs) tend to simulate too few EETCs, perhaps partly due to their coarse horizontal resolution and poorly resolved moist diabatic processes. This study explores whether dynamical downscaling can reduce EETC frequency biases, and whether this affects future projections of storms along North America's Atlantic coast. A regional climate model (CanRCM4) is forced with the CanESM2 GCM for the periods 1981 to 2000 and 2081 to 2100. EETCs are tracked from relative vorticity using an objective feature tracking algorithm. CanESM2 simulates 38% fewer EETC tracks compared to reanalysis data, which is consistent with a negative Eady growth rate bias (-0.1 day^{-1}). Downscaling CanESM2 with CanRCM4 increases EETC frequency by one third, which reduces the frequency bias to -22%, and increases maximum EETC precipitation by 22%. Anthropogenic greenhouse gas forcing is projected to decrease EETC frequency (-15%, -18%) and Eady growth rate (-0.2 day^{-1}, -0.2 day^{-1}), and increase maximum EETC precipitation (46%, 52%) in CanESM2 and CanRCM4, respectively. The limited effect of dynamical downscaling on EETC frequency projections is consistent with the lack of impact on the maximum Eady growth rate. The coarse spatial resolution of GCMs presents an important limitation for simulating extreme ETCs, but Eady growth rate biases are likely just as relevant. Further bias reductions could be achieved by addressing processes that lead to an underestimation of lower tropospheric meridional temperature gradients.

Visual working memory for global, object, and part-based information.

PubMed

Patterson, Michael D; Bly, Benjamin Martin; Porcelli, Anthony J; Rypma, Bart

2007-06-01

We investigated visual working memory for novel objects and parts of novel objects. After a delay period, participants showed strikingly more accurate performance recognizing a single whole object than the parts of that object. This bias to remember whole objects, rather than parts, persisted even when the division between parts was clearly defined and the parts were disconnected from each other so that, in order to remember the single whole object, the participants needed to mentally combine the parts. In addition, the bias was confirmed when the parts were divided by color. These experiments indicated that holistic perceptual-grouping biases are automatically used to organize storage in visual working memory. In addition, our results suggested that the bias was impervious to top-down consciously directed control, because when task demands were manipulated through instruction and catch trials, the participants still recognized whole objects more quickly and more accurately than their parts. This bias persisted even when the whole objects were novel and the parts were familiar. We propose that visual working memory representations depend primarily on the global configural properties of whole objects, rather than part-based representations, even when the parts themselves can be clearly perceived as individual objects. This global configural bias beneficially reduces memory load on a capacity-limited system operating in a complex visual environment, because fewer distinct items must be remembered.

Evaluation of Near-Tropopause Ozone Distributions in the Global Modeling Initiative Combined Stratosphere/Troposphere Model with Ozonesonde Data

NASA Technical Reports Server (NTRS)

Considine, David B.; Logan, Jennifer A.; Olsen, Mark A.

2008-01-01

The NASA Global Modeling Initiative has developed a combined stratosphere/troposphere chemistry and transport model which fully represents the processes governing atmospheric composition near the tropopause. We evaluate model ozone distributions near the tropopause, using two high vertical resolution monthly mean ozone profile climatologies constructed with ozonesonde data, one by averaging on pressure levels and the other relative to the thermal tropopause. Model ozone is high biased at the SH tropical and NH midlatitude tropopause by approx. 45% in a 4 deg. latitude x 5 deg. longitude model simulation. Increasing the resolution to 2 deg. x 2.5 deg. increases the NH tropopause high bias to approx. 60%, but decreases the tropical tropopause bias to approx. 30%, an effect of a better-resolved residual circulation. The tropopause ozone biases appear not to be due to an overly vigorous residual circulation or excessive stratosphere/troposphere exchange, but are more likely due to insufficient vertical resolution or excessive vertical diffusion near the tropopause. In the upper troposphere and lower stratosphere, model/measurement intercomparisons are strongly affected by the averaging technique. NH and tropical mean model lower stratospheric biases are less than 20%. In the upper troposphere, the 2 deg. x 2.5 deg. simulation exhibits mean high biases of approx. 20% and approx. 35% during April in the tropics and NH midlatitudes, respectively, compared to the pressure averaged climatology. However, relative-to-tropopause averaging produces upper troposphere high biases of approx. 30% and 70% in the tropics and NH midlatitudes. This is because relative-to-tropopause averaging better preserves large cross-tropopause O3 gradients, which are seen in the daily sonde data, but not in daily model profiles. The relative annual cycle of ozone near the tropopause is reproduced very well in the model Northern Hemisphere midlatitudes. In the tropics, the model amplitude of the near tropopause annual cycle is weak. This is likely due to the annual amplitude of mean vertical upwelling near the tropopause, which analysis suggests is approx. 30% weaker than in the real atmosphere.

Using Perturbed Physics Ensembles and Machine Learning to Select Parameters for Reducing Regional Biases in a Global Climate Model

NASA Astrophysics Data System (ADS)

Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.

2017-12-01

This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.

A Statistical Bias Correction Tool for Generating Climate Change Scenarios in Indonesia based on CMIP5 Datasets

NASA Astrophysics Data System (ADS)

Faqih, A.

2017-03-01

Providing information regarding future climate scenarios is very important in climate change study. The climate scenario can be used as basic information to support adaptation and mitigation studies. In order to deliver future climate scenarios over specific region, baseline and projection data from the outputs of global climate models (GCM) is needed. However, due to its coarse resolution, the data have to be downscaled and bias corrected in order to get scenario data with better spatial resolution that match the characteristics of the observed data. Generating this downscaled data is mostly difficult for scientist who do not have specific background, experience and skill in dealing with the complex data from the GCM outputs. In this regards, it is necessary to develop a tool that can be used to simplify the downscaling processes in order to help scientist, especially in Indonesia, for generating future climate scenario data that can be used for their climate change-related studies. In this paper, we introduce a tool called as “Statistical Bias Correction for Climate Scenarios (SiBiaS)”. The tool is specially designed to facilitate the use of CMIP5 GCM data outputs and process their statistical bias corrections relative to the reference data from observations. It is prepared for supporting capacity building in climate modeling in Indonesia as part of the Indonesia 3rd National Communication (TNC) project activities.

Climate-driven uncertainties in modeling terrestrial gross primary production: a site level to global-scale analysis.

PubMed

Barman, Rahul; Jain, Atul K; Liang, Miaoling

2014-05-01

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis-driven GPP bias was significantly positive with respect to the observed meteorology-driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m(-2)  yr(-1) across sites (ca. 15% of site level GPP). At the northern mid-/high-latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20-30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short-wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site-level reanalysis-driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate-driven uncertainties in carbon, energy, and water fluxes using a single modeling framework. © 2013 John Wiley & Sons Ltd.

Impact of a statistical bias correction on the projected simulated hydrological changes obtained from three GCMs and two hydrology models

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio

2010-05-01

Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.

On the wintertime low bias of Northern Hemisphere carbon monoxide found in global model simulations

NASA Astrophysics Data System (ADS)

Stein, O.; Schultz, M. G.; Bouarar, I.; Clark, H.; Huijnen, V.; Gaudel, A.; George, M.; Clerbaux, C.

2014-09-01

Despite the developments in the global modelling of chemistry and of the parameterization of the physical processes, carbon monoxide (CO) concentrations remain underestimated during Northern Hemisphere (NH) winter by most state-of-the-art chemistry transport models. The consequential model bias can in principle originate from either an underestimation of CO sources or an overestimation of its sinks. We address both the role of surface sources and sinks with a series of MOZART (Model for Ozone And Related Tracers) model sensitivity studies for the year 2008 and compare our results to observational data from ground-based stations, satellite observations, and vertical profiles from measurements on passenger aircraft. In our base case simulation using MACCity (Monitoring Atmospheric Composition and Climate project) anthropogenic emissions, the near-surface CO mixing ratios are underestimated in the Northern Hemisphere by more than 20 ppb from December to April, with the largest bias of up to 75 ppb over Europe in January. An increase in global biomass burning or biogenic emissions of CO or volatile organic compounds (VOCs) is not able to reduce the annual course of the model bias and yields concentrations over the Southern Hemisphere which are too high. Raising global annual anthropogenic emissions with a simple scaling factor results in overestimations of surface mixing ratios in most regions all year round. Instead, our results indicate that anthropogenic CO and, possibly, VOC emissions in the MACCity inventory are too low for the industrialized countries only during winter and spring. Reasonable agreement with observations can only be achieved if the CO emissions are adjusted seasonally with regionally varying scaling factors. A part of the model bias could also be eliminated by exchanging the original resistance-type dry deposition scheme with a parameterization for CO uptake by oxidation from soil bacteria and microbes, which reduces the boreal winter dry deposition fluxes. The best match to surface observations, satellite retrievals, and aircraft observations was achieved when the modified dry deposition scheme was combined with increased wintertime road traffic emissions over Europe and North America (factors up to 4.5 and 2, respectively). One reason for the apparent underestimation of emissions may be an exaggerated downward trend in the Representative Concentration Pathway (RCP) 8.5 scenario in these regions between 2000 and 2010, as this scenario was used to extrapolate the MACCity emissions from their base year 2000. This factor is potentially amplified by a lack of knowledge about the seasonality of emissions. A methane lifetime of 9.7 yr for our basic model and 9.8 yr for the optimized simulation agrees well with current estimates of global OH, but we cannot fully exclude a potential effect from errors in the geographical and seasonal distribution of OH concentrations on the modelled CO.

Visuoconstructive abilities and visuospatial memory in autism spectrum disorder without intellectual disability: Is the role of local bias specific to the cognitive domain tested?

PubMed

Cardillo, Ramona; Menazza, Cristina; Mammarella, Irene C

2018-06-07

Visuospatial processing in autism spectrum disorder (ASD) without intellectual disability remains only partly understood. The aim of the present study was to investigate global versus local visuospatial processing in individuals with ASD, comparing them with typically developing (TD) controls in visuoconstructive and visuospatial memory tasks. There were 21 participants with ASD without intellectual disability, and 21 TD controls matched for chronological age (M = 161.37 months, SD = 38.19), gender, and perceptual reasoning index who were tested. Participants were administered tasks assessing the visuoconstructive domain and involving fine motor skills, and visuospatial memory tasks in which visuospatial information had to be manipulated mentally. Using a mixed-effects model approach, our results showed different effects of local bias in the ASD group, depending on the domain considered: the use of a local approach only emerged for the visuoconstructive domain-in which fine motor skills were involved. These results seem to suggest that the local bias typical of the cognitive profile of ASD without intellectual disability could be a property of specific cognitive domains rather than a central mechanism. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Non-stationary Bias Correction of Monthly CMIP5 Temperature Projections over China using a Residual-based Bagging Tree Model

NASA Astrophysics Data System (ADS)

Yang, T.; Lee, C.

2017-12-01

The biases in the Global Circulation Models (GCMs) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from the assumption that model bias is stationary. This paper provides a non-stationary bias correction model, termed Residual-based Bagging Tree (RBT) model, to reduce simulation biases and to quantify the contributions of single models. Specifically, the proposed model estimates the residuals between individual models and observations, and takes the differences between observations and the ensemble mean into consideration during the model training process. A case study is conducted for 10 major river basins in Mainland China during different seasons. Results show that the proposed model is capable of providing accurate and stable predictions while including the non-stationarities into the modeling framework. Significant reductions in both bias and root mean squared error are achieved with the proposed RBT model, especially for the central and western parts of China. The proposed RBT model has consistently better performance in reducing biases when compared to the raw ensemble mean, the ensemble mean with simple additive bias correction, and the single best model for different seasons. Furthermore, the contribution of each single GCM in reducing the overall bias is quantified. The single model importance varies between 3.1% and 7.2%. For different future scenarios (RCP 2.6, RCP 4.5, and RCP 8.5), the results from RBT model suggest temperature increases of 1.44 ºC, 2.59 ºC, and 4.71 ºC by the end of the century, respectively, when compared to the average temperature during 1970 - 1999.

Partisan differences in the relationship between newspaper coverage and concern over global warming.

PubMed

Zhao, Xiaoquan; Rolfe-Redding, Justin; Kotcher, John E

2016-07-01

The effects of news media on public opinion about global warming have been a topic of much interest in both academic and popular discourse. Empirical evidence in this regard, however, is still limited and somewhat mixed. This study used data from the 2006 General Social Survey in combination with a content analysis of newspaper coverage of the same time period to examine the relationship between general news climate and public concern about global warming. Results showed a pattern of political polarization, with increased coverage associated with growing divergence between Democrats and Republicans. Further analysis also showed evidence of reactivity in partisan response to coverage from different news outlets. These findings point to a particular form of politically motivated, biased processing of news information. © The Author(s) 2014.

Global and Regional Evaluation of Energy for Water

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yaling; Hejazi, Mohamad; Kyle, Page

Despite significant effort to quantify the inter-dependence of the water and energy sectors, global requirements of energy for water (E4W) are still poorly understood, which may result in biases in projections and consequently in water and energy management and policy. This study estimates water-related energy consumption by water source, sector, and process, for 14 global regions from 1973 to 2012. Globally, E4W amounted to 10.2 ± 5 EJ of primary energy consumption in 2010, accounting for 1.2–3% of total global primary energy consumption, of which 58% pertains to surface water, 30% to groundwater, and 12% to non-fresh water, assuming medianmore » energy intensity levels. The sectoral E4W allocation includes municipal (45%), industrial (30%), and agricultural (25%), and main process-level contributions are from source/conveyance (39%), water purification (27%), water distribution (12%) and wastewater treatment (18%). While the USA was the largest E4W consumer from the 1970’s until the 2000’s, the largest consumers at present are the Middle East, India, and China, driven by rapid growth in desalination, groundwater-based irrigation, and industrial and municipal water use, respectively. The improved understanding of global E4W will enable enhanced consistency of both water and energy representations in integrated assessment models.« less

Self-Orientation Modulates the Neural Correlates of Global and Local Processing

PubMed Central

Liddell, Belinda J.; Das, Pritha; Battaglini, Eva; Malhi, Gin S.; Felmingham, Kim L.; Whitford, Thomas J.; Bryant, Richard A.

2015-01-01

Differences in self-orientation (or “self-construal”) may affect how the visual environment is attended, but the neural and cultural mechanisms that drive this remain unclear. Behavioral studies have demonstrated that people from Western backgrounds with predominant individualistic values are perceptually biased towards local-level information; whereas people from non-Western backgrounds that support collectivist values are preferentially focused on contextual and global-level information. In this study, we compared two groups differing in predominant individualistic (N = 15) vs collectivistic (N = 15) self-orientation. Participants completed a global/local perceptual conflict task whilst undergoing functional Magnetic Resonance Imaging (fMRI) scanning. When participants high in individualistic values attended to the global level (ignoring the local level), greater activity was observed in the frontoparietal and cingulo-opercular networks that underpin attentional control, compared to the match (congruent) baseline. Participants high in collectivistic values activated similar attentional control networks o only when directly compared with global processing. This suggests that global interference was stronger than local interference in the conflict task in the collectivistic group. Both groups showed increased activity in dorsolateral prefrontal regions involved in resolving perceptual conflict during heightened distractor interference. The findings suggest that self-orientation may play an important role in driving attention networks to facilitate interaction with the visual environment. PMID:26270820

Self-Orientation Modulates the Neural Correlates of Global and Local Processing.

PubMed

Liddell, Belinda J; Das, Pritha; Battaglini, Eva; Malhi, Gin S; Felmingham, Kim L; Whitford, Thomas J; Bryant, Richard A

2015-01-01

Differences in self-orientation (or "self-construal") may affect how the visual environment is attended, but the neural and cultural mechanisms that drive this remain unclear. Behavioral studies have demonstrated that people from Western backgrounds with predominant individualistic values are perceptually biased towards local-level information; whereas people from non-Western backgrounds that support collectivist values are preferentially focused on contextual and global-level information. In this study, we compared two groups differing in predominant individualistic (N = 15) vs collectivistic (N = 15) self-orientation. Participants completed a global/local perceptual conflict task whilst undergoing functional Magnetic Resonance Imaging (fMRI) scanning. When participants high in individualistic values attended to the global level (ignoring the local level), greater activity was observed in the frontoparietal and cingulo-opercular networks that underpin attentional control, compared to the match (congruent) baseline. Participants high in collectivistic values activated similar attentional control networks o only when directly compared with global processing. This suggests that global interference was stronger than local interference in the conflict task in the collectivistic group. Both groups showed increased activity in dorsolateral prefrontal regions involved in resolving perceptual conflict during heightened distractor interference. The findings suggest that self-orientation may play an important role in driving attention networks to facilitate interaction with the visual environment.

Evaluation of climate-related carbon turnover processes in global vegetation models for boreal and temperate forests.

PubMed

Thurner, Martin; Beer, Christian; Ciais, Philippe; Friend, Andrew D; Ito, Akihiko; Kleidon, Axel; Lomas, Mark R; Quegan, Shaun; Rademacher, Tim T; Schaphoff, Sibyll; Tum, Markus; Wiltshire, Andy; Carvalhais, Nuno

2017-08-01

Turnover concepts in state-of-the-art global vegetation models (GVMs) account for various processes, but are often highly simplified and may not include an adequate representation of the dominant processes that shape vegetation carbon turnover rates in real forest ecosystems at a large spatial scale. Here, we evaluate vegetation carbon turnover processes in GVMs participating in the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP, including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT) using estimates of vegetation carbon turnover rate (k) derived from a combination of remote sensing based products of biomass and net primary production (NPP). We find that current model limitations lead to considerable biases in the simulated biomass and in k (severe underestimations by all models except JeDi and VISIT compared to observation-based average k), likely contributing to underestimation of positive feedbacks of the northern forest carbon balance to climate change caused by changes in forest mortality. A need for improved turnover concepts related to frost damage, drought, and insect outbreaks to better reproduce observation-based spatial patterns in k is identified. As direct frost damage effects on mortality are usually not accounted for in these GVMs, simulated relationships between k and winter length in boreal forests are not consistent between different regions and strongly biased compared to the observation-based relationships. Some models show a response of k to drought in temperate forests as a result of impacts of water availability on NPP, growth efficiency or carbon balance dependent mortality as well as soil or litter moisture effects on leaf turnover or fire. However, further direct drought effects such as carbon starvation (only in HYBRID4) or hydraulic failure are usually not taken into account by the investigated GVMs. While they are considered dominant large-scale mortality agents, mortality mechanisms related to insects and pathogens are not explicitly treated in these models. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli.

PubMed

Alink, Arjen; Krugliak, Alexandra; Walther, Alexander; Kriegeskorte, Nikolaus

2013-01-01

The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability might alternatively arise from global orientation-preference maps. Such global maps across V1 could result from bottom-up processing, if the preferences of V1 neurons were biased toward particular orientations (e.g., radial from fixation, or cardinal, i.e., vertical or horizontal). Global maps could also arise from local recurrent or top-down processing, reflecting pre-attentive perceptual grouping, attention spreading, or predictive coding of global form. Here we investigate whether fMRI orientation decoding with 2-mm voxels requires (a) globally coherent orientation stimuli and/or (b) global-scale patterns of V1 activity. We used opposite-orientation gratings (balanced about the cardinal orientations) and spirals (balanced about the radial orientation), along with novel patch-swapped variants of these stimuli. The two stimuli of a patch-swapped pair have opposite orientations everywhere (like their globally coherent parent stimuli). However, the two stimuli appear globally similar, a patchwork of opposite orientations. We find that all stimulus pairs are robustly decodable, demonstrating that fMRI orientation decoding does not require globally coherent orientation stimuli. Furthermore, decoding remained robust after spatial high-pass filtering for all stimuli, showing that fine-grained components of the fMRI patterns reflect visual orientations. Consistent with previous studies, we found evidence for global radial and vertical preference maps in V1. However, these were weak or absent for patch-swapped stimuli, suggesting that global preference maps depend on globally coherent orientations and might arise through recurrent or top-down processes related to the perception of global form.

No psychological effect of color context in a low level vision task

PubMed Central

Pedley, Adam; Wade, Alex R

2013-01-01

Background: A remarkable series of recent papers have shown that colour can influence performance in cognitive tasks. In particular, they suggest that viewing a participant number printed in red ink or other red ancillary stimulus elements improves performance in tasks requiring local processing and impedes performance in tasks requiring global processing whilst the reverse is true for the colour blue. The tasks in these experiments require high level cognitive processing such as analogy solving or remote association tests and the chromatic effect on local vs. global processing is presumed to involve widespread activation of the autonomic nervous system. If this is the case, we might expect to see similar effects on all local vs. global task comparisons. To test this hypothesis, we asked whether chromatic cues also influence performance in tasks involving low level visual feature integration. Methods: Subjects performed either local (contrast detection) or global (form detection) tasks on achromatic dynamic Glass pattern stimuli. Coloured instructions, target frames and fixation points were used to attempt to bias performance to different task types. Based on previous literature, we hypothesised that red cues would improve performance in the (local) contrast detection task but would impede performance in the (global) form detection task.  Results: A two-way, repeated measures, analysis of covariance (2×2 ANCOVA) with gender as a covariate, revealed no influence of colour on either task, F(1,29) = 0.289, p = 0.595, partial η 2 = 0.002. Additional analysis revealed no significant differences in only the first attempts of the tasks or in the improvement in performance between trials. Discussion: We conclude that motivational processes elicited by colour perception do not influence neuronal signal processing in the early visual system, in stark contrast to their putative effects on processing in higher areas. PMID:25075280

No psychological effect of color context in a low level vision task.

PubMed

Pedley, Adam; Wade, Alex R

2013-01-01

A remarkable series of recent papers have shown that colour can influence performance in cognitive tasks. In particular, they suggest that viewing a participant number printed in red ink or other red ancillary stimulus elements improves performance in tasks requiring local processing and impedes performance in tasks requiring global processing whilst the reverse is true for the colour blue. The tasks in these experiments require high level cognitive processing such as analogy solving or remote association tests and the chromatic effect on local vs. global processing is presumed to involve widespread activation of the autonomic nervous system. If this is the case, we might expect to see similar effects on all local vs. global task comparisons. To test this hypothesis, we asked whether chromatic cues also influence performance in tasks involving low level visual feature integration. Subjects performed either local (contrast detection) or global (form detection) tasks on achromatic dynamic Glass pattern stimuli. Coloured instructions, target frames and fixation points were used to attempt to bias performance to different task types. Based on previous literature, we hypothesised that red cues would improve performance in the (local) contrast detection task but would impede performance in the (global) form detection task.  A two-way, repeated measures, analysis of covariance (2×2 ANCOVA) with gender as a covariate, revealed no influence of colour on either task, F(1,29) = 0.289, p = 0.595, partial η (2) = 0.002. Additional analysis revealed no significant differences in only the first attempts of the tasks or in the improvement in performance between trials. We conclude that motivational processes elicited by colour perception do not influence neuronal signal processing in the early visual system, in stark contrast to their putative effects on processing in higher areas.

Printed Circuit Board Surface Finish and Effects of Chloride Contamination, Electric Field, and Humidity on Corrosion Reliability

NASA Astrophysics Data System (ADS)

Conseil-Gudla, Hélène; Jellesen, Morten S.; Ambat, Rajan

2017-02-01

Corrosion reliability is a serious issue today for electronic devices, components, and printed circuit boards (PCBs) due to factors such as miniaturization, globalized manufacturing practices which can lead to process-related residues, and global usage effects such as bias voltage and unpredictable user environments. The investigation reported in this paper focuses on understanding the synergistic effect of such parameters, namely contamination, humidity, PCB surface finish, pitch distance, and potential bias on leakage current under different humidity levels, and electrochemical migration probability under condensing conditions. Leakage currents were measured on interdigitated comb test patterns with three different types of surface finish typically used in the electronics industry, namely gold, copper, and tin. Susceptibility to electrochemical migration was studied under droplet conditions. The level of base leakage current (BLC) was similar for the different surface finishes and NaCl contamination levels up to relative humidity (RH) of 65%. A significant increase in leakage current was found for comb patterns contaminated with NaCl above 70% to 75% RH, close to the deliquescent RH of NaCl. Droplet tests on Cu comb patterns with varying pitch size showed that the initial BLC before dendrite formation increased with increasing NaCl contamination level, whereas electrochemical migration and the frequency of dendrite formation increased with bias voltage. The effect of different surface finishes on leakage current under humid conditions was not very prominent.

Nepal and Papua Airborne Gravity Surveys

NASA Astrophysics Data System (ADS)

Olesen, A. V.; Forsberg, R.; Kasenda, F.; Einarsson, I.; Manandhar, N.

2011-12-01

Airborne gravimetry offers a fast and economic way to cover vast areas and it allows access to otherwise difficult accessible areas like mountains, jungles and the near coastal zone. It has the potential to deliver high resolution and bias free data that may bridge the spectral gap between global satellite gravity models and the high resolution gravity information embedded in digital terrain models. DTU Space has for more than a decade done airborne gravity surveys in many parts of the world. Most surveys were done with a LaCoste & Romberg S-meter updated for airborne use. This instrument has proven to deliver near bias free data when properly processed. A Chekan AM gravimeter was recently added to the airborne gravity mapping system and will potentially enhance the spatial resolution and the robustness of the system. This paper will focus on results from two recent surveys over Nepal, flown in December 2010, and over Papua (eastern Indonesia), flown in May and June 2011. Both surveys were flown with the new double gravimeter setup and initial assessment of system performance indicates improved spatial resolution compared to the single gravimeter system. Comparison to EGM08 and to the most recent GOCE models highlights the impact of the new airborne gravity data in both cases. A newly computed geoid model for Nepal based on the airborne data allows for a more precise definition of the height of Mt. Everest in a global height system. This geoid model suggests that the height of Mt. Everest should be increased by approximately 1 meter. The paper will also briefly discuss system setup and will highlight a few essential processing steps that ensure that bias problems are minimized and spatial resolution enhanced.

Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments

NASA Astrophysics Data System (ADS)

van Peet, Jacob C. A.; van der A, Ronald J.; Kelder, Hennie M.; Levelt, Pieternel F.

2018-02-01

A three-dimensional global ozone distribution has been derived from assimilation of ozone profiles that were observed by satellites. By simultaneous assimilation of ozone profiles retrieved from the nadir looking satellite instruments Global Ozone Monitoring Experiment 2 (GOME-2) and Ozone Monitoring Instrument (OMI), which measure the atmosphere at different times of the day, the quality of the derived atmospheric ozone field has been improved. The assimilation is using an extended Kalman filter in which chemical transport model TM5 has been used for the forecast. The combined assimilation of both GOME-2 and OMI improves upon the assimilation results of a single sensor. The new assimilation system has been demonstrated by processing 4 years of data from 2008 to 2011. Validation of the assimilation output by comparison with sondes shows that biases vary between -5 and +10 % between the surface and 100 hPa. The biases for the combined assimilation vary between -3 and +3 % in the region between 100 and 10 hPa where GOME-2 and OMI are most sensitive. This is a strong improvement compared to direct retrievals of ozone profiles from satellite observations.

Understanding Perspectives of African American Medicaid-Insured Women on the Process of Perinatal Care: An Opportunity for Systems Improvement.

PubMed

Roman, Lee Anne; Raffo, Jennifer E; Dertz, Katherine; Agee, Bonita; Evans, Denise; Penninga, Katherine; Pierce, Tiffany; Cunningham, Belinda; VanderMeulen, Peggy

2017-12-01

Objectives To address disparities in adverse birth outcomes, communities are challenged to improve the quality of health services and foster systems integration. The purpose of this study was to explore the perspectives of Medicaid-insured women about their experiences of perinatal care (PNC) across a continuum of clinical and community-based services. Methods Three focus groups (N = 21) were conducted and thematic analysis methods were used to identify basic and global themes about experiences of care. Women were recruited through a  local Federal Healthy Start (HS) program in Michigan  that targets services to African American women. Results Four basic themes were identified: (1) Pursuit of PNC; (2) Experiences of traditional PNC; (3) Enhanced prenatal and postnatal care; and (4) Women's health: A missed opportunity. Two global themes were also identified: (1) Communication with providers, and (2) Perceived socio-economic and racial bias. Many women experienced difficulties engaging in early care, getting more help, and understanding and communicating with their providers, with some reporting socio-economic and racial bias in care. Delays in PNC limited early access to HS and enhanced prenatal care (EPC) programs with little evidence of supportive transitions to primary care. Notably, women's narratives revealed few connections among clinical and community-based services. Conclusions The process of participating in PNC and community-based programs is challenging for women, especially for those with multiple health problems and living in difficult life circumstances. PNC, HS and other EPC programs could partner to streamline processes, improve the content and process of care, and enhance engagement in services.

Global GNSS processing based on the raw observation approach

NASA Astrophysics Data System (ADS)

Strasser, Sebastian; Zehentner, Norbert; Mayer-Gürr, Torsten

2017-04-01

Many global navigation satellite system (GNSS) applications, e.g. Precise Point Positioning (PPP), require high-quality GNSS products, such as precise GNSS satellite orbits and clocks. These products are routinely determined by analysis centers of the International GNSS Service (IGS). The current processing methods of the analysis centers make use of the ionosphere-free linear combination to reduce the ionospheric influence. Some of the analysis centers also form observation differences, in general double-differences, to eliminate several additional error sources. The raw observation approach is a new GNSS processing approach that was developed at Graz University of Technology for kinematic orbit determination of low Earth orbit (LEO) satellites and subsequently adapted to global GNSS processing in general. This new approach offers some benefits compared to well-established approaches, such as a straightforward incorporation of new observables due to the avoidance of observation differences and linear combinations. This becomes especially important in view of the changing GNSS landscape with two new systems, the European system Galileo and the Chinese system BeiDou, currently in deployment. GNSS products generated at Graz University of Technology using the raw observation approach currently comprise precise GNSS satellite orbits and clocks, station positions and clocks, code and phase biases, and Earth rotation parameters. To evaluate the new approach, products generated using the Global Positioning System (GPS) constellation and observations from the global IGS station network are compared to those of the IGS analysis centers. The comparisons show that the products generated at Graz University of Technology are on a similar level of quality to the products determined by the IGS analysis centers. This confirms that the raw observation approach is applicable to global GNSS processing. Some areas requiring further work have been identified, enabling future improvements of the method.

Ensemble perception of color in autistic adults.

PubMed

Maule, John; Stanworth, Kirstie; Pellicano, Elizabeth; Franklin, Anna

2017-05-01

Dominant accounts of visual processing in autism posit that autistic individuals have an enhanced access to details of scenes [e.g., weak central coherence] which is reflected in a general bias toward local processing. Furthermore, the attenuated priors account of autism predicts that the updating and use of summary representations is reduced in autism. Ensemble perception describes the extraction of global summary statistics of a visual feature from a heterogeneous set (e.g., of faces, sizes, colors), often in the absence of local item representation. The present study investigated ensemble perception in autistic adults using a rapidly presented (500 msec) ensemble of four, eight, or sixteen elements representing four different colors. We predicted that autistic individuals would be less accurate when averaging the ensembles, but more accurate in recognizing individual ensemble colors. The results were consistent with the predictions. Averaging was impaired in autism, but only when ensembles contained four elements. Ensembles of eight or sixteen elements were averaged equally accurately across groups. The autistic group also showed a corresponding advantage in rejecting colors that were not originally seen in the ensemble. The results demonstrate the local processing bias in autism, but also suggest that the global perceptual averaging mechanism may be compromised under some conditions. The theoretical implications of the findings and future avenues for research on summary statistics in autism are discussed. Autism Res 2017, 10: 839-851. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Ensemble perception of color in autistic adults

PubMed Central

Stanworth, Kirstie; Pellicano, Elizabeth; Franklin, Anna

2016-01-01

Dominant accounts of visual processing in autism posit that autistic individuals have an enhanced access to details of scenes [e.g., weak central coherence] which is reflected in a general bias toward local processing. Furthermore, the attenuated priors account of autism predicts that the updating and use of summary representations is reduced in autism. Ensemble perception describes the extraction of global summary statistics of a visual feature from a heterogeneous set (e.g., of faces, sizes, colors), often in the absence of local item representation. The present study investigated ensemble perception in autistic adults using a rapidly presented (500 msec) ensemble of four, eight, or sixteen elements representing four different colors. We predicted that autistic individuals would be less accurate when averaging the ensembles, but more accurate in recognizing individual ensemble colors. The results were consistent with the predictions. Averaging was impaired in autism, but only when ensembles contained four elements. Ensembles of eight or sixteen elements were averaged equally accurately across groups. The autistic group also showed a corresponding advantage in rejecting colors that were not originally seen in the ensemble. The results demonstrate the local processing bias in autism, but also suggest that the global perceptual averaging mechanism may be compromised under some conditions. The theoretical implications of the findings and future avenues for research on summary statistics in autism are discussed. Autism Res 2017, 10: 839–851. © 2016 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research PMID:27874263

C-GLORSv5: an improved multipurpose global ocean eddy-permitting physical reanalysis

NASA Astrophysics Data System (ADS)

Storto, Andrea; Masina, Simona

2016-11-01

Global ocean reanalyses combine in situ and satellite ocean observations with a general circulation ocean model to estimate the time-evolving state of the ocean, and they represent a valuable tool for a variety of applications, ranging from climate monitoring and process studies to downstream applications, initialization of long-range forecasts and regional studies. The purpose of this paper is to document the recent upgrade of C-GLORS (version 5), the latest ocean reanalysis produced at the Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC) that covers the meteorological satellite era (1980-present) and it is being updated in delayed time mode. The reanalysis is run at eddy-permitting resolution (1/4° horizontal resolution and 50 vertical levels) and consists of a three-dimensional variational data assimilation system, a surface nudging and a bias correction scheme. With respect to the previous version (v4), C-GLORSv5 contains a number of improvements. In particular, background- and observation-error covariances have been retuned, allowing a flow-dependent inflation in the globally averaged background-error variance. An additional constraint on the Arctic sea-ice thickness was introduced, leading to a realistic ice volume evolution. Finally, the bias correction scheme and the initialization strategy were retuned. Results document that the new reanalysis outperforms the previous version in many aspects, especially in representing the variability of global heat content and associated steric sea level in the last decade, the top 80 m ocean temperature biases and root mean square errors, and the Atlantic Ocean meridional overturning circulation; slight worsening in the high-latitude salinity and deep ocean temperature emerge though, providing the motivation for further tuning of the reanalysis system. The dataset is available in NetCDF format at doi:10.1594/PANGAEA.857995.

Systematic land climate and evapotranspiration biases in CMIP5 simulations.

PubMed

Mueller, B; Seneviratne, S I

2014-01-16

[1] Land climate is important for human population since it affects inhabited areas. Here we evaluate the realism of simulated evapotranspiration (ET), precipitation, and temperature in the CMIP5 multimodel ensemble on continental areas. For ET, a newly compiled synthesis data set prepared within the Global Energy and Water Cycle Experiment-sponsored LandFlux-EVAL project is used. The results reveal systematic ET biases in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations, with an overestimation in most regions, especially in Europe, Africa, China, Australia, Western North America, and part of the Amazon region. The global average overestimation amounts to 0.17 mm/d. This bias is more pronounced than in the previous CMIP3 ensemble (overestimation of 0.09 mm/d). Consistent with the ET overestimation, precipitation is also overestimated relative to existing reference data sets. We suggest that the identified biases in ET can explain respective systematic biases in temperature in many of the considered regions. The biases additionally display a seasonal dependence and are generally of opposite sign (ET underestimation and temperature overestimation) in boreal summer (June-August).

AGCM Biases in Evaporation Regime: Impacts on Soil Moisture Memory and Land-Atmosphere Feedback

NASA Technical Reports Server (NTRS)

Mahanama, Sarith P. P.; Koster, Randal D.

2005-01-01

Because precipitation and net radiation in an atmospheric general circulation model (AGCM) are typically biased relative to observations, the simulated evaporative regime of a region may be biased, with consequent negative effects on the AGCM s ability to translate an initialized soil moisture anomaly into an improved seasonal prediction. These potential problems are investigated through extensive offline analyses with the Mosaic land surface model (LSM). We first forced the LSM globally with a 15-year observations-based dataset. We then repeated the simulation after imposing a representative set of GCM climate biases onto the forcings - the observational forcings were scaled so that their mean seasonal cycles matched those simulated by the NSIPP-1 (NASA Global Modeling and Assimilation Office) AGCM over the same period-The AGCM s climate biases do indeed lead to significant biases in evaporative regime in certain regions, with the expected impacts on soil moisture memory timescales. Furthermore, the offline simulations suggest that the biased forcing in the AGCM should contribute to overestimated feedback in certain parts of North America - parts already identified in previous studies as having excessive feedback. The present study thus supports the notion that the reduction of climate biases in the AGCM will lead to more appropriate translations of soil moisture initialization into seasonal prediction skill.

Analysis and modeling of wafer-level process variability in 28 nm FD-SOI using split C-V measurements

NASA Astrophysics Data System (ADS)

Pradeep, Krishna; Poiroux, Thierry; Scheer, Patrick; Juge, André; Gouget, Gilles; Ghibaudo, Gérard

2018-07-01

This work details the analysis of wafer level global process variability in 28 nm FD-SOI using split C-V measurements. The proposed approach initially evaluates the native on wafer process variability using efficient extraction methods on split C-V measurements. The on-wafer threshold voltage (VT) variability is first studied and modeled using a simple analytical model. Then, a statistical model based on the Leti-UTSOI compact model is proposed to describe the total C-V variability in different bias conditions. This statistical model is finally used to study the contribution of each process parameter to the total C-V variability.

Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework

NASA Astrophysics Data System (ADS)

Raleigh, M. S.; Lundquist, J. D.; Clark, M. P.

2015-07-01

Physically based models provide insights into key hydrologic processes but are associated with uncertainties due to deficiencies in forcing data, model parameters, and model structure. Forcing uncertainty is enhanced in snow-affected catchments, where weather stations are scarce and prone to measurement errors, and meteorological variables exhibit high variability. Hence, there is limited understanding of how forcing error characteristics affect simulations of cold region hydrology and which error characteristics are most important. Here we employ global sensitivity analysis to explore how (1) different error types (i.e., bias, random errors), (2) different error probability distributions, and (3) different error magnitudes influence physically based simulations of four snow variables (snow water equivalent, ablation rates, snow disappearance, and sublimation). We use the Sobol' global sensitivity analysis, which is typically used for model parameters but adapted here for testing model sensitivity to coexisting errors in all forcings. We quantify the Utah Energy Balance model's sensitivity to forcing errors with 1 840 000 Monte Carlo simulations across four sites and five different scenarios. Model outputs were (1) consistently more sensitive to forcing biases than random errors, (2) generally less sensitive to forcing error distributions, and (3) critically sensitive to different forcings depending on the relative magnitude of errors. For typical error magnitudes found in areas with drifting snow, precipitation bias was the most important factor for snow water equivalent, ablation rates, and snow disappearance timing, but other forcings had a more dominant impact when precipitation uncertainty was due solely to gauge undercatch. Additionally, the relative importance of forcing errors depended on the model output of interest. Sensitivity analysis can reveal which forcing error characteristics matter most for hydrologic modeling.

The Earth System Science Pathfinder Orbiting Carbon Observatory (OCO) Mission

NASA Technical Reports Server (NTRS)

Crisp, David

2003-01-01

A viewgraph presentation describing the Earth System Science Pathfinder Orbiting Carbon Observatory (OCO) Mission is shown. The contents include: 1) Why CO2?; 2) What Processes Control CO2 Sinks?; 3) OCO Science Team; 4) Space-Based Measurements of CO2; 5) Driving Requirement: Precise, Bias-Free Global Measurements; 6) Making Precise CO2 Measurements from Space; 7) OCO Spatial Sampling Strategy; 8) OCO Observing Modes; 9) Implementation Approach; 10) The OCO Instrument; 11) The OCO Spacecraft; 12) OCO Will Fly in the A-Train; 13) Validation Program Ensures Accuracy and Minimizes Spatially Coherent Biases; 14) Can OCO Provide the Required Precision?; 15) O2 Column Retrievals with Ground-based FTS; 16) X(sub CO2) Retrieval Simulations; 17) Impact of Albedo and Aerosol Uncertainty on X(sub CO2) Retrievals; 18) Carbon Cycle Modeling Studies: Seasonal Cycle; 19) Carbon Cycle Modeling Studies: The North-South Gradient in CO2; 20) Carbon Cycle Modeling Studies: Effect of Diurnal Biases; 21) Project Status and Schedule; and 22) Summary.

Emotion perception accuracy and bias in face-to-face versus cyberbullying.

PubMed

Ciucci, Enrica; Baroncelli, Andrea; Nowicki, Stephen

2014-01-01

The authors investigated the association of traditional and cyber forms of bullying and victimization with emotion perception accuracy and emotion perception bias. Four basic emotions were considered (i.e., happiness, sadness, anger, and fear); 526 middle school students (280 females; M age = 12.58 years, SD = 1.16 years) were recruited, and emotionality was controlled. Results indicated no significant findings for girls. Boys with higher levels of traditional bullying did not show any deficit in perception accuracy of emotions, but they were prone to identify happiness and fear in faces when a different emotion was expressed; in addition, male cyberbullying was related to greater accuracy in recognizing fear. In terms of the victims, cyber victims had a global problem in recognizing emotions and a specific problem in processing anger and fear. It was concluded that emotion perception accuracy and bias were associated with bullying and victimization for boys not only in traditional settings but also in the electronic ones. Implications of these findings for possible intervention are discussed.

Positioning stability improvement with inter-system biases on multi-GNSS PPP

NASA Astrophysics Data System (ADS)

Choi, Byung-Kyu; Yoon, Hasu

2018-07-01

The availability of multiple signals from different Global Navigation Satellite System (GNSS) constellations provides opportunities for improving positioning accuracy and initial convergence time. With dual-frequency observations from the four constellations (GPS, GLONASS, Galileo, and BeiDou), it is possible to investigate combined GNSS precise point positioning (PPP) accuracy and stability. The differences between GNSS systems result in inter-system biases (ISBs). We consider several ISB values such as GPS-GLONASS, GPS-Galileo, and GPS-BeiDou. These biases are compliant with key parameters defined in the multi-GNSS PPP processing. In this study, we present a unified PPP method that sets ISB values as fixed or constant. A comprehensive analysis that includes satellite visibility, position dilution of precision, position accuracy is performed to evaluate a unified PPP method with constrained cut-off elevation angles. Compared to the conventional PPP solutions, our approach shows more stable positioning at a constrained cut-off elevation angle of 50 degrees.

Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis

NASA Astrophysics Data System (ADS)

Miyazaki, Kazuyuki; Bowman, Kevin

2017-07-01

The Atmospheric Chemistry Climate Model Intercomparison Project (ACCMIP) ensemble ozone simulations for the present day from the 2000 decade simulation results are evaluated by a state-of-the-art multi-constituent atmospheric chemical reanalysis that ingests multiple satellite data including the Tropospheric Emission Spectrometer (TES), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Measurement of Pollution in the Troposphere (MOPITT) for 2005-2009. Validation of the chemical reanalysis against global ozonesondes shows good agreement throughout the free troposphere and lower stratosphere for both seasonal and year-to-year variations, with an annual mean bias of less than 0.9 ppb in the middle and upper troposphere at the tropics and mid-latitudes. The reanalysis provides comprehensive spatiotemporal evaluation of chemistry-model performance that compliments direct ozonesonde comparisons, which are shown to suffer from significant sampling bias. The reanalysis reveals that the ACCMIP ensemble mean overestimates ozone in the northern extratropics by 6-11 ppb while underestimating by up to 18 ppb in the southern tropics over the Atlantic in the lower troposphere. Most models underestimate the spatial variability of the annual mean lower tropospheric concentrations in the extratropics of both hemispheres by up to 70 %. The ensemble mean also overestimates the seasonal amplitude by 25-70 % in the northern extratropics and overestimates the inter-hemispheric gradient by about 30 % in the lower and middle troposphere. A part of the discrepancies can be attributed to the 5-year reanalysis data for the decadal model simulations. However, these differences are less evident with the current sonde network. To estimate ozonesonde sampling biases, we computed model bias separately for global coverage and the ozonesonde network. The ozonesonde sampling bias in the evaluated model bias for the seasonal mean concentration relative to global coverage is 40-50 % over the western Pacific and east Indian Ocean and reaches 110 % over the equatorial Americas and up to 80 % for the global tropics. In contrast, the ozonesonde sampling bias is typically smaller than 30 % for the Arctic regions in the lower and middle troposphere. These systematic biases have implications for ozone radiative forcing and the response of chemistry to climate that can be further quantified as the satellite observational record extends to multiple decades.

A new approach to correct for absorbing aerosols in OMI UV

NASA Astrophysics Data System (ADS)

Arola, A.; Kazadzis, S.; Lindfors, A.; Krotkov, N.; Kujanpää, J.; Tamminen, J.; Bais, A.; di Sarra, A.; Villaplana, J. M.; Brogniez, C.; Siani, A. M.; Janouch, M.; Weihs, P.; Webb, A.; Koskela, T.; Kouremeti, N.; Meloni, D.; Buchard, V.; Auriol, F.; Ialongo, I.; Staneck, M.; Simic, S.; Smedley, A.; Kinne, S.

2009-11-01

Several validation studies of surface UV irradiance based on the Ozone Monitoring Instrument (OMI) satellite data have shown a high correlation with ground-based measurements but a positive bias in many locations. The main part of the bias can be attributed to the boundary layer aerosol absorption that is not accounted for in the current satellite UV algorithms. To correct for this shortfall, a post-correction procedure was applied, based on global climatological fields of aerosol absorption optical depth. These fields were obtained by using global aerosol optical depth and aerosol single scattering albedo data assembled by combining global aerosol model data and ground-based aerosol measurements from AERONET. The resulting improvements in the satellite-based surface UV irradiance were evaluated by comparing satellite and ground-based spectral irradiances at various European UV monitoring sites. The results generally showed a significantly reduced bias by 5-20%, a lower variability, and an unchanged, high correlation coefficient.

Determination of multi-GNSS pseudo-absolute code biases and verification of receiver tracking technology

NASA Astrophysics Data System (ADS)

Villiger, Arturo; Schaer, Stefan; Dach, Rolf; Prange, Lars; Jäggi, Adrian

2017-04-01

It is common to handle code biases in the Global Navigation Satellite System (GNSS) data analysis as conventional differential code biases (DCBs): P1-C1, P1-P2, and P2-C2. Due to the increasing number of signals and systems in conjunction with various tracking modes for the different signals (as defined in RINEX3 format), the number of DCBs would increase drastically and the bookkeeping becomes almost unbearable. The Center for Orbit Determination in Europe (CODE) has thus changed its processing scheme to observable-specific signal biases (OSB). This means that for each observation involved all related satellite and receiver biases are considered. The OSB contributions from various ionosphere analyses (geometry-free linear combination) using different observables and frequencies and from clock analyses (ionosphere-free linear combination) are then combined on normal equation level. By this, one consistent set of OSB values per satellite and receiver can be obtained that contains all information needed for GNSS-related processing. This advanced procedure of code bias handling is now also applied to the IGS (International GNSS Service) MGEX (Multi-GNSS Experiment) procedure at CODE. Results for the biases from the legacy IGS solution as well as the CODE MGEX processing (considering GPS, GLONASS, Galileo, BeiDou, and QZSS) are presented. The consistency with the traditional method is confirmed and the new results are discussed regarding the long-term stability. When processing code data, it is essential to know the true observable types in order to correct for the associated biases. CODE has been verifying the receiver tracking technologies for GPS based on estimated DCB multipliers (for the RINEX 2 case). With the change to OSB, the original verification approach was extended to search for the best fitting observable types based on known OSB values. In essence, a multiplier parameter is estimated for each involved GNSS observable type. This implies that we could recover, for receivers tracking a combination of signals, even the factors of these combinations. The verification of the observable types is crucial to identify the correct observable types of RINEX 2 data (which does not contain the signal modulation in comparison to RINEX 3). The correct information of the used observable types is essential for precise point positioning (PPP) applications and GNSS ambiguity resolution. Multi-GNSS OSBs and verified receiver tracking modes are essential to get best possible multi-GNSS solutions for geodynamic purposes and other applications.

"Hunting with a knife and ... fork": examining central coherence in autism, attention deficit/hyperactivity disorder, and typical development with a linguistic task.

PubMed

Booth, Rhonda; Happé, Francesca

2010-12-01

A local processing bias, referred to as "weak central coherence," has been postulated to underlie key aspects of autism spectrum disorder (ASD). Little research has examined whether individual differences in this cognitive style can be found in typical development, independent of intelligence, and how local processing relates to executive control. We present a brief and easy-to-administer test of coherence requiring global sentence completions. We report results from three studies assessing (a) 176 typically developing (TD) 8- to 25-year-olds, (b) individuals with ASD and matched controls, and (c) matched groups with ASD or attention deficit/hyperactivity disorder (ADHD). The results suggest that the Sentence Completion Task can reveal individual differences in cognitive style unrelated to IQ in typical development, that most (but not all) people with ASD show weak coherence on this task, and that performance is not related to inhibitory control. The Sentence Completion Task was found to be a useful test instrument, capable of tapping local processing bias in a range of populations. (c) 2010 Elsevier Inc. All rights reserved.

The limits of direct satellite tracking with the Global Positioning System (GPS)

NASA Technical Reports Server (NTRS)

Bertiger, W. I.; Yunck, T. P.

1988-01-01

Recent advances in high precision differential Global Positioning System-based satellite tracking can be applied to the more conventional direct tracking of low earth satellites. To properly evaluate the limiting accuracy of direct GPS-based tracking, it is necessary to account for the correlations between the a-priori errors in GPS states, Y-bias, and solar pressure parameters. These can be obtained by careful analysis of the GPS orbit determination process. The analysis indicates that sub-meter accuracy can be readily achieved for a user above 1000 km altitude, even when the user solution is obtained with data taken 12 hours after the data used in the GPS orbit solutions.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Technical Reports Server (NTRS)

Koster, Randal; Walker, G.; Thornton, Patti; Collatz, G. J.

2012-01-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Astrophysics Data System (ADS)

Koster, R. D.; Walker, G.; Thornton, P. E.; Collatz, G. J.

2012-12-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if somewhat biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

More attentional focusing through binaural beats: evidence from the global-local task.

PubMed

Colzato, Lorenza S; Barone, Hayley; Sellaro, Roberta; Hommel, Bernhard

2017-01-01

A recent study showed that binaural beats have an impact on the efficiency of allocating attention over time. We were interested to see whether this impact affects attentional focusing or, even further, the top-down control over irrelevant information. Healthy adults listened to gamma-frequency (40 Hz) binaural beats, which are assumed to increase attentional concentration, or a constant tone of 340 Hz (control condition) for 3 min before and during a global-local task. While the size of the congruency effect (indicating the failure to suppress task-irrelevant information) was unaffected by the binaural beats, the global-precedence effect (reflecting attentional focusing) was considerably smaller after gamma-frequency binaural beats than after the control condition. Our findings suggest that high-frequency binaural beats bias the individual attentional processing style towards a reduced spotlight of attention.

On the Frozen Soil Scheme for High Latitude Regions

NASA Astrophysics Data System (ADS)

Ganji, A.; Sushama, L.

2014-12-01

Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the frozen scheme in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. Interflow is also included in these experiments presented in this study to better explain the steamflows after snow melt season. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations, performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA-Interim), for the 1990-2001 period, over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept, compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS, over most of the study domain. The simulated spring peaks and their timing in this simulation is also in better agreement to those observed.

The relationship between level of autistic traits and local bias in the context of the McGurk effect

PubMed Central

Ujiie, Yuta; Asai, Tomohisa; Wakabayashi, Akio

2015-01-01

The McGurk effect is a well-known illustration that demonstrates the influence of visual information on hearing in the context of speech perception. Some studies have reported that individuals with autism spectrum disorder (ASD) display abnormal processing of audio-visual speech integration, while other studies showed contradictory results. Based on the dimensional model of ASD, we administered two analog studies to examine the link between level of autistic traits, as assessed by the Autism Spectrum Quotient (AQ), and the McGurk effect among a sample of university students. In the first experiment, we found that autistic traits correlated negatively with fused (McGurk) responses. Then, we manipulated presentation types of visual stimuli to examine whether the local bias toward visual speech cues modulated individual differences in the McGurk effect. The presentation included four types of visual images, comprising no image, mouth only, mouth and eyes, and full face. The results revealed that global facial information facilitates the influence of visual speech cues on McGurk stimuli. Moreover, individual differences between groups with low and high levels of autistic traits appeared when the full-face visual speech cue with an incongruent voice condition was presented. These results suggest that individual differences in the McGurk effect might be due to a weak ability to process global facial information in individuals with high levels of autistic traits. PMID:26175705

Improving evapotranspiration processes in distrubing hydrological models using Remote Sensing derived ET products.

NASA Astrophysics Data System (ADS)

Abitew, T. A.; van Griensven, A.; Bauwens, W.

2015-12-01

Evapotranspiration is the main process in hydrology (on average around 60%), though has not received as much attention in the evaluation and calibration of hydrological models. In this study, Remote Sensing (RS) derived Evapotranspiration (ET) is used to improve the spatially distributed processes of ET of SWAT model application in the upper Mara basin (Kenya) and the Blue Nile basin (Ethiopia). The RS derived ET data is obtained from recently compiled global datasets (continuously monthly data at 1 km resolution from MOD16NBI,SSEBop,ALEXI,CMRSET models) and from regionally applied Energy Balance Models (for several cloud free days). The RS-RT data is used in different forms: Method 1) to evaluate spatially distributed evapotransiration model resultsMethod 2) to calibrate the evotranspiration processes in hydrological modelMethod 3) to bias-correct the evapotranpiration in hydrological model during simulation after changing the SWAT codesAn inter-comparison of the RS-ET products shows that at present there is a significant bias, but at the same time an agreement on the spatial variability of ET. The ensemble mean of different ET products seems the most realistic estimation and was further used in this study.The results show that:Method 1) the spatially mapped evapotranspiration of hydrological models shows clear differences when compared to RS derived evapotranspiration (low correlations). Especially evapotranspiration in forested areas is strongly underestimated compared to other land covers.Method 2) Calibration allows to improve the correlations between the RS and hydrological model results to some extent.Method 3) Bias-corrections are efficient in producing (sesonal or annual) evapotranspiration maps from hydrological models which are very similar to the patterns obtained from RS data.Though the bias-correction is very efficient, it is advised to improve the model results by better representing the ET processes by improved plant/crop computations, improved agricultural management practices or by providing improved meteorological data.

Evaluating models of object-decision priming: evidence from event-related potential repetition effects.

PubMed

Soldan, Anja; Mangels, Jennifer A; Cooper, Lynn A

2006-03-01

This study was designed to differentiate between structural description and bias accounts of performance in the possible/impossible object-decision test. Two event-related potential (ERP) studies examined how the visual system processes structurally possible and impossible objects. Specifically, the authors investigated the effects of object repetition on a series of early posterior components during structural (Experiment 1) and functional (Experiment 2) encoding and the relationship of these effects to behavioral measures of priming. In both experiments, the authors found repetition enhancement of the posterior N1 and N2 for possible objects only. In addition, the magnitude of the N1 repetition effect for possible objects was correlated with priming for possible objects. Although the behavioral results were more ambiguous, these ERP results fail to support bias models that hold that both possible and impossible objects are processed similarly in the visual system. Instead, they support the view that priming is supported by a structural description system that encodes the global 3-dimensional structure of an object.

Probing the photoresponse of individual Nb2O5 nanowires with global and localized laser beam irradiation.

PubMed

Tamang, Rajesh; Varghese, Binni; Mhaisalkar, Subodh G; Tok, Eng Soon; Sow, Chorng Haur

2011-03-18

Photoresponse of isolated Nb(2)O(5) nanowires (NW) padded with platinum (Pt) at both ends were studied with global irradiation by a laser beam and localized irradiation using a focused laser beam. Global laser irradiation on individual NW in ambient and vacuum conditions revealed photocurrent contributions with different time characteristics (rapid and slowly varying components) arising from defect level excitations, thermal heating effect, surface states and NW-Pt contacts. With a spot size of < 1 µm, localized irradiation highlighted the fact that the measured photocurrent in this single NW device (with and without applied bias) depended sensitively on the photoresponse at the NW-Pt contacts. At applied bias, unidirectional photocurrent was observed and higher photocurrent was achieved with localized laser irradiation at reverse-biased NW-Pt contacts. At zero bias, the opposite polarity of photocurrents was detected when the two NW-Pt contacts were subjected to focused laser beam irradiation. A reduced Schottky barrier/width resulting from an increase in charge carriers and thermoelectric effects arising from the localized thermal heating due to focused laser beam irradiation were proposed as the mechanisms dictating the photocurrent at the NW-Pt interface. Comparison of photocurrents generated upon global and localized laser irradiation showed that the main contribution to the photocurrent was largely due to the photoresponse of the NW-Pt contacts.

Non-biased and efficient global amplification of a single-cell cDNA library

PubMed Central

Huang, Huan; Goto, Mari; Tsunoda, Hiroyuki; Sun, Lizhou; Taniguchi, Kiyomi; Matsunaga, Hiroko; Kambara, Hideki

2014-01-01

Analysis of single-cell gene expression promises a more precise understanding of molecular mechanisms of a living system. Most techniques only allow studies of the expressions for limited numbers of gene species. When amplification of cDNA was carried out for analysing more genes, amplification biases were frequently reported. A non-biased and efficient global-amplification method, which uses a single-cell cDNA library immobilized on beads, was developed for analysing entire gene expressions for single cells. Every step in this analysis from reverse transcription to cDNA amplification was optimized. By removing degrading excess primers, the bias due to the digestion of cDNA was prevented. Since the residual reagents, which affect the efficiency of each subsequent reaction, could be removed by washing beads, the conditions for uniform and maximized amplification of cDNAs were achieved. The differences in the amplification rates for randomly selected eight genes were within 1.5-folds, which could be negligible for most of the applications of single-cell analysis. The global amplification gives a large amount of amplified cDNA (>100 μg) from a single cell (2-pg mRNA), and that amount is enough for downstream analysis. The proposed global-amplification method was used to analyse transcript ratios of multiple cDNA targets (from several copies to several thousand copies) quantitatively. PMID:24141095

Satellite-enhanced dynamical downscaling for the analysis of extreme events

NASA Astrophysics Data System (ADS)

Nunes, Ana M. B.

2016-09-01

The use of regional models in the downscaling of general circulation models provides a strategy to generate more detailed climate information. In that case, boundary-forcing techniques can be useful to maintain the large-scale features from the coarse-resolution global models in agreement with the inner modes of the higher-resolution regional models. Although those procedures might improve dynamics, downscaling via regional modeling still aims for better representation of physical processes. With the purpose of improving dynamics and physical processes in regional downscaling of global reanalysis, the Regional Spectral Model—originally developed at the National Centers for Environmental Prediction—employs a newly reformulated scale-selective bias correction, together with the 3-hourly assimilation of the satellite-based precipitation estimates constructed from the Climate Prediction Center morphing technique. The two-scheme technique for the dynamical downscaling of global reanalysis can be applied in analyses of environmental disasters and risk assessment, with hourly outputs, and resolution of about 25 km. Here the satellite-enhanced dynamical downscaling added value is demonstrated in simulations of the first reported hurricane in the western South Atlantic Ocean basin through comparisons with global reanalyses and satellite products available in ocean areas.

Reduced Distractibility in a Remote Culture

PubMed Central

de Fockert, Jan W.; Caparos, Serge; Linnell, Karina J.; Davidoff, Jules

2011-01-01

Background In visual processing, there are marked cultural differences in the tendency to adopt either a global or local processing style. A remote culture (the Himba) has recently been reported to have a greater local bias in visual processing than Westerners. Here we give the first evidence that a greater, and remarkable, attentional selectivity provides the basis for this local bias. Methodology/Principal Findings In Experiment 1, Eriksen-type flanker interference was measured in the Himba and in Western controls. In both groups, responses to the direction of a task-relevant target arrow were affected by the compatibility of task-irrelevant distractor arrows. However, the Himba showed a marked reduction in overall flanker interference compared to Westerners. The smaller interference effect in the Himba occurred despite their overall slower performance than Westerners, and was evident even at a low level of perceptual load of the displays. In Experiment 2, the attentional selectivity of the Himba was further demonstrated by showing that their attention was not even captured by a moving singleton distractor. Conclusions/Significance We argue that the reduced distractibility in the Himba is clearly consistent with their tendency to prioritize the analysis of local details in visual processing. PMID:22046275

Decadal climate simulations using the Climate Forecast System (CFS) coupled to the SSiB2 land surface model

NASA Astrophysics Data System (ADS)

De Sales, F.; Xue, Y.; Marx, L.; Ek, M. B.

2016-12-01

The Simplified Simple Biophysical version 2 (SSiB2) model was implemented in the NCEP Climate Forecast System (CFS) for two 30-yr simulations. One simulation was initialized from CFS reanalysis data (EXP1), and the other from a 10-yr spin-up run (EXP2), in which the ocean model was allowed to run freely while the atmosphere and land surface were maintained constant to adjust inconsistencies in the initial conditions. EXP2 also includes an update in the SSiB2's average soil water potential calculation. The material presented highlights the model's performance in predicting spatial and temporal variability of monthly precipitation and surface temperature and aims at determining the optimum configuration for longer simulations. In general, the model is able to reproduce the main features of large-scale precipitation, with spatial correlation (scorr) and RMSE of 0.8 and 1.4 mm day-1, respectively. A split ITCZ pattern is observed in the Pacific and Indian oceans, which results in dry biases along the equator and wet-bias bands to its north and south. Positive biases are also observed in the Atlantic ITCZ. The model generates consistent surface temperature climatology (scorr > 0.9, RMSE= 2.3°C). Warm biases are observed especially over southern Asia during summer. Both experiments produce similar precipitation climatology patterns with similar biases. EXP2, however, improves the temperature simulation by reducing the global bias by 48% and 26% during boreal winter and summer, respectively; and improves the temperature decadal variability for many areas. Moreover, EXP2 generates a better continental surface air warming trend. In the attempt to improve the precipitation decadal variability in the simulations, remotely-sensed LAI and vegetation cover fraction have been implemented in the CFS/SSiB2 to substitute the look-up table originally used in EXP1 and 2. The satellite vegetation data has been processed into global monthly maps which are continuous updated throughout the simulation. Results from this experiment will also be presented.

Counting abilities in autism: possible implications for central coherence theory.

PubMed

Jarrold, C; Russell, J

1997-02-01

We examined the claim that children with autism have a "weak drive for central coherence" which biases them towards processing information at an analytic rather than global level. This was done by investigating whether children with autism would rapidly and automatically enumerate a number of dots presented in a canonical form, or count each dot individually to obtain the total. The time taken to count stimuli was compared across three participant groups: children with autism, children with moderate learning difficulties, and normally developing children. There were 22 children in each group, and individuals were matched across groups on the basis of verbal mental age. Results implied that children with autism did show a tendency towards an analytic level of processing. However, though the groups differed on measures of counting speeds, the number or children showing patterns of global or analytic processing did not differ significantly across the groups. Whether these results implicate a weak drive for central coherence in autism, which is both specific to, and pervasive in the disorder, is discussed.

Trends in the predictive performance of raw ensemble weather forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Scheuerer, Michael; Pappenberger, Florian; Bogner, Konrad; Haiden, Thomas

2015-04-01

Over the last two decades the paradigm in weather forecasting has shifted from being deterministic to probabilistic. Accordingly, numerical weather prediction (NWP) models have been run increasingly as ensemble forecasting systems. The goal of such ensemble forecasts is to approximate the forecast probability distribution by a finite sample of scenarios. Global ensemble forecast systems, like the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble, are prone to probabilistic biases, and are therefore not reliable. They particularly tend to be underdispersive for surface weather parameters. Hence, statistical post-processing is required in order to obtain reliable and sharp forecasts. In this study we apply statistical post-processing to ensemble forecasts of near-surface temperature, 24-hour precipitation totals, and near-surface wind speed from the global ECMWF model. Our main objective is to evaluate the evolution of the difference in skill between the raw ensemble and the post-processed forecasts. The ECMWF ensemble is under continuous development, and hence its forecast skill improves over time. Parts of these improvements may be due to a reduction of probabilistic bias. Thus, we first hypothesize that the gain by post-processing decreases over time. Based on ECMWF forecasts from January 2002 to March 2014 and corresponding observations from globally distributed stations we generate post-processed forecasts by ensemble model output statistics (EMOS) for each station and variable. Parameter estimates are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over rolling training periods that consist of the n days preceding the initialization dates. Given the higher average skill in terms of CRPS of the post-processed forecasts for all three variables, we analyze the evolution of the difference in skill between raw ensemble and EMOS forecasts. The fact that the gap in skill remains almost constant over time, especially for near-surface wind speed, suggests that improvements to the atmospheric model have an effect quite different from what calibration by statistical post-processing is doing. That is, they are increasing potential skill. Thus this study indicates that (a) further model development is important even if one is just interested in point forecasts, and (b) statistical post-processing is important because it will keep adding skill in the foreseeable future.

Understanding intersatellite biases of microwave humidity sounders using global simultaneous nadir overpasses

NASA Astrophysics Data System (ADS)

John, Viju O.; Holl, Gerrit; Buehler, Stefan A.; Candy, Brett; Saunders, Roger W.; Parker, David E.

2012-01-01

Simultaneous nadir overpasses (SNOs) of polar-orbiting satellites are most frequent in polar areas but can occur at any latitude when the equatorial crossing times of the satellites become close owing to orbital drift. We use global SNOs of polar orbiting satellites to evaluate the intercalibration of microwave humidity sounders from the more frequent high-latitude SNOs. We have found based on sensitivity analyses that optimal distance and time thresholds for defining collocations are pixel centers less than 5 km apart and time differences less than 300 s. These stringent collocation criteria reduce the impact of highly variable surface or atmospheric conditions on the estimated biases. Uncertainties in the estimated biases are dominated by the combined radiometric noise of the instrument pair. The effects of frequency changes between different versions of the humidity sounders depend on the amount of water vapor in the atmosphere. There are significant scene radiance and thus latitude dependencies in the estimated biases and this has to taken into account while intercalibrating microwave humidity sounders. Therefore the results obtained using polar SNOs will not be representative for moist regions, necessitating the use of global collocations for reliable intercalibration.

Hamiltonian replica exchange combined with elastic network analysis to enhance global domain motions in atomistic molecular dynamics simulations.

PubMed

Ostermeir, Katja; Zacharias, Martin

2014-12-01

Coarse-grained elastic network models (ENM) of proteins offer a low-resolution representation of protein dynamics and directions of global mobility. A Hamiltonian-replica exchange molecular dynamics (H-REMD) approach has been developed that combines information extracted from an ENM analysis with atomistic explicit solvent MD simulations. Based on a set of centers representing rigid segments (centroids) of a protein, a distance-dependent biasing potential is constructed by means of an ENM analysis to promote and guide centroid/domain rearrangements. The biasing potentials are added with different magnitude to the force field description of the MD simulation along the replicas with one reference replica under the control of the original force field. The magnitude and the form of the biasing potentials are adapted during the simulation based on the average sampled conformation to reach a near constant biasing in each replica after equilibration. This allows for canonical sampling of conformational states in each replica. The application of the methodology to a two-domain segment of the glycoprotein 130 and to the protein cyanovirin-N indicates significantly enhanced global domain motions and improved conformational sampling compared with conventional MD simulations. © 2014 Wiley Periodicals, Inc.

Nitrogen and Phosphorus Plant Uptake During Periods with no Photosynthesis Accounts for About Half of Global Annual Uptake

NASA Astrophysics Data System (ADS)

Riley, W. J.; Zhu, Q.; Tang, J.

2017-12-01

Uncertainties in current Earth System Model (ESM) predictions of terrestrial carbon-climate feedbacks over the 21st century are as large as, or larger than, any other reported natural system uncertainties. Soil Organic Matter (SOM) decomposition and photosynthesis, the dominant fluxes in this regard, are tightly linked through nutrient availability, and the recent Coupled Model Inter-comparison Project 5 (CMIP5) used for climate change assessment had no credible representations of these constraints. In response, many ESM land models (ESMLMs) have developed dynamic and coupled soil and plant nutrient cycles. Here we quantify terrestrial carbon cycle impacts from well-known observed plant nutrient uptake mechanisms ignored in most current ESMLMs. In particular, we estimate the global role of plant root nutrient competition with microbes and abiotic process at night and during the non-growing season using the ACME land model (ALMv1-ECA-CNP) that explicitly represents these dynamics. We first demonstrate that short-term nutrient uptake dynamics and competition between plants and microbes are accurately predicted by the model compared to 15N and 33P isotopic tracer measurements from more than 20 sites. We then show that global nighttime and non-growing season nitrogen and phosphorus uptake accounts for 46 and 45%, respectively, of annual uptake, with large latitudinal variation. Model experiments show that ignoring these plant uptake periods leads to large positive biases in annual N leaching (globally 58%) and N2O emissions (globally 68%). Biases these large will affect modeled carbon cycle dynamics over time, and lead to predictions of ecosystems that have overly open nutrient cycles and therefore lower capacity to sequester carbon.

Reduction of ZTD outliers through improved GNSS data processing and screening strategies

NASA Astrophysics Data System (ADS)

Stepniak, Katarzyna; Bock, Olivier; Wielgosz, Pawel

2018-03-01

Though Global Navigation Satellite System (GNSS) data processing has been significantly improved over the years, it is still commonly observed that zenith tropospheric delay (ZTD) estimates contain many outliers which are detrimental to meteorological and climatological applications. In this paper, we show that ZTD outliers in double-difference processing are mostly caused by sub-daily data gaps at reference stations, which cause disconnections of clusters of stations from the reference network and common mode biases due to the strong correlation between stations in short baselines. They can reach a few centimetres in ZTD and usually coincide with a jump in formal errors. The magnitude and sign of these biases are impossible to predict because they depend on different errors in the observations and on the geometry of the baselines. We elaborate and test a new baseline strategy which solves this problem and significantly reduces the number of outliers compared to the standard strategy commonly used for positioning (e.g. determination of national reference frame) in which the pre-defined network is composed of a skeleton of reference stations to which secondary stations are connected in a star-like structure. The new strategy is also shown to perform better than the widely used strategy maximizing the number of observations available in many GNSS programs. The reason is that observations are maximized before processing, whereas the final number of used observations can be dramatically lower because of data rejection (screening) during the processing. The study relies on the analysis of 1 year of GPS (Global Positioning System) data from a regional network of 136 GNSS stations processed using Bernese GNSS Software v.5.2. A post-processing screening procedure is also proposed to detect and remove a few outliers which may still remain due to short data gaps. It is based on a combination of range checks and outlier checks of ZTD and formal errors. The accuracy of the final screened GPS ZTD estimates is assessed by comparison to ERA-Interim reanalysis.

Synaptic Correlates of Low-Level Perception in V1.

PubMed

Gerard-Mercier, Florian; Carelli, Pedro V; Pananceau, Marc; Troncoso, Xoana G; Frégnac, Yves

2016-04-06

The computational role of primary visual cortex (V1) in low-level perception remains largely debated. A dominant view assumes the prevalence of higher cortical areas and top-down processes in binding information across the visual field. Here, we investigated the role of long-distance intracortical connections in form and motion processing by measuring, with intracellular recordings, their synaptic impact on neurons in area 17 (V1) of the anesthetized cat. By systematically mapping synaptic responses to stimuli presented in the nonspiking surround of V1 receptive fields, we provide the first quantitative characterization of the lateral functional connectivity kernel of V1 neurons. Our results revealed at the population level two structural-functional biases in the synaptic integration and dynamic association properties of V1 neurons. First, subthreshold responses to oriented stimuli flashed in isolation in the nonspiking surround exhibited a geometric organization around the preferred orientation axis mirroring the psychophysical "association field" for collinear contour perception. Second, apparent motion stimuli, for which horizontal and feedforward synaptic inputs summed in-phase, evoked dominantly facilitatory nonlinear interactions, specifically during centripetal collinear activation along the preferred orientation axis, at saccadic-like speeds. This spatiotemporal integration property, which could constitute the neural correlate of a human perceptual bias in speed detection, suggests that local (orientation) and global (motion) information is already linked within V1. We propose the existence of a "dynamic association field" in V1 neurons, whose spatial extent and anisotropy are transiently updated and reshaped as a function of changes in the retinal flow statistics imposed during natural oculomotor exploration. The computational role of primary visual cortex in low-level perception remains debated. The expression of this "pop-out" perception is often assumed to require attention-related processes, such as top-down feedback from higher cortical areas. Using intracellular techniques in the anesthetized cat and novel analysis methods, we reveal unexpected structural-functional biases in the synaptic integration and dynamic association properties of V1 neurons. These structural-functional biases provide a substrate, within V1, for contour detection and, more unexpectedly, global motion flow sensitivity at saccadic speed, even in the absence of attentional processes. We argue for the concept of a "dynamic association field" in V1 neurons, whose spatial extent and anisotropy changes with retinal flow statistics, and more generally for a renewed focus on intracortical computation. Copyright © 2016 the authors 0270-6474/16/363925-18$15.00/0.

Comparison of Water Vapor Measurements from Ground-based and Space-based GPS Atmospheric Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

Colon-Pagan, Ian; Kuo, Ying-Hwa

2008-10-01

In this study, we compare precipitable water vapor (PWV) values from ground-based GPS water vapor sensing and COSMIC radio occultation (RO) measurements over the Caribbean Sea, Gulf of Mexico, and United States regions as well as global analyses from NCEP and ECMWF models. The results show good overall agreement; however, the PWV values estimated by ground-based GPS receivers tend to have a slight dry bias for low PWV values and a slight wet bias for higher PWV values, when compared with GPS RO measurements and global analyses. An application of a student T-test indicates that there is a significant difference between both ground- and space-based GPS measured datasets. The dry bias associated with space-based GPS is attributed to the missing low altitude data, where the concentration of water vapor is large. The close agreements between space-based and global analyses are due to the fact that these global analyses assimilate space-based GPS RO data from COSMIC, and the retrieval of water vapor profiles from space-based technique requires the use of global analyses as the first guess. This work is supported by UCAR SOARS and a grant from the National Oceanic and Atmospheric Administration, Educational Partnership Program under the cooperative agreement NA06OAR4810187.

Climate intercomparison of GPS radio occultation, RS90/92 radiosondes and GRUAN from 2002 to 2013

NASA Astrophysics Data System (ADS)

Ladstädter, F.; Steiner, A. K.; Schwärz, M.; Kirchengast, G.

2015-04-01

Observations from the GPS radio occultation (GPSRO) satellite technique and from the newly established GCOS Reference Upper Air Network (GRUAN) are both candidates to serve as reference observations in the Global Climate Observing System (GCOS). Such reference observations are key to decrease existing uncertainties in upper-air climate research. There are now more than 12 years of data available from GPSRO, with the recognized properties high accuracy, global coverage, high vertical resolution, and long-term stability. These properties make GPSRO a suitable choice for comparison studies with other upper-air observational systems. The GRUAN network consists of reference radiosonde ground stations (16 at present), which adhere to the GCOS climate monitoring principles. In this study, we intercompare GPSRO temperature and humidity profiles and Vaisala RS90/92 data from the "standard" global radiosonde network over the whole 2002 to 2013 time frame. Additionally, we include the first years of GRUAN data (using Vaisala RS92), available since 2009. GPSRO profiles which occur within 3 h and 300 km of radiosonde launches are used. Overall very good agreement is found between all three data sets with temperature differences usually less than 0.2 K. In the stratosphere above 30 hPa, temperature differences are larger but still within 0.5 K. Day/night comparisons with GRUAN data reveal small deviations likely related to a warm bias of the radiosonde data at high altitudes, but also residual errors from the GPSRO retrieval process might play a role. Vaisala RS90/92 specific humidity exhibits a dry bias of up to 40% in the upper troposphere, with a smaller bias at lower altitudes within 15%. GRUAN shows a marked improvement in the bias characteristics, with less than 5% difference to GPSRO, up to 300 hPa. GPSRO dry temperature and physical temperature are validated using radiosonde data as reference. We find that GPSRO provides valuable long-term stable reference observations with well-defined error characteristics for climate applications and for anchoring other upper-air measurements.

Climate intercomparison of GPS radio occultation, RS90/92 radiosondes and GRUAN over 2002 to 2013

NASA Astrophysics Data System (ADS)

Ladstädter, F.; Steiner, A. K.; Schwärz, M.; Kirchengast, G.

2014-11-01

Observations from the GPS radio occultation (GPSRO) satellite technique and from the newly established GCOS Reference Upper Air Network (GRUAN) are both candidates to serve as reference observations in the Global Climate Observing System (GCOS). Such reference observations are key to decrease existing uncertainties in upper-air climate research. There are now more than 12 years of data available from GPSRO, with the recognized properties high accuracy, global coverage, high vertical resolution, and long-term stability. These properties make GPSRO a suitable choice for comparison studies with other upper-air observational systems. The GRUAN network consists of reference radiosonde ground stations (16 at present), which adhere to the GCOS climate monitoring principles. In this study, we intercompare GPSRO temperature and humidity profiles and Vaisala RS90/92 data from the "standard" global radiosonde network over the whole 2002 to 2013 time frame. Additionally, we include the first years of GRUAN data (using Vaisala RS92), available since 2009. GPSRO profiles which occur within 3 h and 300 km of radiosonde launches are used. Very good agreement is found between all three datasets with temperature differences usually less than 0.2 K. In the stratosphere above 30 hPa, temperature differences are larger but still within 0.5 K. Day/night comparisons with GRUAN data reveal small deviations likely related to a warm bias of the radiosonde data at high altitudes, but also residual errors from the GPSRO retrieval process might play a role. Vaisala RS90/92 specific humidity exhibits a dry bias of up to 40% in the upper troposphere, with a smaller bias at lower altitudes within 15%. GRUAN shows a marked improvement in the bias characteristics, with less than 5% difference to GPSRO up to 300 hPa. GPSRO dry temperature and physical temperature are validated using radiosonde data as reference. We find that GPSRO provides valuable long-term stable reference observations with well-defined error characteristics for climate applications and for anchoring other upper-air measurements.

Carbon Monitoring System Flux Estimation and Attribution: Impact of ACOS-GOSAT X(CO2) Sampling on the Inference of Terrestrial Biospheric Sources and Sinks

NASA Technical Reports Server (NTRS)

Liu, Junjie; Bowman, Kevin W.; Lee, Memong; Henze, David K.; Bousserez, Nicolas; Brix, Holger; Collatz, G. James; Menemenlis, Dimitris; Ott, Lesley; Pawson, Steven;

Hybrid Monte Carlo/deterministic methods for radiation shielding problems

NASA Astrophysics Data System (ADS)

Becker, Troy L.

For the past few decades, the most common type of deep-penetration (shielding) problem simulated using Monte Carlo methods has been the source-detector problem, in which a response is calculated at a single location in space. Traditionally, the nonanalog Monte Carlo methods used to solve these problems have required significant user input to generate and sufficiently optimize the biasing parameters necessary to obtain a statistically reliable solution. It has been demonstrated that this laborious task can be replaced by automated processes that rely on a deterministic adjoint solution to set the biasing parameters---the so-called hybrid methods. The increase in computational power over recent years has also led to interest in obtaining the solution in a region of space much larger than a point detector. In this thesis, we propose two methods for solving problems ranging from source-detector problems to more global calculations---weight windows and the Transform approach. These techniques employ sonic of the same biasing elements that have been used previously; however, the fundamental difference is that here the biasing techniques are used as elements of a comprehensive tool set to distribute Monte Carlo particles in a user-specified way. The weight window achieves the user-specified Monte Carlo particle distribution by imposing a particular weight window on the system, without altering the particle physics. The Transform approach introduces a transform into the neutron transport equation, which results in a complete modification of the particle physics to produce the user-specified Monte Carlo distribution. These methods are tested in a three-dimensional multigroup Monte Carlo code. For a basic shielding problem and a more realistic one, these methods adequately solved source-detector problems and more global calculations. Furthermore, they confirmed that theoretical Monte Carlo particle distributions correspond to the simulated ones, implying that these methods can be used to achieve user-specified Monte Carlo distributions. Overall, the Transform approach performed more efficiently than the weight window methods, but it performed much more efficiently for source-detector problems than for global problems.

Influence of finite geometrical asymmetry of the electrodes in capacitively coupled radio frequency plasma

NASA Astrophysics Data System (ADS)

Bora, B.; Soto, L.

2014-08-01

Capacitively coupled radio frequency (CCRF) plasmas are widely studied in last decades due to the versatile applicability of energetic ions, chemically active species, radicals, and also energetic neutral species in many material processing fields including microelectronics, aerospace, and biology. A dc self-bias is known to generate naturally in geometrically asymmetric CCRF plasma because of the difference in electrode sizes known as geometrical asymmetry of the electrodes in order to compensate electron and ion flux to each electrode within one rf period. The plasma series resonance effect is also come into play due to the geometrical asymmetry and excited several harmonics of the fundamental in low pressure CCRF plasma. In this work, a 13.56 MHz CCRF plasma is studied on the based on the nonlinear global model of asymmetric CCRF discharge to understand the influences of finite geometrical asymmetry of the electrodes in terms of generation of dc self-bias and plasma heating. The nonlinear global model on asymmetric discharge has been modified by considering the sheath at the grounded electrode to taking account the finite geometrical asymmetry of the electrodes. The ion density inside both the sheaths has been taken into account by incorporating the steady-state fluid equations for ions considering that the applied rf frequency is higher than the typical ion plasma frequency. Details results on the influences of geometrical asymmetry on the generation of dc self-bias and plasma heating are discussed.

Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

NASA Astrophysics Data System (ADS)

Jha, Sanjeev K.; Shrestha, Durga L.; Stadnyk, Tricia A.; Coulibaly, Paulin

2018-03-01

Flooding in Canada is often caused by heavy rainfall during the snowmelt period. Hydrologic forecast centers rely on precipitation forecasts obtained from numerical weather prediction (NWP) models to enforce hydrological models for streamflow forecasting. The uncertainties in raw quantitative precipitation forecasts (QPFs) are enhanced by physiography and orography effects over a diverse landscape, particularly in the western catchments of Canada. A Bayesian post-processing approach called rainfall post-processing (RPP), developed in Australia (Robertson et al., 2013; Shrestha et al., 2015), has been applied to assess its forecast performance in a Canadian catchment. Raw QPFs obtained from two sources, Global Ensemble Forecasting System (GEFS) Reforecast 2 project, from the National Centers for Environmental Prediction, and Global Deterministic Forecast System (GDPS), from Environment and Climate Change Canada, are used in this study. The study period from January 2013 to December 2015 covered a major flood event in Calgary, Alberta, Canada. Post-processed results show that the RPP is able to remove the bias and reduce the errors of both GEFS and GDPS forecasts. Ensembles generated from the RPP reliably quantify the forecast uncertainty.

Simulated cold bias being improved by using MODIS time-varying albedo in the Tibetan Plateau in WRF model

NASA Astrophysics Data System (ADS)

Meng, X.; Lyu, S.; Zhang, T.; Zhao, L.; Li, Z.; Han, B.; Li, S.; Ma, D.; Chen, H.; Ao, Y.; Luo, S.; Shen, Y.; Guo, J.; Wen, L.

2018-04-01

Systematic cold biases exist in the simulation for 2 m air temperature in the Tibetan Plateau (TP) when using regional climate models and global atmospheric general circulation models. We updated the albedo in the Weather Research and Forecasting (WRF) Model lower boundary condition using the Global LAnd Surface Satellite Moderate-Resolution Imaging Spectroradiometer albedo products and demonstrated evident improvement for cold temperature biases in the TP. It is the large overestimation of albedo in winter and spring in the WRF model that resulted in the large cold temperature biases. The overestimated albedo was caused by the simulated precipitation biases and over-parameterization of snow albedo. Furthermore, light-absorbing aerosols can result in a large reduction of albedo in snow and ice cover. The results suggest the necessity of developing snow albedo parameterization using observations in the TP, where snow cover and melting are very different from other low-elevation regions, and the influence of aerosols should be considered as well. In addition to defining snow albedo, our results show an urgent call for improving precipitation simulation in the TP.

Tropospheric carbon monoxide over the Pacific during HIPPO: two-way coupled simulation of GEOS-Chem and its multiple nested models

NASA Astrophysics Data System (ADS)

Yan, Y.-Y.; Lin, J.-T.; Kuang, Y.; Yang, D.; Zhang, L.

2014-07-01

Global chemical transport models (CTMs) are used extensively to study air pollution and transport at a global scale. These models are limited by coarse horizontal resolutions, not allowing for detailed representation of small-scale nonlinear processes over the pollutant source regions. Here we couple the global GEOS-Chem CTM and its three high-resolution nested models to simulate the tropospheric carbon monoxide (CO) over the Pacific Ocean during five HIAPER Pole-to-Pole Observations (HIPPO) campaigns between 2009 and 2011. We develop a two-way coupler, PKUCPL, to integrate simulation results for chemical constituents from the global model (at 2.5° long. × 2° lat.) and the three nested models (at 0.667° long. × 0.5° lat.) covering Asia, North America and Europe, respectively. The coupler obtains nested model results to modify the global model simulation within the respective nested domains, and simultaneously acquires global model results to provide lateral boundary conditions for the nested models. Compared to the global model alone, the two-way coupled simulation results in enhanced CO concentrations in the nested domains. Sensitivity tests suggest the enhancement to be a result of improved representation of the spatial distributions of CO, nitrogen oxides and non-methane volatile organic compounds, the meteorological dependence of natural emissions, and other resolution-dependent processes. The relatively long lifetime of CO allows for the enhancement to be accumulated and carried across the globe. We find that the two-way coupled simulation increases the global tropospheric mean CO concentrations in 2009 by 10.4%, with a greater enhancement at 13.3% in the Northern Hemisphere. Coincidently, the global tropospheric mean hydroxyl radical (OH) is reduced by 4.2% (as compared to the interannual variability of OH at 2.3%), resulting in a 4.2% enhancement in the methyl chloroform lifetime (MCF, via reaction with tropospheric OH). The resulting CO and OH contents and MCF lifetime are closer to observation-based estimates. Both the global and the two-way coupled models capture the general spatiotemporal patterns of HIPPO CO over the Pacific. The two-way coupled simulation is much closer to HIPPO CO, with a mean bias of 1.1 ppb (1.4%) below 9 km compared to the bias at -7.2 ppb (-9.2%) for the global model. The improvement is most apparent over the North Pacific. Our test simulations show that the global model could resemble the two-way coupled simulation (especially below 4 km) by increasing its global CO emissions by 15% for HIPPO-1 and HIPPO-3, by 25% for HIPPO-2 and HIPPO-4, and by 35% for HIPPO-5. This has important implications for using the global model to constrain CO emissions. Thus, the two-way coupled simulation is a significantly improved model tool to studying the global impacts of air pollutants from major anthropogenic source regions.

BIS impulsivity and acute nicotine exposure are associated with discounting global consequences in the Harvard game.

PubMed

Hogarth, Lee; Stillwell, David J; Tunney, Richard J

2013-01-01

The Barratt Impulsivity Scale (BIS) provides a transdiagnostic marker for a number of psychiatric conditions and drug abuse, but the precise psychological trait(s) tapped by this questionnaire remain obscure. To address this, 51 smokers completed in counterbalanced order the BIS, a delay discounting task and a Harvard game that measured choice between a response that yielded a high immediate monetary payoff but decreased opportunity to earn money overall (local choice) versus a response that yielded a lower immediate payoff but afforded a greater opportunity to earn overall (global choice). Individual level of BIS impulsivity and self-elected smoking prior to the study were independently associated with increased preference for the local over the global choice in the Harvard game, but not delay discounting. BIS impulsivity and acute nicotine exposure reflect a bias in the governance of choice by immediate reward contingencies over global consequences, consistent with contemporary dual-process instrumental learning theories. Copyright © 2013 John Wiley & Sons, Ltd.

Calibration and assessment of channel-specific biases in microarray data with extended dynamical range.

PubMed

Bengtsson, Henrik; Jönsson, Göran; Vallon-Christersson, Johan

2004-11-12

Non-linearities in observed log-ratios of gene expressions, also known as intensity dependent log-ratios, can often be accounted for by global biases in the two channels being compared. Any step in a microarray process may introduce such offsets and in this article we study the biases introduced by the microarray scanner and the image analysis software. By scanning the same spotted oligonucleotide microarray at different photomultiplier tube (PMT) gains, we have identified a channel-specific bias present in two-channel microarray data. For the scanners analyzed it was in the range of 15-25 (out of 65,535). The observed bias was very stable between subsequent scans of the same array although the PMT gain was greatly adjusted. This indicates that the bias does not originate from a step preceding the scanner detector parts. The bias varies slightly between arrays. When comparing estimates based on data from the same array, but from different scanners, we have found that different scanners introduce different amounts of bias. So do various image analysis methods. We propose a scanning protocol and a constrained affine model that allows us to identify and estimate the bias in each channel. Backward transformation removes the bias and brings the channels to the same scale. The result is that systematic effects such as intensity dependent log-ratios are removed, but also that signal densities become much more similar. The average scan, which has a larger dynamical range and greater signal-to-noise ratio than individual scans, can then be obtained. The study shows that microarray scanners may introduce a significant bias in each channel. Such biases have to be calibrated for, otherwise systematic effects such as intensity dependent log-ratios will be observed. The proposed scanning protocol and calibration method is simple to use and is useful for evaluating scanner biases or for obtaining calibrated measurements with extended dynamical range and better precision. The cross-platform R package aroma, which implements all described methods, is available for free from http://www.maths.lth.se/bioinformatics/.

Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxies

NASA Astrophysics Data System (ADS)

Lawlor, David; Budavári, Tamás; Mahoney, Michael W.

2016-12-01

We present a novel approach to studying the diversity of galaxies. It is based on a novel spectral graph technique, that of locally-biased semi-supervised eigenvectors. Our method introduces new coordinates that summarize an entire spectrum, similar to but going well beyond the widely used Principal Component Analysis (PCA). Unlike PCA, however, this technique does not assume that the Euclidean distance between galaxy spectra is a good global measure of similarity. Instead, we relax that condition to only the most similar spectra, and we show that doing so yields more reliable results for many astronomical questions of interest. The global variant of our approach can identify very finely numerous astronomical phenomena of interest. The locally-biased variants of our basic approach enable us to explore subtle trends around a set of chosen objects. The power of the method is demonstrated in the Sloan Digital Sky Survey Main Galaxy Sample, by illustrating that the derived spectral coordinates carry an unprecedented amount of information.

Remembering everyday experience through the prism of self-esteem.

PubMed

Christensen, Tamlin Conner; Wood, Joanne V; Barrett, Lisa Feldman

2003-01-01

Two studies examined whether global self-esteem was associated with bias in memory for autobiographical experience. For 7 days, participants described specific events and made ratings of their experience (i.e., state self-esteem, positive and negative emotion, and perceived valence of the event) in response to each event. Later, participants were presented with their event descriptions and were asked to recall their experience ratings from memory. As hypothesized, higher global self-esteem predicted positive shifts in memory for experience, whereas lower global self-esteem predicted negative shifts in memory for experience. Patterns of bias were strongest for remembered state self-esteem, moderate for positive emotion, and minimal for event valence. Self-esteem did not predict bias for negative emotion. Mood at the time of recall (measured in Study 2) generally did not account for the patterns. These findings strengthen the view that self-esteem is a rich source of knowledge about the self that can influence memory for some kinds of autobiographical experience. Copyright 2003 Society for Personality and Social Psychology, Inc.

Examination of global correlations in ground deformation for terrestrial reference frame estimation

NASA Astrophysics Data System (ADS)

Chin, T. M.; Abbondanza, C.; Argus, D. F.; Gross, R. S.; Heflin, M. B.; Parker, J. W.; Wu, X.

2016-12-01

The KALman filter for REFerence frames (KALREF, Wu et al. 2015) has been developed to produce terrestrial reference frame (TRF) solutions. TRFs consist of precise position coordinates and velocity vectors of terrestrial reference sites (with the geocenter as the origin) along with the Earth orientation parameters, and they are produced by combining decades worth of space geodetic data using site tie data. To perform the combination, KALREF relies on stochastic models of the geophysical processes that are causing the Earth's surface to deform and reference sites to be displaced. We are investigating application of the GRACE data to improve the KALREF stochastic models by determining spatial statistics of the deformation of the Earth's surface caused by mass loading. A potential target of improvement is the non-uniform distribution of the geodetic observation sites, which can introduce bias in TRF estimates of the geocenter. The global and relatively uniform coverage of the GRACE measurements is expected to be free of such bias and allow us to improve physical realism of the stochastic model. For such a goal, we examine the spatial correlations in ground deformation derived from several GRACE data sets.[Wu et al. 2015: Journal of Geophysical Research (Solid Earth) 120:3775-3802

CAUSES: Clouds Above the United States and Errors at the Surface

NASA Astrophysics Data System (ADS)

Ma, H. Y.; Klein, S. A.; Xie, S.; Morcrette, C. J.; Van Weverberg, K.; Zhang, Y.; Lo, M. H.

2015-12-01

The Clouds Above the United States and Errors at the Surface (CAUSES) is a new joint Global Atmospheric System Studies/Regional and Global Climate model/Atmospheric System Research (GASS/RGCM/ASR) intercomparison project to evaluate the central U.S. summertime surface warm biases seen in many weather and climate models. The main focus is to identify the role of cloud, radiation, and precipitation processes in contributing to surface air temperature biases. In this project, we use short-term hindcast approach and examine the growth of the error as a function of hindcast lead time. The study period covers from April 1 to August 31, 2011, which also covers the entire Midlatitude Continental Convective Clouds Experiment (MC3E) campaign. Preliminary results from several models will be presented. (http://portal.nersc.gov/project/capt/CAUSES/) (This study is funded by the RGCM and ASR programs of the U.S. Department of Energy as part of the Cloud-Associated Parameterizations Testbed. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-658017)

CAUSES: Clouds Above the United States and Errors at the Surface

NASA Astrophysics Data System (ADS)

Ma, H. Y.; Klein, S. A.; Xie, S.; Zhang, Y.; Morcrette, C. J.; Van Weverberg, K.; Petch, J.; Lo, M. H.

2014-12-01

The Clouds Above the United States and Errors at the Surface (CAUSES) is a new joint Global Atmospheric System Studies/Regional and Global Climate model/Atmospheric System Research (GASS/RGCM/ASR) intercomparison project to evaluate the central U.S. summertime surface warm biases seen in many weather and climate models. The main focus is to identify the role of cloud, radiation, and precipitation processes in contributing to surface air temperature biases. In this project, we use short-term hindcast approach and examine the growth of the error as a function of hindcast lead time. The study period covers from April 1 to August 31, 2011, which also covers the entire Midlatitude Continental Convective Clouds Experiment (MC3E) campaign. Preliminary results from several models will be presented. (http://portal.nersc.gov/project/capt/CAUSES/) (This study is funded by the RGCM and ASR programs of the U.S. Department of Energy as part of the Cloud-Associated Parameterizations Testbed. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-658017)

Variability of Upper-Tropospheric Precipitable from Satellite and Model Reanalysis Datasets

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Iwai, Hisaki

1999-01-01

Numerous datasets have been used to quantify water vapor and its variability in the upper-troposphere from satellite and model reanalysis data. These investigations have shown some usefulness in monitoring seasonal and inter-annual variations in moisture either globally, with polar orbiting satellite data or global model output analysis, or regionally, with the higher spatial and temporal resolution geostationary measurements. The datasets are not without limitations, however, due to coverage or limited temporal sampling, and may also contain bias in their representation of moisture processes. The research presented in this conference paper inter-compares the NVAP, NCEP/NCAR and DAO reanalysis models, and GOES satellite measurements of upper-tropospheric,precipitable water for the period from 1988-1994. This period captures several dramatic swings in climate events associated with ENSO events. The data are evaluated for temporal and spatial continuity, inter-compared to assess reliability and potential bias, and analyzed in light of expected trends due to changes in precipitation and synoptic-scale weather features. This work is the follow-on to previous research which evaluated total precipitable water over the same period. The relationship between total and upper-level precipitable water in the datasets will be discussed as well.

Global Optimization Ensemble Model for Classification Methods

PubMed Central

Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab

2014-01-01

Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382

Clear-sky irradiance simulation using GMAO products and its comparison to ground and CERES satellite observation

NASA Astrophysics Data System (ADS)

Ham, S. H.; Loeb, N. G.; Kato, S.; Rose, F. G.; Bosilovich, M. G.; Rutan, D. A.; Huang, X.; Collow, A.

2017-12-01

Global Modeling Assimilation Office (GMAO) GEOS assimilated datasets are used to describe temperature and humidity profiles in the Clouds and the Earth's Radiant Energy System (CERES) data processing. Given that advance versions of the assimilated data sets known as of Forward Processing (FP), FP Parallel (FPP), and Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) datasets are available, we examine clear-sky irradiance calculation to see if accuracy is improved with these newer versions of GMAO datasets when their temperature and humidity profiles are used in computing irradiances. Two older versions, GEOS-5.2.0 and GEOS-5.4.1 are used for producing, respectively, Ed3 and Ed4 CERES data products. For the evaluation, CERES-derived TOA irradiances and observed ground-based surface irradiances are compared with the computed irradiances for clear skies identified by Moderate Resolution Imaging Spectroradiometer (MODIS). Surface type dependent spectral emissivity is taken from an observationally-based monthly gridded emissivity dataset. TOA longwave (LW) irradiances computed with GOES-5.2.0 temperature and humidity profiles are biased low, up to -5 Wm-2, compared to CERES-derived TOA longwave irradiance over tropical oceans. In contrast, computed longwave irradiances agree well with CERES observations with the biases less than 2 W m-2 when GOES-5.4.1, FP v5.13, or MERRA-2 temperature and humidity are used. The negative biases of the TOA LW irradiance computed with GOES-5.2.0 appear to be related to a wet bias at 500-850 hPa layer. This indicates that if the input of CERES algorithm switches from GOES-5.2.0 to FP v5.13 or MERRA-2, the bias in clear-sky longwave TOA fluxes over tropical oceans is expected to be smaller. At surface, downward LW irradiances computed with FP v5.13 and MERRA-2 are biased low, up to -10 Wm-2, compared to ground observations over tropical oceans. The magnitude of the bias in the longwave surface irradiances cannot be explained by uncertainties related to aerosol, which is estimated to be less than 2.5 W m-2. Therefore, the negative biases are likely caused by cold or dry biases in FP v5.13 and MERRA-2 datasets. We plan to continue the investigation with more ground sites.

Vision for a Global Registry of Anticipated Public Health Studies

PubMed Central

Choi, Bernard C.K.; Frank, John; Mindell, Jennifer S.; Orlova, Anna; Lin, Vivian; Vaillancourt, Alain D.M.G.; Puska, Pekka; Pang, Tikki; Skinner, Harvey A.; Marsh, Marsha; Mokdad, Ali H.; Yu, Shun-Zhang; Lindner, M. Cristina; Sherman, Gregory; Barreto, Sandhi M.; Green, Lawrence W.; Svenson, Lawrence W.; Sainsbury, Peter; Yan, Yongping; Zhang, Zuo-Feng; Zevallos, Juan C.; Ho, Suzanne C.; de Salazar, Ligia M.

2007-01-01

In public health, the generation, management, and transfer of knowledge all need major improvement. Problems in generating knowledge include an imbalance in research funding, publication bias, unnecessary studies, adherence to fashion, and undue interest in novel and immediate issues. Impaired generation of knowledge, combined with a dated and inadequate process for managing knowledge and an inefficient system for transferring knowledge, mean a distorted body of evidence available for decisionmaking in public health. This article hopes to stimulate discussion by proposing a Global Registry of Anticipated Public Health Studies. This prospective, comprehensive system for tracking research in public health could help enhance collaboration and improve efficiency. Practical problems must be discussed before such a vision can be further developed. PMID:17413073

Sampling biases in datasets of historical mean air temperature over land.

PubMed

Wang, Kaicun

2014-04-10

Global mean surface air temperature (Ta) has been reported to have risen by 0.74°C over the last 100 years. However, the definition of mean Ta is still a subject of debate. The most defensible definition might be the integral of the continuous temperature measurements over a day (Td0). However, for technological and historical reasons, mean Ta over land have been taken to be the average of the daily maximum and minimum temperature measurements (Td1). All existing principal global temperature analyses over land rely heavily on Td1. Here, I make a first quantitative assessment of the bias in the use of Td1 to estimate trends of mean Ta using hourly Ta observations at 5600 globally distributed weather stations from the 1970s to 2013. I find that the use of Td1 has a negligible impact on the global mean warming rate. However, the trend of Td1 has a substantial bias at regional and local scales, with a root mean square error of over 25% at 5° × 5° grids. Therefore, caution should be taken when using mean Ta datasets based on Td1 to examine high resolution details of warming trends.

Evaluation of the Global Multi-Resolution Terrain Elevation Data 2010 (GMTED2010) using ICESat geodetic control

USGS Publications Warehouse

Carabajal, C.C.; Harding, D.J.; Boy, J.-P.; Danielson, Jeffrey J.; Gesch, D.B.; Suchdeo, V.P.

2011-01-01

Supported by NASA's Earth Surface and Interior (ESI) Program, we are producing a global set of Ground Control Points (GCPs) derived from the Ice, Cloud and land Elevation Satellite (ICESat) altimetry data. From February of 2003, to October of 2009, ICESat obtained nearly global measurements of land topography (?? 86?? latitudes) with unprecedented accuracy, sampling the Earth's surface at discrete ???50 m diameter laser footprints spaced 170 m along the altimetry profiles. We apply stringent editing to select the highest quality elevations, and use these GCPs to characterize and quantify spatially varying elevation biases in Digital Elevation Models (DEMs). In this paper, we present an evaluation of the soon to be released Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010). Elevation biases and error statistics have been analyzed as a function of land cover and relief. The GMTED2010 products are a large improvement over previous sources of elevation data at comparable resolutions. RMSEs for all products and terrain conditions are below 7 m and typically are about 4 m. The GMTED2010 products are biased upward with respect to the ICESat GCPs on average by approximately 3 m. ?? 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Evaluation of the Global Multi-Resolution Terrain Elevation Data 2010 (GMTED2010) Using ICESat Geodetic Control

NASA Technical Reports Server (NTRS)

Carabajal, Claudia C.; Harding, David J.; Boy, Jean-Paul; Danielson, Jeffrey J.; Gesch, Dean B.; Suchdeo, Vijay P.

2011-01-01

Supported by NASA's Earth Surface and Interior (ESI) Program, we are producing a global set of Ground Control Points (GCPs) derived from the Ice, Cloud and land Elevation Satellite (ICESat) altimetry data. From February of 2003, to October of 2009, ICESat obtained nearly global measurements of land topography (+/- 86deg latitudes) with unprecedented accuracy, sampling the Earth's surface at discrete approx.50 m diameter laser footprints spaced 170 m along the altimetry profiles. We apply stringent editing to select the highest quality elevations, and use these GCPs to characterize and quantify spatially varying elevation biases in Digital Elevation Models (DEMs). In this paper, we present an evaluation of the soon to be released Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010). Elevation biases and error statistics have been analyzed as a function of land cover and relief. The GMTED2010 products are a large improvement over previous sources of elevation data at comparable resolutions. RMSEs for all products and terrain conditions are below 7 m and typically are about 4 m. The GMTED2010 products are biased upward with respect to the ICESat GCPs on average by approximately 3 m.

What does a compound letter tell the psychologist's mind?

PubMed

Navon, David

2003-11-01

The paradigm based on using compound stimuli for studying global and local processing is revisited. Noting that not all researchers employ compound stimuli for the same purpose, the issue of its purpose is discussed. It is argued that the paradigm is pertinent for examining at least three notions--formation preference, global addressability, and within-object global precedence. It is suggested that findings in the paradigm are accommodated well by a disjunction of those three perceptual dispositions. A number of further issues associated with the interpretation of findings obtained with it are examined as well. An experimental study is reported that is meant to examine one such issue--a possible artifact putatively introduced by the special attribute of element homogeneity characteristic of compound stimuli. Seven experiments were used to examine to what extent, if at all, global advantage observed in compound stimulus paradigms depends on element heterogeneity. Across those experiments, heterogeneity did not have any effect that could be interpreted as suggesting that the paradigm is biased in favor of the global structure due to element homogeneity.

Simulating PACE Global Ocean Radiances

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Rousseaux, Cecile S.

2017-01-01

The NASA PACE mission is a hyper-spectral radiometer planned for launch in the next decade. It is intended to provide new information on ocean biogeochemical constituents by parsing the details of high resolution spectral absorption and scattering. It is the first of its kind for global applications and as such, poses challenges for design and operation. To support pre-launch mission development and assess on-orbit capabilities, the NASA Global Modeling and Assimilation Office has developed a dynamic simulation of global water-leaving radiances, using an ocean model containing multiple ocean phytoplankton groups, particulate detritus, particulate inorganic carbon (PIC), and chromophoric dissolved organic carbon (CDOC) along with optical absorption and scattering processes at 1 nm spectral resolution. The purpose here is to assess the skill of the dynamic model and derived global radiances. Global bias, uncertainty, and correlation are derived using available modern satellite radiances at moderate spectral resolution. Total chlorophyll, PIC, and the absorption coefficient of CDOC (aCDOC), are simultaneously assimilated to improve the fidelity of the optical constituent fields. A 5-year simulation showed statistically significant (P < 0.05) comparisons of chlorophyll (r = 0.869), PIC (r = 0.868), and a CDOC (r =0.890) with satellite data. Additionally, diatoms (r = 0.890), cyanobacteria (r = 0.732), and coccolithophores (r = 0.716) were significantly correlated with in situ data. Global assimilated distributions of optical constituents were coupled with a radiative transfer model (Ocean-Atmosphere Spectral Irradiance Model, OASIM) to estimate normalized water-leaving radiances at 1 nm for the spectral range 250-800 nm. These unassimilated radiances were within 0.074 mW/sq cm/micron/sr of MODIS-Aqua radiances at 412, 443, 488, 531, 547, and 667 nm. This difference represented a bias of 10.4% (model low). A mean correlation of 0.706 (P < 0.05) was found with global distributions of MODIS radiances. These results suggest skill in the global assimilated model and resulting radiances. The reported error characterization suggests that the global dynamical simulation can support some aspects of mission design and analysis. For example, the high spectral resolution of the simulation supports investigations of band selection. The global nature of the radiance representations supports investigations of satellite observing scenarios. Global radiances at bands not available in current and past missions support investigations of mission capability. PACE, ocean color, water-leaving radiances, biogeochemical model, radiative transfer model

Simulating PACE Global Ocean Radiances

PubMed Central

Gregg, Watson W.; Rousseaux, Cécile S.

2017-01-01

The NASA PACE mission is a hyper-spectral radiometer planned for launch in the next decade. It is intended to provide new information on ocean biogeochemical constituents by parsing the details of high resolution spectral absorption and scattering. It is the first of its kind for global applications and as such, poses challenges for design and operation. To support pre-launch mission development and assess on-orbit capabilities, the NASA Global Modeling and Assimilation Office has developed a dynamic simulation of global water-leaving radiances, using an ocean model containing multiple ocean phytoplankton groups, particulate detritus, particulate inorganic carbon (PIC), and chromophoric dissolved organic carbon (CDOC) along with optical absorption and scattering processes at 1 nm spectral resolution. The purpose here is to assess the skill of the dynamic model and derived global radiances. Global bias, uncertainty, and correlation are derived using available modern satellite radiances at moderate spectral resolution. Total chlorophyll, PIC, and the absorption coefficient of CDOC (aCDOC), are simultaneously assimilated to improve the fidelity of the optical constituent fields. A 5-year simulation showed statistically significant (P <0.05) comparisons of chlorophyll (r = 0.869), PIC (r = 0.868), and aCDOC (r = 0.890) with satellite data. Additionally, diatoms (r = 0.890), cyanobacteria (r = 0.732), and coccolithophores (r = 0.716) were significantly correlated with in situ data. Global assimilated distributions of optical constituents were coupled with a radiative transfer model (Ocean-Atmosphere Spectral Irradiance Model, OASIM) to estimate normalized water-leaving radiances at 1 nm for the spectral range 250–800 nm. These unassimilated radiances were within −0.074 mW cm−2 μm1 sr−1 of MODIS-Aqua radiances at 412, 443, 488, 531, 547, and 667 nm. This difference represented a bias of −10.4% (model low). A mean correlation of 0.706 (P < 0.05) was found with global distributions of MODIS radiances. These results suggest skill in the global assimilated model and resulting radiances. The reported error characterization suggests that the global dynamical simulation can support some aspects of mission design and analysis. For example, the high spectral resolution of the simulation supports investigations of band selection. The global nature of the radiance representations supports investigations of satellite observing scenarios. Global radiances at bands not available in current and past missions support investigations of mission capability. PMID:29292403

The Rise of Global Science and the Emerging Political Economy of International Research Collaborations

ERIC Educational Resources Information Center

Peters, Michael A.

2006-01-01

This article charts the rise of global science and a global science infrastructure as part of the emerging international knowledge system exemplifying a geography of knowledge and the importance of new info-communications networks. The article theorises the rise of global science, which still strongly reflects a Western bias and is highly…

Stability Analysis of Receiver ISB for BDS/GPS

NASA Astrophysics Data System (ADS)

Zhang, H.; Hao, J. M.; Tian, Y. G.; Yu, H. L.; Zhou, Y. L.

2017-07-01

Stability analysis of receiver ISB (Inter-System Bias) is essential for understanding the feature of ISB as well as the ISB modeling and prediction. In order to analyze the long-term stability of ISB, the data from MGEX (Multi-GNSS Experiment) covering 3 weeks, which are from 2014, 2015 and 2016 respectively, are processed with the precise satellite clock and orbit products provided by Wuhan University and GeoForschungsZentrum (GFZ). Using the ISB calculated by BDS (BeiDou Navigation Satellite System)/GPS (Global Positioning System) combined PPP (Precise Point Positioning), the daily stability and weekly stability of ISB are investigated. The experimental results show that the diurnal variation of ISB is stable, and the average of daily standard deviation is about 0.5 ns. The weekly averages and standard deviations of ISB vary greatly in different years. The weekly averages of ISB are relevant to receiver types. There is a system bias between ISB calculated from the precise products provided by Wuhan University and GFZ. In addition, the system bias of the weekly average ISB of different stations is consistent with each other.

A meta-analysis of sex differences in human brain structure☆

PubMed Central

Ruigrok, Amber N.V.; Salimi-Khorshidi, Gholamreza; Lai, Meng-Chuan; Baron-Cohen, Simon; Lombardo, Michael V.; Tait, Roger J.; Suckling, John

2014-01-01

The prevalence, age of onset, and symptomatology of many neuropsychiatric conditions differ between males and females. To understand the causes and consequences of sex differences it is important to establish where they occur in the human brain. We report the first meta-analysis of typical sex differences on global brain volume, a descriptive account of the breakdown of studies of each compartmental volume by six age categories, and whole-brain voxel-wise meta-analyses on brain volume and density. Gaussian-process regression coordinate-based meta-analysis was used to examine sex differences in voxel-based regional volume and density. On average, males have larger total brain volumes than females. Examination of the breakdown of studies providing total volumes by age categories indicated a bias towards the 18–59 year-old category. Regional sex differences in volume and tissue density include the amygdala, hippocampus and insula, areas known to be implicated in sex-biased neuropsychiatric conditions. Together, these results suggest candidate regions for investigating the asymmetric effect that sex has on the developing brain, and for understanding sex-biased neurological and psychiatric conditions. PMID:24374381

New Radiosonde Temperature Bias Adjustments for Potential NWP Applications Based on GPS RO Data

NASA Astrophysics Data System (ADS)

Sun, B.; Reale, A.; Ballish, B.; Seidel, D. J.

2014-12-01

Conventional radiosonde observations (RAOBs), along with satellite and other in situ data, are assimilated in numerical weather prediction (NWP) models to generate a forecast. Radiosonde temperature observations, however, have solar and thermal radiation induced biases (typically a warm daytime bias from sunlight heating the sensor and a cold bias at night as the sensor emits longwave radiation). Radiation corrections made at stations based on algorithms provided by radiosonde manufacturers or national meteorological agencies may not be adequate, so biases remain. To adjust these biases, NWP centers may make additional adjustments to radiosonde data. However, the radiation correction (RADCOR) schemes used in the NOAA NCEP data assimilation and forecasting system is outdated and does not cover several widely-used contemporary radiosonde types. This study focuses on work whose objective is to improve these corrections and test their impacts on the NWP forecasting and analysis. GPS Radio Occultation (RO) dry temperature (Tdry) is considered to be highly accurate in the upper troposphere and low stratosphere where atmospheric water vapor is negligible. This study uses GPS RO Tdry from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) as the reference to quantify the radiation induced RAOB temperature errors by analyzing ~ 3-yr collocated RAOB and COSMIC GPS RO data compile by the NOAA Products Validation System (NPROVS). The new radiation adjustments are developed for different solar angle categories and for all common sonde types flown in the WMO global operational upper air network. Results for global and several commonly used sondes are presented in the context of NCEP Global Forecast System observation-minus-background analysis, indicating projected impacts in reducing forecast error. Dedicated NWP impact studies to quantify the impact of the new RADCOR schemes on the NCEP analyses and forecast are under consideration.

What is the importance of climate model bias when projecting the impacts of climate change on land surface processes?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, M. L.; Rajagopalan, K.; Chung, S. H.

2014-05-16

Regional climate change impact (CCI) studies have widely involved downscaling and bias-correcting (BC) Global Climate Model (GCM)-projected climate for driving land surface models. However, BC may cause uncertainties in projecting hydrologic and biogeochemical responses to future climate due to the impaired spatiotemporal covariance of climate variables and a breakdown of physical conservation principles. Here we quantify the impact of BC on simulated climate-driven changes in water variables(evapotranspiration, ET; runoff; snow water equivalent, SWE; and water demand for irrigation), crop yield, biogenic volatile organic compounds (BVOC), nitric oxide (NO) emissions, and dissolved inorganic nitrogen (DIN) export over the Pacific Northwest (PNW)more » Region. We also quantify the impacts on net primary production (NPP) over a small watershed in the region (HJ Andrews). Simulation results from the coupled ECHAM5/MPI-OM model with A1B emission scenario were firstly dynamically downscaled to 12 km resolutions with WRF model. Then a quantile mapping based statistical downscaling model was used to downscale them into 1/16th degree resolution daily climate data over historical and future periods. Two series climate data were generated according to the option of bias-correction (i.e. with bias-correction (BC) and without bias-correction, NBC). Impact models were then applied to estimate hydrologic and biogeochemical responses to both BC and NBC meteorological datasets. These im20 pact models include a macro-scale hydrologic model (VIC), a coupled cropping system model (VIC-CropSyst), an ecohydrologic model (RHESSys), a biogenic emissions model (MEGAN), and a nutrient export model (Global-NEWS). Results demonstrate that the BC and NBC climate data provide consistent estimates of the climate-driven changes in water fluxes (ET, runoff, and water demand), VOCs (isoprene and monoterpenes) and NO emissions, mean crop yield, and river DIN export over the PNW domain. However, significant differences rise from projected SWE, crop yield from dry lands, and HJ Andrews’s ET between BC and NBC data. Even though BC post-processing has no significant impacts on most of the studied variables when taking PNW as a whole, their effects have large spatial variations and some local areas are substantially influenced. In addition, there are months during which BC and NBC post-processing produces significant differences in projected changes, such as summer runoff. Factor-controlled simulations indicate that BC post-processing of precipitation and temperature both substantially contribute to these differences at region scales. We conclude that there are trade-offs between using BC climate data for offline CCI studies vs. direct modeled climate data. These trade-offs should be considered when designing integrated modeling frameworks for specific applications; e.g., BC may be more important when considering impacts on reservoir operations in mountainous watersheds than when investigating impacts on biogenic emissions and air quality (where VOCs are a primary indicator).« less

Eye Movements while Reading Biased Homographs: Effects of Prior Encounter and Biasing Context on Reducing the Subordinate Bias Effect

PubMed Central

Leinenger, Mallorie; Rayner, Keith

2013-01-01

Readers experience processing difficulties when reading biased homographs preceded by subordinate-biasing contexts. Attempts to overcome this processing deficit have often failed to reduce the subordinate bias effect (SBE). In the present studies, we examined the processing of biased homographs preceded by single-sentence, subordinate-biasing contexts, and varied whether this preceding context contained a prior instance of the homograph or a control word/phrase. Having previously encountered the homograph earlier in the sentence reduced the SBE for the subsequent encounter, while simply instantiating the subordinate meaning produced processing difficulty. We compared these reductions in reading times to differences in processing time between dominant-biased repeated and non-repeated conditions in order to verify that the reductions observed in the subordinate cases did not simply reflect a general repetition benefit. Our results indicate that a strong, subordinate-biasing context can interact during lexical access to overcome the activation from meaning frequency and reduce the SBE during reading. PMID:24073328

GEWEX Water and Energy Budget Study

NASA Technical Reports Server (NTRS)

Roads, J.; Bainto, E.; Masuda, K.; Rodell, Matthew; Rossow, W. B.

2008-01-01

Closing the global water and energy budgets has been an elusive Global Energy and Water-cycle Experiment (GEWEX) goal. It has been difficult to gather many of the needed global water and energy variables and processes, although, because of GEWEX, we now have globally gridded observational estimates for precipitation and radiation and many other relevant variables such as clouds and aerosols. Still, constrained models are required to fill in many of the process and variable gaps. At least there are now several atmospheric reanalyses ranging from the early National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) and NCEP/Department of Energy (DOE) reanalyses to the more recent ERA40 and JRA-25 reanalyses. Atmospheric constraints include requirements that the models state variables remain close to in situ observations or observed satellite radiances. This is usually done by making short-term forecasts from an analyzed initial state; these short-term forecasts provide the next guess, which is corrected by comparison to available observations. While this analysis procedure is likely to result in useful global descriptions of atmospheric temperature, wind and humidity, there is no guarantee that relevant hydroclimate processes like precipitation, which we can observe and evaluate, and evaporation over land, which we cannot, have similar verisimilitude. Alternatively, the Global Land Data Assimilation System (GLDAS), drives uncoupled land surface models with precipitation, surface solar radiation, and surface meteorology (from bias-corrected reanalyses during the study period) to simulate terrestrial states and surface fluxes. Further constraints are made when a tuned water balance model is used to characterize the global runoff observational estimates. We use this disparate mix of observational estimates, reanalyses, GLDAS and calibrated water balance simulations to try to characterize and close global and terrestrial atmospheric and surface water and energy budgets to within 10-20% for long term (1986-1995), large-scale global to regional annual means.

Practical guidance on characterizing availability in resource selection functions under a use-availability design

USGS Publications Warehouse

Northrup, Joseph M.; Hooten, Mevin B.; Anderson, Charles R.; Wittemyer, George

2013-01-01

Habitat selection is a fundamental aspect of animal ecology, the understanding of which is critical to management and conservation. Global positioning system data from animals allow fine-scale assessments of habitat selection and typically are analyzed in a use-availability framework, whereby animal locations are contrasted with random locations (the availability sample). Although most use-availability methods are in fact spatial point process models, they often are fit using logistic regression. This framework offers numerous methodological challenges, for which the literature provides little guidance. Specifically, the size and spatial extent of the availability sample influences coefficient estimates potentially causing interpretational bias. We examined the influence of availability on statistical inference through simulations and analysis of serially correlated mule deer GPS data. Bias in estimates arose from incorrectly assessing and sampling the spatial extent of availability. Spatial autocorrelation in covariates, which is common for landscape characteristics, exacerbated the error in availability sampling leading to increased bias. These results have strong implications for habitat selection analyses using GPS data, which are increasingly prevalent in the literature. We recommend researchers assess the sensitivity of their results to their availability sample and, where bias is likely, take care with interpretations and use cross validation to assess robustness.

A New Paradigm for Diagnosing Contributions to Model Aerosol Forcing Error

NASA Astrophysics Data System (ADS)

Jones, A. L.; Feldman, D. R.; Freidenreich, S.; Paynter, D.; Ramaswamy, V.; Collins, W. D.; Pincus, R.

2017-12-01

A new paradigm in benchmark absorption-scattering radiative transfer is presented that enables both the globally averaged and spatially resolved testing of climate model radiation parameterizations in order to uncover persistent sources of biases in the aerosol instantaneous radiative effect (IRE). A proof of concept is demonstrated with the Geophysical Fluid Dynamics Laboratory AM4 and Community Earth System Model 1.2.2 climate models. Instead of prescribing atmospheric conditions and aerosols, as in prior intercomparisons, native snapshots of the atmospheric state and aerosol optical properties from the participating models are used as inputs to an accurate radiation solver to uncover model-relevant biases. These diagnostic results show that the models' aerosol IRE bias is of the same magnitude as the persistent range cited ( 1 W/m2) and also varies spatially and with intrinsic aerosol optical properties. The findings underscore the significance of native model error analysis and its dispositive ability to diagnose global biases, confirming its fundamental value for the Radiative Forcing Model Intercomparison Project.

Evaluation of atmospheric profiles derived from single- and zero-difference excess phase processing of BeiDou radio occultation data from the FY-3C GNOS mission

NASA Astrophysics Data System (ADS)

Bai, Weihua; Liu, Congliang; Meng, Xiangguang; Sun, Yueqiang; Kirchengast, Gottfried; Du, Qifei; Wang, Xianyi; Yang, Guanglin; Liao, Mi; Yang, Zhongdong; Zhao, Danyang; Xia, Junming; Cai, Yuerong; Liu, Lijun; Wang, Dongwei

2018-02-01

The Global Navigation Satellite System (GNSS) Occultation Sounder (GNOS) is one of the new-generation payloads onboard the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth's neutral atmosphere and ionosphere. The GNOS was designed for acquiring setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BeiDou System (BDS) and the US Global Positioning System (GPS). An ultra-stable oscillator with 1 s stability (Allan deviation) at the level of 10-12 was installed on the FY-3C GNOS, and thus both zero-difference and single-difference excess phase processing methods should be feasible for FY-3C GNOS observations. In this study we focus on evaluating zero-difference processing of BDS RO data vs. single-difference processing, in order to investigate the zero-difference feasibility for this new instrument, which after its launch in September 2013 started to use BDS signals from five geostationary orbit (GEO) satellites, five inclined geosynchronous orbit (IGSO) satellites and four medium Earth orbit (MEO) satellites. We used a 3-month set of GNOS BDS RO data (October to December 2013) for the evaluation and compared atmospheric bending angle and refractivity profiles, derived from single- and zero-difference excess phase data, against co-located profiles from European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. We also compared against co-located refractivity profiles from radiosondes. The statistical evaluation against these reference data shows that the results from single- and zero-difference processing are reasonably consistent in both bias and standard deviation, clearly demonstrating the feasibility of zero differencing for GNOS BDS RO observations. The average bias (and standard deviation) of the bending angle and refractivity profiles were found to be about 0.05 to 0.2 % (and 0.7 to 1.6 %) over the upper troposphere and lower stratosphere. Zero differencing was found to perform slightly better, as may be expected from its lower vulnerability to noise. The validation results indicate that GNOS can provide, on top of GPS RO profiles, accurate and precise BDS RO profiles both from single- and zero-difference processing. The GNOS observations by the series of FY-3 satellites are thus expected to provide important contributions to numerical weather prediction and global climate change analysis.

Affective Components Perceived to Be Important in Today's Global Society from a Cross-Cultural Perspective

ERIC Educational Resources Information Center

Wallenberg-Lerner, Helena

2013-01-01

Global competencies, with differences in terminology by various researchers, had been frequently investigated, primarily from an American-biased perspective. Little or no defining research existed that identified requisite, universally agreed upon global competencies, or identified what affective components were perceived to be important cross…

An Unbiased Estimate of Global Interrater Agreement

ERIC Educational Resources Information Center

Cousineau, Denis; Laurencelle, Louis

2017-01-01

Assessing global interrater agreement is difficult as most published indices are affected by the presence of mixtures of agreements and disagreements. A previously proposed method was shown to be specifically sensitive to global agreement, excluding mixtures, but also negatively biased. Here, we propose two alternatives in an attempt to find what…

The global distribution of tetrapods reveals a need for targeted reptile conservation.

PubMed

Roll, Uri; Feldman, Anat; Novosolov, Maria; Allison, Allen; Bauer, Aaron M; Bernard, Rodolphe; Böhm, Monika; Castro-Herrera, Fernando; Chirio, Laurent; Collen, Ben; Colli, Guarino R; Dabool, Lital; Das, Indraneil; Doan, Tiffany M; Grismer, Lee L; Hoogmoed, Marinus; Itescu, Yuval; Kraus, Fred; LeBreton, Matthew; Lewin, Amir; Martins, Marcio; Maza, Erez; Meirte, Danny; Nagy, Zoltán T; de C Nogueira, Cristiano; Pauwels, Olivier S G; Pincheira-Donoso, Daniel; Powney, Gary D; Sindaco, Roberto; Tallowin, Oliver J S; Torres-Carvajal, Omar; Trape, Jean-François; Vidan, Enav; Uetz, Peter; Wagner, Philipp; Wang, Yuezhao; Orme, C David L; Grenyer, Richard; Meiri, Shai

2017-11-01

The distributions of amphibians, birds and mammals have underpinned global and local conservation priorities, and have been fundamental to our understanding of the determinants of global biodiversity. In contrast, the global distributions of reptiles, representing a third of terrestrial vertebrate diversity, have been unavailable. This prevented the incorporation of reptiles into conservation planning and biased our understanding of the underlying processes governing global vertebrate biodiversity. Here, we present and analyse the global distribution of 10,064 reptile species (99% of extant terrestrial species). We show that richness patterns of the other three tetrapod classes are good spatial surrogates for species richness of all reptiles combined and of snakes, but characterize diversity patterns of lizards and turtles poorly. Hotspots of total and endemic lizard richness overlap very little with those of other taxa. Moreover, existing protected areas, sites of biodiversity significance and global conservation schemes represent birds and mammals better than reptiles. We show that additional conservation actions are needed to effectively protect reptiles, particularly lizards and turtles. Adding reptile knowledge to a global complementarity conservation priority scheme identifies many locations that consequently become important. Notably, investing resources in some of the world's arid, grassland and savannah habitats might be necessary to represent all terrestrial vertebrates efficiently.

A global satellite environmental data record derived from AMSR-E and AMSR2 microwave Earth observations

NASA Astrophysics Data System (ADS)

Du, Jinyang; Kimball, John S.; Jones, Lucas A.; Kim, Youngwook; Glassy, Joseph; Watts, Jennifer D.

2017-11-01

Spaceborne microwave remote sensing is widely used to monitor global environmental changes for understanding hydrological, ecological, and climate processes. A new global land parameter data record (LPDR) was generated using similar calibrated, multifrequency brightness temperature (Tb) retrievals from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2). The resulting LPDR provides a long-term (June 2002-December 2015) global record of key environmental observations at a 25 km grid cell resolution, including surface fractional open water (FW) cover, atmosphere precipitable water vapor (PWV), daily maximum and minimum surface air temperatures (Tmx and Tmn), vegetation optical depth (VOD), and surface volumetric soil moisture (VSM). Global mapping of the land parameter climatology means and seasonal variability over the full-year records from AMSR-E (2003-2010) and AMSR2 (2013-2015) observation periods is consistent with characteristic global climate and vegetation patterns. Quantitative comparisons with independent observations indicated favorable LPDR performance for FW (R ≥ 0.75; RMSE ≤ 0.06), PWV (R ≥ 0.91; RMSE ≤ 4.94 mm), Tmx and Tmn (R ≥ 0.90; RMSE ≤ 3.48 °C), and VSM (0.63 ≤ R ≤ 0.84; bias-corrected RMSE ≤ 0.06 cm3 cm-3). The LPDR-derived global VOD record is also proportional to satellite-observed NDVI (GIMMS3g) seasonality (R ≥ 0.88) due to the synergy between canopy biomass structure and photosynthetic greenness. Statistical analysis shows overall LPDR consistency but with small biases between AMSR-E and AMSR2 retrievals that should be considered when evaluating long-term environmental trends. The resulting LPDR and potential updates from continuing AMSR2 operations provide for effective global monitoring of environmental parameters related to vegetation activity, terrestrial water storage, and mobility and are suitable for climate and ecosystem studies. The LPDR dataset is publicly available at http://files.ntsg.umt.edu/data/LPDR_v2/.<

Automatic segmentation for brain MR images via a convex optimized segmentation and bias field correction coupled model.

PubMed

Chen, Yunjie; Zhao, Bo; Zhang, Jianwei; Zheng, Yuhui

2014-09-01

Accurate segmentation of magnetic resonance (MR) images remains challenging mainly due to the intensity inhomogeneity, which is also commonly known as bias field. Recently active contour models with geometric information constraint have been applied, however, most of them deal with the bias field by using a necessary pre-processing step before segmentation of MR data. This paper presents a novel automatic variational method, which can segment brain MR images meanwhile correcting the bias field when segmenting images with high intensity inhomogeneities. We first define a function for clustering the image pixels in a smaller neighborhood. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. In order to reduce the effect of the noise, the local intensity variations are described by the Gaussian distributions with different means and variances. Then, the objective functions are integrated over the entire domain. In order to obtain the global optimal and make the results independent of the initialization of the algorithm, we reconstructed the energy function to be convex and calculated it by using the Split Bregman theory. A salient advantage of our method is that its result is independent of initialization, which allows robust and fully automated application. Our method is able to estimate the bias of quite general profiles, even in 7T MR images. Moreover, our model can also distinguish regions with similar intensity distribution with different variances. The proposed method has been rigorously validated with images acquired on variety of imaging modalities with promising results. Copyright © 2014 Elsevier Inc. All rights reserved.

Quantile Mapping Bias correction for daily precipitation over Vietnam in a regional climate model

NASA Astrophysics Data System (ADS)

Trinh, L. T.; Matsumoto, J.; Ngo-Duc, T.

2017-12-01

In the past decades, Regional Climate Models (RCMs) have been developed significantly, allowing climate simulation to be conducted at a higher resolution. However, RCMs often contained biases when comparing with observations. Therefore, statistical correction methods were commonly employed to reduce/minimize the model biases. In this study, outputs of the Regional Climate Model (RegCM) version 4.3 driven by the CNRM-CM5 global products were evaluated with and without the Quantile Mapping (QM) bias correction method. The model domain covered the area from 90oE to 145oE and from 15oS to 40oN with a horizontal resolution of 25km. The QM bias correction processes were implemented by using the Vietnam Gridded precipitation dataset (VnGP) and the outputs of RegCM historical run in the period 1986-1995 and then validated for the period 1996-2005. Based on the statistical quantity of spatial correlation and intensity distributions, the QM method showed a significant improvement in rainfall compared to the non-bias correction method. The improvements both in time and space were recognized in all seasons and all climatic sub-regions of Vietnam. Moreover, not only the rainfall amount but also some extreme indices such as R10m, R20mm, R50m, CDD, CWD, R95pTOT, R99pTOT were much better after the correction. The results suggested that the QM correction method should be taken into practice for the projections of the future precipitation over Vietnam.

Climate model biases and statistical downscaling for application in hydrologic model

USDA-ARS?s Scientific Manuscript database

Climate change impact studies use global climate model (GCM) simulations to define future temperature and precipitation. The best available bias-corrected GCM output was obtained from Coupled Model Intercomparison Project phase 5 (CMIP5). CMIP5 data (temperature and precipitation) are available in d...

Spatial Correlation Bias in Thermochronologically Derived Late Cenozoic Erosion Histories

NASA Astrophysics Data System (ADS)

Schildgen, T. F.; van Der Beek, P.; Sinclair, H. D.; Thiede, R. C.

2017-12-01

The potential link between erosion rates at the Earth's surface and changes in global climate has intrigued geoscientists for decades, as such a coupling has implications for the influence of silicate weathering and organic-carbon burial on climate, as well as the role of Quaternary glaciations on landscape evolution. A global increase in late-Cenozoic erosion rates in response to a cooling, more variable climate has been proposed based on a compilation of deposition rates in sedimentary basins worldwide. However, it has been argued that the stratigraphic record could show an apparent increase in rates toward the present due to a preservation bias linked to stochastic erosional events, depositional hiatuses, and varying measurement intervals. More recently, a global compilation of thermochronology data has been used to infer a nearly two-fold increase in erosion rates from mountainous landscapes over the late Cenozoic. It is contended that this result is free of the biases that affect sedimentary records. Here, we test this assumption and demonstrate that in addition to the bias resulting from the relative timescales over which thermochronological data are averaged, there is a bias associated with spatial variations in exhumation rates among points that are combined to derive exhumation histories. Whether one or multiple thermochronological systems are used to reconstruct an erosion history, there is always an apparent increase in rates toward the present when combining data that have not shared a common exhumation history (e.g., samples collected from different sides of an active tectonic boundary). Such unwarranted combinations commonly arise when inversions of thermochronological data are performed using an a priori scheme that combines data points according to an assumed spatial correlation structure. We find that in nearly all cases where such inversions have been performed, spatial gradients in erosion rates are converted into apparent temporal increases. On a global scale, currently available thermochronology data provide limited resolution concerning the impact of late Cenozoic climate change on erosion rates. These results, combined with previous analyses of bias in the sedimentary record, call into question the evidence presented to date for a worldwide increase in late Cenozoic erosion rates.

Improving Assimilated Global Data Sets using TMI Rainfall and Columnar Moisture Observations

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.

1999-01-01

A global analysis that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. In this study, we show that assimilating precipitation and total precipitable water (TPW) retrievals derived from the TRMM Microwave Imager (TMI) improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). In particular, assimilating TMI rain improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. The improved analysis also improves short-range forecasts in the tropics. Ensemble forecasts initialized with the GEOS analysis incorporating TMI rain rates and TPW yield smaller biases in tropical precipitation forecasts beyond 1 day and better 500 hPa geopotential height forecasts up to 5 days. Results of this study demonstrate the potential of using high-quality space-borne rainfall and moisture observations to improve the quality of assimilated global data for climate analysis and weather forecasting applications

Plasticity of visual attention in Isha yoga meditation practitioners before and after a 3-month retreat

PubMed Central

Braboszcz, Claire; Cahn, B. Rael; Balakrishnan, Bhavani; Maturi, Raj K.; Grandchamp, Romain; Delorme, Arnaud

2013-01-01

Meditation has lately received considerable interest from cognitive neuroscience. Studies suggest that daily meditation leads to long lasting attentional and neuronal plasticity. We present changes related to the attentional systems before and after a 3 month intensive meditation retreat. We used three behavioral psychophysical tests - a Stroop task, an attentional blink task, and a global-local letter task-to assess the effect of Isha yoga meditation on attentional resource allocation. 82 Isha yoga practitioners were tested at the beginning and at the end of the retreat. Our results showed an increase in correct responses specific to incongruent stimuli in the Stroop task. Congruently, a positive correlation between previous meditation experience and accuracy to incongruent Stroop stimuli was also observed at baseline. We also observed a reduction of the attentional blink. Unexpectedly, a negative correlation between previous meditation experience and attentional blink performance at baseline was observed. Regarding spatial attention orientation as assessed using the global-local letter task, participants showed a bias toward local processing. Only slight differences in performance were found pre- vs. post- meditation retreat. Biasing toward the local stimuli in the global-local task and negative correlation of previous meditation experience with attentional blink performance is consistent with Isha practices being focused-attention practices. Given the relatively small effect sizes and the absence of a control group, our results do not allow clear support nor rejection of the hypothesis of meditation-driven neuronal plasticity in the attentional system for Isha yoga practice. PMID:24376429

Free Energy Computations by Minimization of Kullback-Leibler Divergence: An Efficient Adaptive Biasing Potential Method for Sparse Representations

DTIC Science & Technology

2011-10-14

landscapes. It is motivated by statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and...statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and estimating the free energy...experimentally, to characterize global changes as well as investigate relative stabilities. In most applications, a brute- force computation based on

The cortical microstructural basis of lateralized cognition: a review

PubMed Central

Chance, Steven A.

2014-01-01

The presence of asymmetry in the human cerebral hemispheres is detectable at both the macroscopic and microscopic scales. The horizontal expansion of cortical surface during development (within individual brains), and across evolutionary time (between species), is largely due to the proliferation and spacing of the microscopic vertical columns of cells that form the cortex. In the asymmetric planum temporale (PT), minicolumn width asymmetry is associated with surface area asymmetry. Although the human minicolumn asymmetry is not large, it is estimated to account for a surface area asymmetry of approximately 9% of the region’s size. Critically, this asymmetry of minicolumns is absent in the equivalent areas of the brains of other apes. The left-hemisphere dominance for processing speech is thought to depend, partly, on a bias for higher resolution processing across widely spaced minicolumns with less overlapping dendritic fields, whereas dense minicolumn spacing in the right hemisphere is associated with more overlapping, lower resolution, holistic processing. This concept refines the simple notion that a larger brain area is associated with dominance for a function and offers an alternative explanation associated with “processing type.” This account is mechanistic in the sense that it offers a mechanism whereby asymmetrical components of structure are related to specific functional biases yielding testable predictions, rather than the generalization that “bigger is better” for any given function. Face processing provides a test case – it is the opposite of language, being dominant in the right hemisphere. Consistent with the bias for holistic, configural processing of faces, the minicolumns in the right-hemisphere fusiform gyrus are thinner than in the left hemisphere, which is associated with featural processing. Again, this asymmetry is not found in chimpanzees. The difference between hemispheres may also be seen in terms of processing speed, facilitated by asymmetric myelination of white matter tracts (Anderson et al., 1999 found that axons of the left posterior superior temporal lobe were more thickly myelinated). By cross-referencing the differences between the active fields of the two hemispheres, via tracts such as the corpus callosum, the relationship of local features to global features may be encoded. The emergent hierarchy of features within features is a recursive structure that may functionally contribute to generativity – the ability to perceive and express layers of structure and their relations to each other. The inference is that recursive generativity, an essential component of language, reflects an interaction between processing biases that may be traceable in the microstructure of the cerebral cortex. Minicolumn organization in the PT and the prefrontal cortex has been found to correlate with cognitive scores in humans. Altered minicolumn organization is also observed in neuropsychiatric disorders including autism and schizophrenia. Indeed, altered interhemispheric connections correlated with minicolumn asymmetry in schizophrenia may relate to language-processing anomalies that occur in the disorder. Schizophrenia is associated with over-interpretation of word meaning at the semantic level and over-interpretation of relevance at the level of pragmatic competence, whereas autism is associated with overly literal interpretation of word meaning and under-interpretation of social relevance at the pragmatic level. Both appear to emerge from a disruption of the ability to interpret layers of meaning and their relations to each other. This may be a consequence of disequilibrium in the processing of local and global features related to disorganization of minicolumnar units of processing. PMID:25126082

High-end climate change impact on European runoff and low flows – exploring the effects of forcing biases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papadimitriou, Lamprini V.; Koutroulis, Aristeidis G.; Grillakis, Manolis G.

Climate models project a much more substantial warming than the 2 °C target under the more probable emission scenarios, making higher-end scenarios increasingly plausible. Freshwater availability under such conditions is a key issue of concern. In this study, an ensemble of Euro-CORDEX projections under RCP8.5 is used to assess the mean and low hydrological states under +4 °C of global warming for the European region. Five major European catchments were analysed in terms of future drought climatology and the impact of +2 °C versus +4 °C global warming was investigated. The effect of bias correction of the climate model outputsmore » and the observations used for this adjustment was also quantified. Projections indicate an intensification of the water cycle at higher levels of warming. Even for areas where the average state may not considerably be affected, low flows are expected to reduce, leading to changes in the number of dry days and thus drought climatology. The identified increasing or decreasing runoff trends are substantially intensified when moving from the +2 to the +4° of global warming. Bias correction resulted in an improved representation of the historical hydrology. Moreover, it is also found that the selection of the observational data set for the application of the bias correction has an impact on the projected signal that could be of the same order of magnitude to the selection of the Global Climate Model (GCM).« less

High-end climate change impact on European runoff and low flows – exploring the effects of forcing biases

DOE PAGES

Papadimitriou, Lamprini V.; Koutroulis, Aristeidis G.; Grillakis, Manolis G.; ...

2016-05-10

Climate models project a much more substantial warming than the 2 °C target under the more probable emission scenarios, making higher-end scenarios increasingly plausible. Freshwater availability under such conditions is a key issue of concern. In this study, an ensemble of Euro-CORDEX projections under RCP8.5 is used to assess the mean and low hydrological states under +4 °C of global warming for the European region. Five major European catchments were analysed in terms of future drought climatology and the impact of +2 °C versus +4 °C global warming was investigated. The effect of bias correction of the climate model outputsmore » and the observations used for this adjustment was also quantified. Projections indicate an intensification of the water cycle at higher levels of warming. Even for areas where the average state may not considerably be affected, low flows are expected to reduce, leading to changes in the number of dry days and thus drought climatology. The identified increasing or decreasing runoff trends are substantially intensified when moving from the +2 to the +4° of global warming. Bias correction resulted in an improved representation of the historical hydrology. Moreover, it is also found that the selection of the observational data set for the application of the bias correction has an impact on the projected signal that could be of the same order of magnitude to the selection of the Global Climate Model (GCM).« less

Global Patch Matching

NASA Astrophysics Data System (ADS)

Huang, X.; Hu, K.; Ling, X.; Zhang, Y.; Lu, Z.; Zhou, G.

2017-09-01

This paper introduces a novel global patch matching method that focuses on how to remove fronto-parallel bias and obtain continuous smooth surfaces with assuming that the scenes covered by stereos are piecewise continuous. Firstly, simple linear iterative cluster method (SLIC) is used to segment the base image into a series of patches. Then, a global energy function, which consists of a data term and a smoothness term, is built on the patches. The data term is the second-order Taylor expansion of correlation coefficients, and the smoothness term is built by combing connectivity constraints and the coplanarity constraints are combined to construct the smoothness term. Finally, the global energy function can be built by combining the data term and the smoothness term. We rewrite the global energy function in a quadratic matrix function, and use least square methods to obtain the optimal solution. Experiments on Adirondack stereo and Motorcycle stereo of Middlebury benchmark show that the proposed method can remove fronto-parallel bias effectively, and produce continuous smooth surfaces.

Evolution of Indian land surface biases in the seasonal hindcasts from the Met Office Global Seasonal Forecasting System GloSea5

NASA Astrophysics Data System (ADS)

Chevuturi, Amulya; Turner, Andrew G.; Woolnoug, Steve J.; Martin, Gill

2017-04-01

In this study we investigate the development of biases over the Indian region in summer hindcasts of the UK Met Office coupled initialised global seasonal forecasting system, GloSea5-GC2. Previous work has demonstrated the rapid evolution of strong monsoon circulation biases over India from seasonal forecasts initialised in early May, together with coupled strong easterly wind biases on the equator. These mean state biases lead to strong precipitation errors during the monsoon over the subcontinent. We analyse a set of three springtime start dates for the 20-year hindcast period (1992-2011) and fifteen total ensemble members for each year. We use comparisons with variety of observations to assess the evolution of the mean state biases over the Indian land surface. All biases within the model develop rapidly, particularly surface heat and radiation flux biases. Strong biases are present within the model climatology from pre-monsoon (May) in the surface heat fluxes over India (higher sensible / lower latent heat fluxes) when compared to observed estimates. The early evolution of such biases prior to onset rains suggests possible problems with the land surface scheme or soil moisture errors. Further analysis of soil moisture over the Indian land surface shows a dry bias present from the beginning of the hindcasts during the pre-monsoon. This lasts until the after the monsoon develops (July) after which there is a wet bias over the region. Soil moisture used for initialization of the model also shows a dry bias when compared against the observed estimates, which may lead to the same in the model. The early dry bias in the model may reduce local moisture availability through surface evaporation and thus may possibly limit precipitation recycling. On this premise, we identify and test the sensitivity of the monsoon in the model against higher soil moisture forcing. We run sensitivity experiments initiated using gridpoint-wise annual soil moisture maxima over the Indian land surface as input for experiments in the atmosphere-only version of the model. We plan to analyse the response of the sensitivity experiments on seasonal forecasting of surface heat fluxes and subsequently monsoon precipitation.

Development and application of a large scale river system model for National Water Accounting in Australia

NASA Astrophysics Data System (ADS)

Dutta, Dushmanta; Vaze, Jai; Kim, Shaun; Hughes, Justin; Yang, Ang; Teng, Jin; Lerat, Julien

2017-04-01

Existing global and continental scale river models, mainly designed for integrating with global climate models, are of very coarse spatial resolutions and lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing water accounts, which have become increasingly important for water resources planning and management at regional and national scales. A continental scale river system model called Australian Water Resource Assessment River System model (AWRA-R) has been developed and implemented for national water accounting in Australia using a node-link architecture. The model includes major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. Two key components of the model are an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. The results in the Murray-Darling Basin shows highly satisfactory performance of the model with median daily Nash-Sutcliffe Efficiency (NSE) of 0.64 and median annual bias of less than 1% for the period of calibration (1970-1991) and median daily NSE of 0.69 and median annual bias of 12% for validation period (1992-2014). The results have demonstrated that the performance of the model is less satisfactory when the key processes such as overbank flow, groundwater seepage and irrigation diversion are switched off. The AWRA-R model, which has been operationalised by the Australian Bureau of Meteorology for continental scale water accounting, has contributed to improvements in the national water account by substantially reducing accounted different volume (gain/loss).

Rater variables associated with ITER ratings.

PubMed

Paget, Michael; Wu, Caren; McIlwrick, Joann; Woloschuk, Wayne; Wright, Bruce; McLaughlin, Kevin

2013-10-01

Advocates of holistic assessment consider the ITER a more authentic way to assess performance. But this assessment format is subjective and, therefore, susceptible to rater bias. Here our objective was to study the association between rater variables and ITER ratings. In this observational study our participants were clerks at the University of Calgary and preceptors who completed online ITERs between February 2008 and July 2009. Our outcome variable was global rating on the ITER (rated 1-5), and we used a generalized estimating equation model to identify variables associated with this rating. Students were rated "above expected level" or "outstanding" on 66.4 % of 1050 online ITERs completed during the study period. Two rater variables attenuated ITER ratings: the log transformed time taken to complete the ITER [β = -0.06, 95 % confidence interval (-0.10, -0.02), p = 0.002], and the number of ITERs that a preceptor completed over the time period of the study [β = -0.008 (-0.02, -0.001), p = 0.02]. In this study we found evidence of leniency bias that resulted in two thirds of students being rated above expected level of performance. This leniency bias appeared to be attenuated by delay in ITER completion, and was also blunted in preceptors who rated more students. As all biases threaten the internal validity of the assessment process, further research is needed to confirm these and other sources of rater bias in ITER ratings, and to explore ways of limiting their impact.

Time Biases in laser ranging measurements; impacts on geodetic products (Reference Frame and Orbitography)

NASA Astrophysics Data System (ADS)

Belli, A.; Exertier, P.; Lemoine, F. G.; Chinn, D. S.; Zelensky, N. P.

2017-12-01

The GGOS objectives are to maintain a geodetic network with an accuracy of 1 mm and a stability of 0.1 mm per year. For years, the laser ranging technique, which provide very accurate absolute distances to geodetic targets enable to determine the scale factor as well as coordinates of the geocenter. In order to achieve this goal, systematic errors appearing in the laser ranging measurements must be considered and solved. In addition to Range Bias (RB), which is the primary source of uncertainty of the technique, Time Bias (TB) has been recently detected by using the Time Transfer by Laser Link (T2L2) space instrument capability on-board the satellite Jason-2. Instead of determining TB through the precise orbit determination that is applied to commonly used geodetic targets like LAGEOS to estimate global geodetic products, we have developed, independently, a dedicated method to transfer time between remote satellite laser ranging stations. As a result, the evolving clock phase shift to UTC of around 30 stations has been determined under the form of time series of time bias per station from 2008 to 2016 with an accuracy of 3-4 ns. It demonstrated the difficulty, in terms of Time & Frequency used technologies, to locally maintain accuracy and long term stability at least in the range of 100 ns that is the current requirement for time measurements (UTC) for the laser ranging technique. Because some laser ranging stations oftently exceed this limit (from 100 ns to a few μs) we have been studying these effects first on the precision orbit determination itself, second on the station positioning. We discuss the impact of TB on LAGEOS and Jason-2 orbits, which appears to affect the along-track component essentially. We also investigate the role of TB in global geodetic parameters as the station coordinates. Finally, we propose to provide the community with time series of time bias of laser ranging stations, under the form of a data- handling-file in order to be included in each orbit determination process that is using laser ranging data since 2008.

Pollen reconstructions, tree-rings and early climate data from Minnesota, USA: a cautionary tale of bias and signal attentuation

NASA Astrophysics Data System (ADS)

St-Jacques, J. M.; Cumming, B. F.; Smol, J. P.; Sauchyn, D.

2015-12-01

High-resolution proxy reconstructions are essential to assess the rate and magnitude of anthropogenic global warming. High-resolution pollen records are being critically examined for the production of accurate climate reconstructions of the last millennium, often as extensions of tree-ring records. Past climate inference from a sedimentary pollen record depends upon the stationarity of the pollen-climate relationship. However, humans have directly altered vegetation, and hence modern pollen deposition is a product of landscape disturbance and climate, unlike in the past with its dominance of climate-derived processes. This could cause serious bias in pollen reconstructions. In the US Midwest, direct human impacts have greatly altered the vegetation and pollen rain since Euro-American settlement in the mid-19th century. Using instrumental climate data from the early 1800s from Fort Snelling (Minnesota), we assessed the bias from the conventional method of inferring climate from pollen assemblages in comparison to a calibration set from pre-settlement pollen assemblages and the earliest instrumental climate data. The pre-settlement calibration set provides more accurate reconstructions of 19th century temperature than the modern set does. When both calibration sets are used to reconstruct temperatures since AD 1116 from a varve-dated pollen record from Lake Mina, Minnesota, the conventional method produces significant low-frequency (centennial-scale) signal attenuation and positive bias of 0.8-1.7 oC, resulting in an overestimation of Little Ice Age temperature and an underestimation of anthropogenic warming. We also compared the pollen-inferred moisture reconstruction to a four-century tree-ring-inferred moisture record from Minnesota and Dakotas, which shows that the tree-ring reconstruction is biased towards dry conditions and records wet periods relatively poorly, giving a false impression of regional aridity. The tree-ring chronology also suggests varve chronology problems. It remains to be explored how widespread this landscape disturbance problem is when conventional pollen-based inference methods are used, and consequently how seriously regional manifestations of global warming might have been underestimated with traditional pollen-based techniques.

Downwelling Longwave Fluxes at Continental Surfaces-A Comparison of Observations with GCM Simulations and Implications for the Global Land-Surface Radiation Budget.

NASA Astrophysics Data System (ADS)

Garratt, J. R.; Prata, A. J.

1996-03-01

Previous work suggests that general circulation (global climate) models have excess net radiation at land surfaces, apparently due to overestimates in downwelling shortwave flux and underestimates in upwelling long-wave flux. Part of this excess, however, may be compensated for by an underestimate in downwelling longwave flux. Long term observations of the downwelling longwave component at several land stations in Europe, the United States, Australia, and Antarctica suggest that climate models (four are used, as in previous studies) underestimate this flux component on an annual basis by up to 10 W m2, yet with low statistical significance. It is probable that the known underestimate in boundary-layer air temperature contributes to this, as would low model cloudiness and neglect of minor gases such as methane, nitrogen oxide, and the freons. The bias in downwelling longwave flux, together with those found earlier for downwelling shortwave and upwlling long-wave fluxes, are consistent with the model bias found previously for net radiation. All annually averaged fluxes and biases are deduced for global land as a whole.

Fabricated World Class: Global University League Tables, Status Differentiation and Myths of Global Competition

ERIC Educational Resources Information Center

David, Matthew

2016-01-01

UK media coverage of global university league tables shows systematic bias towards the Russell Group, although also highlighting tensions within its membership. Coverage positions UK "elite" institutions between US superiority and Asian ascent. Coverage claims that league table results warrant UK university funding reform. However,…

Ocean Carbon States: Data Mining in Observations and Numerical Simulations Results

NASA Astrophysics Data System (ADS)

Latto, R.; Romanou, A.

2017-12-01

Advanced data mining techniques are rapidly becoming widely used in Climate and Earth Sciences with the purpose of extracting new meaningful information from increasingly larger and more complex datasets. This is particularly important in studies of the global carbon cycle, where any lack of understanding of its combined physical and biogeochemical drivers is detrimental to our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major carbon reservoirs. The analysis presented here evaluates the use of cluster analysis as a means of identifying and comparing spatial and temporal patterns extracted from observational and model datasets. As the observational data is organized into various regimes, which we will call "ocean carbon states", we gain insight into the physical and/or biogeochemical processes controlling the ocean carbon cycle as well as how well these processes are simulated by a state-of-the-art climate model. We find that cluster analysis effectively produces realistic, dynamic regimes that can be associated with specific processes at different temporal scales for both observations and the model. In addition, we show how these regimes can be used to illustrate and characterize the model biases in the model air-sea flux of CO2. These biases are attributed to biases in salinity, sea surface temperature, wind speed, and nitrate, which are then used to identify the physical processes that are inaccurately reproduced by the model. In this presentation, we provide a proof-of-concept application using simple datasets, and we expand to more complex ones, using several physical and biogeochemical variable pairs, thus providing considerable insight into the mechanisms and phases of the ocean carbon cycle over different temporal and spatial scales.

GPS receiver CODE bias estimation: A comparison of two methods

NASA Astrophysics Data System (ADS)

McCaffrey, Anthony M.; Jayachandran, P. T.; Themens, D. R.; Langley, R. B.

2017-04-01

The Global Positioning System (GPS) is a valuable tool in the measurement and monitoring of ionospheric total electron content (TEC). To obtain accurate GPS-derived TEC, satellite and receiver hardware biases, known as differential code biases (DCBs), must be estimated and removed. The Center for Orbit Determination in Europe (CODE) provides monthly averages of receiver DCBs for a significant number of stations in the International Global Navigation Satellite Systems Service (IGS) network. A comparison of the monthly receiver DCBs provided by CODE with DCBs estimated using the minimization of standard deviations (MSD) method on both daily and monthly time intervals, is presented. Calibrated TEC obtained using CODE-derived DCBs, is accurate to within 0.74 TEC units (TECU) in differenced slant TEC (sTEC), while calibrated sTEC using MSD-derived DCBs results in an accuracy of 1.48 TECU.

Tropospheric carbon monoxide over the Pacific during HIPPO: two-way coupled simulation of GEOS-Chem and its multiple nested models

NASA Astrophysics Data System (ADS)

Yan, Y.-Y.; Lin, J.-T.; Kuang, Y.; Yang, D.; Zhang, L.

2014-12-01

Global chemical transport models (CTMs) are used extensively to study air pollution and transport at a global scale. These models are limited by coarse horizontal resolutions that do not allow for a detailed representation of small-scale nonlinear processes over the pollutant source regions. Here we couple the global GEOS-Chem CTM and its three high-resolution nested models to simulate the tropospheric carbon monoxide (CO) over the Pacific Ocean during five High-performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) campaigns between 2009 and 2011. We develop a two-way coupler, the PeKing University CouPLer (PKUCPL), allowing for the exchange and interaction of chemical constituents between the global model (at 2.5° long. × 2° lat.) and the three nested models (at 0.667° long. × 0.5° lat.) covering Asia, North America, and Europe. The coupler obtains nested model results to modify the global model simulation within the respective nested domains, and simultaneously acquires global model results to provide lateral boundary conditions (LBCs) for the nested models. Compared to the global model alone, the two-way coupled simulation results in enhanced CO concentrations in the nested domains. Sensitivity tests suggest the enhancement to be a result of improved representation of the spatial distributions of CO, nitrogen oxides, and non-methane volatile organic compounds, the meteorological dependence of natural emissions, and other resolution-dependent processes. The relatively long lifetime of CO allows for the enhancement to be accumulated and carried across the globe. We found that the two-way coupled simulation increased the global tropospheric mean CO concentrations in 2009 by 10.4%, with a greater enhancement at 13.3% in the Northern Hemisphere. Coincidently, the global tropospheric mean hydroxyl radical (OH) was reduced by 4.2%, resulting in a 4.2% enhancement in the methyl chloroform lifetime (MCF; via reaction with tropospheric OH). The resulting CO and OH contents and MCF lifetime are closer to observation-based estimates. Both the global and the two-way coupled models capture the general spatiotemporal patterns of HIPPO CO over the Pacific. The two-way coupled simulation is much closer to HIPPO CO, with a mean bias of 1.1 ppb (1.4%) below 9 km compared to the bias at -7.2 ppb (-9.2%) for the global model alone. The improvement is most apparent over the North Pacific. Our test simulations show that the global model alone could resemble the two-way coupled simulation (especially below 4 km) by increasing its global CO emissions by 15% for HIPPO-1 and HIPPO-3, by 25% for HIPPO-2 and HIPPO-4, and by 35% for HIPPO-5. This has important implications for using the global model alone to constrain CO emissions. Thus, the two-way coupled simulation is a significantly improved model tool for studying the global impacts of air pollutants from major anthropogenic source regions.

Signal analysis and radioholographic methods for airborne radio occultations

NASA Astrophysics Data System (ADS)

Wang, Kuo-Nung

Global Positioning System (GPS) radio occultation (RO) is an atmospheric sounding technique utilizing the change in propagation direction and delay of the GPS signal to measure refractivity, which provides information on temperature and humidity. The GPS-RO technique is now operational on several Low Earth Orbiting (LEO) satellite missions. Nevertheless, when observing localized transient events, such as tropical storms, current LEO satellite systems cannot provide sufficiently high temporal and spatial resolution soundings. An airborne RO (ARO) system has therefore been developed for localized GPS-RO campaigns. The open-loop (OL) tracking in post-processing is used to cross-correlates the received Global Navigation Satellite System (GNSS) signal with an internally generated local carrier signal predicted from a Doppler model and extract the atmospheric refractivity information. OL tracking also allows robust processing of rising GPS signals using backward tracking, which will double the observed occultation event numbers. RO signals in the lower troposphere are adversely affected by rapid phase accelerations and severe signal power fading, however. The negative bias caused by low signal-to-noise ratio (SNR) and multipath ray propagation limits the depth of tracking in the atmosphere. Therefore, we developed a model relating the SNR to the variance in the residual phase of the observed signal produced from OL tracking, and its applicability to airborne data is demonstrated. We then apply this model to set a threshold on refractivity retrieval, based upon the cumulative unwrapping error bias, to determine the altitude limit for reliable signal tracking. To enhance the SNR and decrease the unwrapping error rate, the CIRA-Q climatological model and signal residual phase pre-filtering are utilized to process the ARO residual phase. This more accurately modeled phase and less noisy received signal are shown to greatly reduce the bias caused by unwrapping error at lower altitude. On the other hand, to process the superimposed signal in the lower troposphere with its highly variable moisture distribution, Radio-Holographic (RH) methods such as Phase Matching (PM) have been adapted for ARO platforms to untangle the bending angle of each signal path. Under the assumption of spherically symmetric atmosphere, ARO PM can identify different subsignals using the Method of the Stationary Phase (MSP) and determine the arrival angle for each impact parameter. As a result, each subsignal can be distinguished and its corresponding bending angle can be retrieved without producing a negative bias. The refractivity retrieval results using ARO PM are compared to those using the traditional Geometrical Optics (GO) method. The improvements are shown and discussed in the dissertation. We applied these new methods to the received ARO data collected by the GNSS instrument system for multistatic and occultation sensing (GISMOS) in the 2010 PREDepression Investigation of Cloud systems (PREDICT) campaign. A data set of 5 research flights with 57 occultation events during the formation stage of the Hurricane Karl are processed and analyzed. In this research, the refractivity fractional difference with ERA-I model can be maintained at an average 2% above a height of 2km with a climatological model and ARO PM. Compared to the traditional geometrical optics (GO) method without climatological method assistance, the new ARO processing can effectively decrease the refractivity negative bias and significantly improve the retrieval depth of ARO.

A leftward bias however you look at it: Revisiting the emotional chimeric face task as a tool for measuring emotion lateralization.

PubMed

R Innes, Bobby; Burt, D Michael; Birch, Yan K; Hausmann, Markus

2015-12-28

Left hemiface biases observed within the Emotional Chimeric Face Task (ECFT) support emotional face perception models whereby all expressions are preferentially processed by the right hemisphere. However, previous research using this task has not considered that the visible midline between hemifaces might engage atypical facial emotion processing strategies in upright or inverted conditions, nor controlled for left visual field (thus right hemispheric) visuospatial attention biases. This study used novel emotional chimeric faces (blended at the midline) to examine laterality biases for all basic emotions. Left hemiface biases were demonstrated across all emotional expressions and were reduced, but not reversed, for inverted faces. The ECFT bias in upright faces was significantly increased in participants with a large attention bias. These results support the theory that left hemiface biases reflect a genuine bias in emotional face processing, and this bias can interact with attention processes similarly localized in the right hemisphere.

Towards process-informed bias correction of climate change simulations

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Shepherd, Theodore G.; Widmann, Martin; Zappa, Giuseppe; Walton, Daniel; Gutiérrez, José M.; Hagemann, Stefan; Richter, Ingo; Soares, Pedro M. M.; Hall, Alex; Mearns, Linda O.

2017-11-01

Biases in climate model simulations introduce biases in subsequent impact simulations. Therefore, bias correction methods are operationally used to post-process regional climate projections. However, many problems have been identified, and some researchers question the very basis of the approach. Here we demonstrate that a typical cross-validation is unable to identify improper use of bias correction. Several examples show the limited ability of bias correction to correct and to downscale variability, and demonstrate that bias correction can cause implausible climate change signals. Bias correction cannot overcome major model errors, and naive application might result in ill-informed adaptation decisions. We conclude with a list of recommendations and suggestions for future research to reduce, post-process, and cope with climate model biases.

Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety.

PubMed

Seshia, Shashi S; Bryan Young, G; Makhinson, Michael; Smith, Preston A; Stobart, Kent; Croskerry, Pat

2018-02-01

Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care-related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive-affective biases plus cascade could advance the understanding of cognitive-affective processes that underlie decisions and organizational cultures across the continuum of care. Thematic analysis, qualitative information from several sources being used to support argumentation. Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive-affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive-affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive-affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error-provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error-provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive-affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. The concept is abstract, the model is virtual, and the best supportive evidence is qualitative and indirect. The proposed model may help enhance rational decision making across the continuum of care, thereby improving patient safety globally. © 2017 The Authors. Journal of Evaluation in Clinical Practice published by John Wiley & Sons, Ltd.

Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety

PubMed Central

Bryan Young, G.; Makhinson, Michael; Smith, Preston A.; Stobart, Kent; Croskerry, Pat

2017-01-01

Abstract Introduction Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care–related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. Hypothesis A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive‐affective biases plus cascade could advance the understanding of cognitive‐affective processes that underlie decisions and organizational cultures across the continuum of care. Methods Thematic analysis, qualitative information from several sources being used to support argumentation. Discussion Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive‐affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive‐affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive‐affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error‐provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error‐provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive‐affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. Limitations The concept is abstract, the model is virtual, and the best supportive evidence is qualitative and indirect. Conclusions The proposed model may help enhance rational decision making across the continuum of care, thereby improving patient safety globally. PMID:29168290

Evaluation of the Reanalysis Surface Incident Shortwave Radiation Products from NCEP, ECMWF, GSFC, and JMA using Satellite and Surface Observations

NASA Astrophysics Data System (ADS)

Zhang, X.; Liang, S.; Wang, G.; Yao, Y.; Jiang, B.; Cheng, J.

2016-12-01

Solar radiation incident at the Earth's surface (Rs) is an essential component of the total energy exchange between the atmosphere and the surface. Reanalysis data have been widely used, but a comprehensive validation using surface measurements is still highly needed. In this study, we evaluated the Rs estimates from six current representative global reanalyses [NCEP-NCAR, NCEP-DOE; CFSR; ERA-Interim; MERRA; and JRA-55] using surface measurements from different observation networks [GEBA; BSRN; GC-NET; Buoy; and CMA] (674 sites in total) and the Earth's Radiant Energy System (CERES) EBAF product from 2001 to 2009. The global mean biases between the reanalysis Rs and surface measurements at all sites ranged from 11.25 W/m2 to 49.80 W/m2. Comparing with the CERES-EBAF Rs product, all the reanalyses overestimate Rs, except for ERA-Interim, with the biases ranging from -2.98 W/m2 to 21.97 W/m2 over the globe. It was also found that the biases of cloud fraction (CF) in the reanalyses caused the overestimation of Rs. After removing the averaged bias of CERES-EBAF, weighted by the area of the latitudinal band, a global annual mean Rs values of 184.6 W/m2, 180.0 W/m2, and 182.9 W/m2 was obtained over land, ocean, and the globe, respectively.

Assessment of the Jason-2 Extension to the TOPEX/Poseidon, Jason-l Sea-Surface Height Time Series for Global Mean Sea Level Monitoring

NASA Technical Reports Server (NTRS)

Beckley, B. D.; Zelensky, N. P.; Holmes, S. A.; Lemoine, F. G.; Ray, R. D.; Mitchum, G. T.; Dedai, S. D.; Brown, S. T.

2010-01-01

The Jason-2 (OSTM) follow-on mission to Jason-I provides for the continuation of global and regional mean sea level estimates along the ground-track of the initial phase of the TOPEX/Poseidon mission. During the first several months, Jason-I and Jason-2 flew in formation separated by only 55 seconds, enabling the isolation of intermission instrument biases through direct collinear differencing of near simultaneous observations. The Jason-2 Ku-band range bias with respect to Jason-I is estimated to be -84 +/- 9 mm, based on the orbit altitudes provided on the Geophysical Data Records. Modest improved agreement is achieved with the GSFC replacement orbits, which further enables the isolation of subtle 1 cm) instrument-dependent range correction biases. Inter-mission bias estimates are confirmed with an independent assessment from comparisons to a 64-station tide-gauge network, also providing an estimate of the stability of the 17-year time series to be less than 0.1 mm/yr +/- 0.4 mm/yr. The global mean sea level derived from the multi-mission altimeter sea-surface height record from January 1993 through September 2009 is 3.3 +/- 0.4 mm/yr. Recent trends over the period from 2004 through 2008 are smaller and estimated to be 2.0 +/- 0.4 mm/yr.

Unconscious gender bias in fame judgments?

PubMed

Buchner, A; Wippich, W

1996-01-01

In two experiments the conditions of, and the processes leading to, gender biases in fame judgments were investigated. In Experiment 1, the gender bias was not reduced in a condition that alerted participants to the gender of the names. In Experiment 2, participants' sex-role orientation, but not their gender, was related to the gender bias. The process dissociation procedure was used in both experiments in an attempt to separate conscious and unconscious memory processes contributing to the gender bias. Using L.L. Jacoby's 1991) original measurement model there appeared to be evidence for unconscious influences on the gender bias in fame judgments. Unfortunately, this evidence disappeared when a model was used that takes guessing and, hence, response biases into account, which confirms that measurement models that ignore response biases in the process dissociation procedure may lead to erroneous conclusions.

Entrofy: Participant Selection Made Easy

NASA Astrophysics Data System (ADS)

Huppenkothen, Daniela

2016-03-01

Selection participants for a workshop out of a much larger applicant pool can be a difficult task, especially when the goal is diversifying over a range of criteria (e.g. academic seniority, research field, skill levels, gender etc). In this talk I am presenting our tool, Entrofy, aimed at aiding organizers in this task. Entrofy is an open-source tool using a maximum entropy-based algorithm that aims to select a set of participants out of the applicant pool such that a pre-defined range of criteria are globally maximized. This approach allows for a potentially more transparent and less biased selection process while encouraging organizers to think deeply about the goals and the process of their participant selection.

The climate impacts of absorbing aerosols on and within the Arctic

NASA Astrophysics Data System (ADS)

Rasch, P.; Wang, H.; Ma, P.; Fast, J. D.; Wang, M.; Easter, R. C.; Liu, X.; Qian, Y.; Flanner, M. G.; Ghan, S.; Singh, B.

2011-12-01

Absorbing aerosols are receiving increasing attention as forcing agents in the climate system. By scattering and absorbing light they can reduce planetary albedo, particularly over bright surfaces (clouds, snow and ice). They also act as cloud condensation and/or ice nuclei, influencing the brightness, lifetime and precipitation properties of clouds. Atmospheric stability and primary circulation features respond to the changing vertical and horizontal patterns of heating, cooling, and surface fluxes produced by the aerosols, clouds and surface properties. These changes in meteorology have further impacts on aerosols and clouds producing a complex interplay between transport, forcings, and feedbacks involving absorbing aerosols and climate. The complexity of the processes and the interactions between them make it very challenging to represent aerosols realistically in large scale (global and regional) climate models. Simulations of important features of aerosols still contain easily identifiable biases. I will describe our efforts to identify the processes responsible for some of those biases and the deficiencies in model formulations that impede progress in treating aerosols and understanding their role in polar climate. I plan to summarize some studies performed with the NCAR CESM (global) and WRF-Chem (regional) Community models that examine the simulation sensitivity to treatments of physics, chemistry, and meteorology. Some of these simulations were allowed to evolve freely; others were strongly constrained to agree with observed meteorological fields. We have also altered the formulation of a number of the processes in the model to improve fidelity in the aerosol distributions. The parameterizations used in our global model have also been transferred to the regional model, allowing comparisons to be made between the simpler formulations used in the global model with more elaborate and costly formulations available in the regional model. The regional model can be run at higher resolution in order to explore the resolution dependence of the parameterizations and make comparisons to field experiments more straightforward. Aerosols sources have also been tagged by sector and geographic region to help in attribution and interpretation. The many variations mentioned here help in understanding how aerosols reach the arctic and how they produce changes in radiative forcing and Arctic climate. I will provide a brief overview of these studies, with more detail available in presentations submitted to this session and elsewhere.

Mood-congruent attention and memory bias in dysphoria: Exploring the coherence among information-processing biases.

PubMed

Koster, Ernst H W; De Raedt, Rudi; Leyman, Lemke; De Lissnyder, Evi

2010-03-01

Recent studies indicate that depression is characterized by mood-congruent attention bias at later stages of information-processing. Moreover, depression has been associated with enhanced recall of negative information. The present study tested the coherence between attention and memory bias in dysphoria. Stable dysphoric (n = 41) and non-dysphoric (n = 41) undergraduates first performed a spatial cueing task that included negative, positive, and neutral words. Words were presented for 250 ms under conditions that allowed or prevented elaborate processing. Memory for the words presented in the cueing task was tested using incidental free recall. Dysphoric individuals exhibited an attention bias for negative words in the condition that allowed elaborate processing, with the attention bias for negative words predicting free recall of negative words. Results demonstrate the coherence of attention and memory bias in dysphoric individuals and provide suggestions on the influence of attention bias on further processing of negative material. 2009 Elsevier Ltd. All rights reserved.

Can They See It? The Functional Field of View Is Narrower in Individuals with Autism Spectrum Disorder.

PubMed

Song, Yongning; Hakoda, Yuji; Sanefuji, Wakako; Cheng, Chen

2015-01-01

Although social cognitive deficits have long been thought to underlie the characteristic and pervasive difficulties with social interaction observed in individuals with autism spectrum disorder (ASD), several recent behavioral and neuroimaging studies have indicated that visual perceptual impairments might also play a role. People with ASD show a robust bias towards detailed information at the expense of global information, although the mechanisms that underlie this phenomenon remain elusive. To address this issue, we investigated the functional field of view in a group of high-functioning children with autism (n = 13) and a paired non-ASD group (n = 13). Our results indicate that the ability to correctly detect and identify stimuli sharply decreases with greater eccentricity from the fovea in people with ASD. Accordingly, a probe analysis revealed that the functional field of view in the ASD group was only about 6.62° of retinal eccentricity, compared with 8.57° in typically developing children. Thus, children with ASD appear to have a narrower functional field of view. These results challenge the conventional hypothesis that the deficit in global processing in individuals with ASD is solely due to weak central coherence. Alternatively, our data suggest that a narrower functional field of view may also contribute to this bias.

Attention, interpretation, and memory biases in subclinical depression: a proof-of-principle test of the combined cognitive biases hypothesis.

PubMed

Everaert, Jonas; Duyck, Wouter; Koster, Ernst H W

2014-04-01

Emotional biases in attention, interpretation, and memory are viewed as important cognitive processes underlying symptoms of depression. To date, there is a limited understanding of the interplay among these processing biases. This study tested the dependence of memory on depression-related biases in attention and interpretation. Subclinically depressed and nondepressed participants completed a computerized version of the scrambled sentences test (measuring interpretation bias) while their eye movements were recorded (measuring attention bias). This task was followed by an incidental free recall test of previously constructed interpretations (measuring memory bias). Path analysis revealed a good fit for the model in which selective orienting of attention was associated with interpretation bias, which in turn was associated with a congruent bias in memory. Also, a good fit was observed for a path model in which biases in the maintenance of attention and interpretation were associated with memory bias. Both path models attained a superior fit compared with path models without the theorized functional relations among processing biases. These findings enhance understanding of how mechanisms of attention and interpretation regulate what is remembered. As such, they offer support for the combined cognitive biases hypothesis or the notion that emotionally biased cognitive processes are not isolated mechanisms but instead influence each other. Implications for theoretical models and emotion regulation across the spectrum of depressive symptoms are discussed.

Assessment of clear sky radiative fluxes in CMIP5 climate models using surface observations from BSRN

NASA Astrophysics Data System (ADS)

Wild, M.; Hakuba, M. Z.; Folini, D.; Ott, P.; Long, C. N.

2017-12-01

Clear sky fluxes in the latest generation of Global Climate Models (GCM) from CMIP5 still vary largely particularly at the Earth's surface, covering in their global means a range of 16 and 24 Wm-2 in the surface downward clear sky shortwave (SW) and longwave radiation, respectively. We assess these fluxes with monthly clear sky reference climatologies derived from more than 40 Baseline Surface Radiation Network (BSRN) sites based on Long and Ackermann (2000) and Hakuba et al. (2015). The comparison is complicated by the fact that the monthly SW clear sky BSRN reference climatologies are inferred from measurements under true cloud-free conditions, whereas the GCM clear sky fluxes are calculated continuously at every timestep solely by removing the clouds, yet otherwise keeping the prevailing atmospheric composition (e.g. water vapor, temperature, aerosols) during the cloudy conditions. This induces the risk of biases in the GCMs just due to the additional sampling of clear sky fluxes calculated under atmospheric conditions representative for cloudy situations. Thereby, a wet bias may be expected in the GCMs compared to the observational references, which may induce spurious low biases in the downward clear sky SW fluxes. To estimate the magnitude of these spurious biases in the available monthly mean fields from 40 CMIP5 models, we used their respective multi-century control runs, and searched therein for each month and each BSRN station the month with the lowest cloud cover. The deviations of the clear sky fluxes in this month from their long-term means have then be used as indicators of the magnitude of the abovementioned sampling biases and as correction factors for an appropriate comparison with the BSRN climatologies, individually applied for each model and BSRN site. The overall correction is on the order of 2 Wm-2. This revises our best estimate for the global mean surface downward SW clear sky radiation, previously at 249 Wm-2 infered from the GCM clear sky flux fields and their biases compared to the BSRN climatologies, now to 247 Wm-2 including this additional correction. 34 out of 40 CMIP5 GCMs exceed this reference value. With a global mean surface albedo of 13 % and net TOA SW clear sky flux of 287 Wm-2 from CERES-EBAF this results in a global mean clear sky surface and atmospheric SW absorption of 214 and 73 Wm-2, respectively.

Nationalistic vs. Global Education: An Examination of National Bias in the Schools and Its Implications For a Global Society

ERIC Educational Resources Information Center

Nelson, Jack L.

1976-01-01

This article discusses the history of nationalistic education, describes examples of it in Poland, Germany, France, Germany, Russia, and China, and examines selected requirements related to it in the United States. Several approaches for making nationalist education more relevant to a global society are presented. (Author/RM)

Coherence and specificity of information-processing biases in depression and social phobia.

PubMed

Gotlib, Ian H; Kasch, Karen L; Traill, Saskia; Joormann, Jutta; Arnow, Bruce A; Johnson, Sheri L

2004-08-01

Research has not resolved whether depression is associated with a distinct information-processing bias, whether the content of the information-processing bias in depression is specific to themes of loss and sadness, or whether biases are consistent across the tasks most commonly used to assess attention and memory processing. In the present study, participants diagnosed with major depression, social phobia, or no Axis I disorder, completed several information-processing tasks assessing attention and memory for sad, socially threatening, physically threatening, and positive stimuli. As predicted, depressed participants exhibited specific biases for stimuli connoting sadness; social phobic participants did not evidence such specificity for threat stimuli. It is important to note that the different measures of bias in memory and attention were not systematically intercorrelated. Implications for the study of cognitive bias in depression, and for cognitive theory more broadly, are discussed.

Effect of heterogeneousatmospheric CO2 on simulated global carbon budget

USGS Publications Warehouse

Zhang, Zhen; Jiang, Hong; Liu, Jinxun; Ju, Weimin; Zhang, Xiuying

2013-01-01

The effects of rising atmospheric carbon dioxide (CO2) on terrestrial carbon (C) sequestration have been a key focus in global change studies. As anthropological CO2 emissions substantially increase, the spatial variability of atmospheric CO2 should be considered to reduce the potential bias on C source and sink estimations. In this study, the global spatial–temporal patterns of near surface CO2 concentrations for the period 2003-2009 were established using the SCIAMACHY satellite observations and the GLOBALVIEW-CO2 field observations. With this CO2 data and the Integrated Biosphere Simulator (IBIS), our estimation of the global mean annual NPP and NEP was 0.5% and 7% respectively which differs from the traditional C sequestration assessments. The Amazon, Southeast Asia, and Tropical Africa showed higher C sequestration than the traditional assessment, and the rest of the areas around the world showed slightly lower C sequestration than the traditional assessment. We find that the variability of NEP is less intense under heterogeneous CO2 pattern on a global scale. Further studies of the cause of CO2 variation and the interactions between natural and anthropogenic processes of C sequestration are needed.

A New Paradigm for Diagnosing Contributions to Model Aerosol Forcing Error: Diagnosing Model Aerosol Forcing Error

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, A. L.; Feldman, D. R.; Freidenreich, S.

A new paradigm in benchmark absorption-scattering radiative transfer is presented that enables both the globally averaged and spatially resolved testing of climate model radiation parameterizations in order to uncover persistent sources of biases in the aerosol instantaneous radiative effect (IRE). A proof of concept is demonstrated with the Geophysical Fluid Dynamics Laboratory AM4 and Community Earth System Model 1.2.2 climate models. Instead of prescribing atmospheric conditions and aerosols, as in prior intercomparisons, native snapshots of the atmospheric state and aerosol optical properties from the participating models are used as inputs to an accurate radiation solver to uncover model-relevant biases. Thesemore » diagnostic results show that the models' aerosol IRE bias is of the same magnitude as the persistent range cited (~1 W/m 2) and also varies spatially and with intrinsic aerosol optical properties. The findings presented here underscore the significance of native model error analysis and its dispositive ability to diagnose global biases, confirming its fundamental value for the Radiative Forcing Model Intercomparison Project.« less

A New Paradigm for Diagnosing Contributions to Model Aerosol Forcing Error: Diagnosing Model Aerosol Forcing Error

DOE PAGES

Jones, A. L.; Feldman, D. R.; Freidenreich, S.; ...

2017-12-07

A new paradigm in benchmark absorption-scattering radiative transfer is presented that enables both the globally averaged and spatially resolved testing of climate model radiation parameterizations in order to uncover persistent sources of biases in the aerosol instantaneous radiative effect (IRE). A proof of concept is demonstrated with the Geophysical Fluid Dynamics Laboratory AM4 and Community Earth System Model 1.2.2 climate models. Instead of prescribing atmospheric conditions and aerosols, as in prior intercomparisons, native snapshots of the atmospheric state and aerosol optical properties from the participating models are used as inputs to an accurate radiation solver to uncover model-relevant biases. Thesemore » diagnostic results show that the models' aerosol IRE bias is of the same magnitude as the persistent range cited (~1 W/m 2) and also varies spatially and with intrinsic aerosol optical properties. The findings presented here underscore the significance of native model error analysis and its dispositive ability to diagnose global biases, confirming its fundamental value for the Radiative Forcing Model Intercomparison Project.« less

A Projection of Changes in Landfilling Atmospheric River Frequency and Extreme Precipitation over Western North America from the Large Ensemble CESM Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson M.; Leung, Lai-Yung R.; Yoon, Jin-Ho

Simulations from the Community Earth System Model Large Ensemble project are analyzed to investigate the impact of global warming on atmospheric rivers (ARs). The model has notable biases in simulating the subtropical jet position and the relationship between extreme precipitation and moisture transport. After accounting for these biases, the model projects an ensemble mean increase of 35% in the number of landfalling AR days between the last twenty years of the 20th and 21st centuries. However, the number of AR associated extreme precipitation days increases only by 28% because the moisture transport required to produce extreme precipitation also increases withmore » warming. Internal variability introduces an uncertainty of ±8% and ±7% in the projected changes in AR days and associated extreme precipitation days. In contrast, accountings for model biases only change the projected changes by about 1%. The significantly larger mean changes compared to internal variability and to the effects of model biases highlight the robustness of AR responses to global warming.« less

Global budget of tropospheric ozone: Evaluating recent model advances with satellite (OMI), aircraft (IAGOS), and ozonesonde observations

NASA Astrophysics Data System (ADS)

Hu, Lu; Jacob, Daniel J.; Liu, Xiong; Zhang, Yi; Zhang, Lin; Kim, Patrick S.; Sulprizio, Melissa P.; Yantosca, Robert M.

2017-10-01

The global budget of tropospheric ozone is governed by a complicated ensemble of coupled chemical and dynamical processes. Simulation of tropospheric ozone has been a major focus of the GEOS-Chem chemical transport model (CTM) over the past 20 years, and many developments over the years have affected the model representation of the ozone budget. Here we conduct a comprehensive evaluation of the standard version of GEOS-Chem (v10-01) with ozone observations from ozonesondes, the OMI satellite instrument, and MOZAIC-IAGOS commercial aircraft for 2012-2013. Global validation of the OMI 700-400 hPa data with ozonesondes shows that OMI maintained persistent high quality and no significant drift over the 2006-2013 period. GEOS-Chem shows no significant seasonal or latitudinal bias relative to OMI and strong correlations in all seasons on the 2° × 2.5° horizontal scale (r = 0.88-0.95), improving on previous model versions. The most pronounced model bias revealed by ozonesondes and MOZAIC-IAGOS is at high northern latitudes in winter-spring where the model is 10-20 ppbv too low. This appears to be due to insufficient stratosphere-troposphere exchange (STE). Model updates to lightning NOx, Asian anthropogenic emissions, bromine chemistry, isoprene chemistry, and meteorological fields over the past decade have overall led to gradual increase in the simulated global tropospheric ozone burden and more active ozone production and loss. From simulations with different versions of GEOS meteorological fields we find that tropospheric ozone in GEOS-Chem v10-01 has a global production rate of 4960-5530 Tg a-1, lifetime of 20.9-24.2 days, burden of 345-357 Tg, and STE of 325-492 Tg a-1. Change in the intensity of tropical deep convection between these different meteorological fields is a major factor driving differences in the ozone budget.

Understanding the West African monsoon variability and its remote effects: an illustration of the grid point nudging methodology

NASA Astrophysics Data System (ADS)

Bielli, Soline; Douville, Hervé; Pohl, Benjamin

2010-07-01

General circulation models still show deficiencies in simulating the basic features of the West African Monsoon at intraseasonal, seasonal and interannual timescales. It is however, difficult to disentangle the remote versus regional factors that contribute to such deficiencies, and to diagnose their possible consequences for the simulation of the global atmospheric variability. The aim of the present study is to address these questions using the so-called grid point nudging technique, where prognostic atmospheric fields are relaxed either inside or outside the West African Monsoon region toward the ERA40 reanalysis. This regional or quasi-global nudging is tested in ensembles of boreal summer simulations. The impact is evaluated first on the model climatology, then on intraseasonal timescales with an emphasis on North Atlantic/Europe weather regimes, and finally on interannual timescales. Results show that systematic biases in the model climatology over West Africa are mostly of regional origin and have a limited impact outside the domain. A clear impact is found however on the eddy component of the extratropical circulation, in particular over the North Atlantic/European sector. At intraseasonal timescale, the main regional biases also resist to the quasi-global nudging though their magnitude is reduced. Conversely, nudging the model over West Africa exerts a strong impact on the frequency of the two North Atlantic weather regimes that favor the occurrence of heat waves over Europe. Significant impacts are also found at interannual timescale. Not surprisingly, the quasi-global nudging allows the model to capture the variability of large-scale dynamical monsoon indices, but exerts a weaker control on rainfall variability suggesting the additional contribution of regional processes. Conversely, nudging the model toward West Africa suppresses the spurious ENSO teleconnection that is simulated over Europe in the control experiment, thereby emphasizing the relevance of a realistic West African monsoon simulation for seasonal prediction in the extratropics. Further experiments will be devoted to case studies aiming at a better understanding of regional processes governing the monsoon variability and of the possible monsoon teleconnections, especially over Europe.

Long-Term Efficacy of Psychosocial Treatments for Adults With Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Review

PubMed Central

López-Pinar, Carlos; Martínez-Sanchís, Sonia; Carbonell-Vayá, Enrique; Fenollar-Cortés, Javier; Sánchez-Meca, Julio

2018-01-01

Background: Recent evidence suggests that psychosocial treatments, particularly cognitive-behavioral therapy (CBT), are effective interventions for adult attention deficit hyperactivity disorder (ADHD). The objective of this review was to determine the long-term efficacy of psychosocial interventions in improving clinically relevant variables, including ADHD core symptoms, clinical global impression (CGI), and global functioning. Methods: In total, nine randomized controlled trials and three uncontrolled single-group pretest-posttest studies were included. The data from these studies were combined using the inverse variance method. Heterogeneity and risk of bias were assessed. Subgroup analyses and meta-regressions were performed, to determine the influence of different potential moderator variables (risk of bias, medication status, follow-up length, therapy type and setting, and control group type) on effect size (ES) estimates. Results: Up to 680 of a total of 1,073 participants assessed pre-treatment were retained at follow-up. Treatment groups showed greater improvement than control groups in self-reported total ADHD symptoms, inattention, and hyperactivity/impulsivity, in addition to CGI and global functioning. Blind assessors also reported a large ES in within-subject outcomes. Studies using dialectical behavioral therapy (DBT) in a group setting, with active control matching, and that were rated as having an unclear risk of bias, achieved significantly lower ES estimates for most outcomes. Treatment effectiveness, according to the CGI measure, and global functioning were significantly increased when the percentage of medicated participants was greater. Conclusions: Our results indicate that the post-treatment gains reported in previous reviews are sustained for at least 12 months. Nevertheless, these results must be interpreted with caution, because of a high level of heterogeneity among studies and the risk of bias observed in the majority of outcomes. Thus, these findings indicate that psychological interventions are a highly valuable and stable clinical tool for the treatment of core symptoms and global functioning in adults with ADHD. PMID:29780342

Long-Term Efficacy of Psychosocial Treatments for Adults With Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Review.

PubMed

López-Pinar, Carlos; Martínez-Sanchís, Sonia; Carbonell-Vayá, Enrique; Fenollar-Cortés, Javier; Sánchez-Meca, Julio

2018-01-01

Background: Recent evidence suggests that psychosocial treatments, particularly cognitive-behavioral therapy (CBT), are effective interventions for adult attention deficit hyperactivity disorder (ADHD). The objective of this review was to determine the long-term efficacy of psychosocial interventions in improving clinically relevant variables, including ADHD core symptoms, clinical global impression (CGI), and global functioning. Methods: In total, nine randomized controlled trials and three uncontrolled single-group pretest-posttest studies were included. The data from these studies were combined using the inverse variance method. Heterogeneity and risk of bias were assessed. Subgroup analyses and meta-regressions were performed, to determine the influence of different potential moderator variables (risk of bias, medication status, follow-up length, therapy type and setting, and control group type) on effect size (ES) estimates. Results: Up to 680 of a total of 1,073 participants assessed pre-treatment were retained at follow-up. Treatment groups showed greater improvement than control groups in self-reported total ADHD symptoms, inattention, and hyperactivity/impulsivity, in addition to CGI and global functioning. Blind assessors also reported a large ES in within-subject outcomes. Studies using dialectical behavioral therapy (DBT) in a group setting, with active control matching, and that were rated as having an unclear risk of bias, achieved significantly lower ES estimates for most outcomes. Treatment effectiveness, according to the CGI measure, and global functioning were significantly increased when the percentage of medicated participants was greater. Conclusions: Our results indicate that the post-treatment gains reported in previous reviews are sustained for at least 12 months. Nevertheless, these results must be interpreted with caution, because of a high level of heterogeneity among studies and the risk of bias observed in the majority of outcomes. Thus, these findings indicate that psychological interventions are a highly valuable and stable clinical tool for the treatment of core symptoms and global functioning in adults with ADHD.

Investigating Uncertainty in Predicting Carbon Dynamics in North American Biomes: Putting Support-Effect Bias in Perspective

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Brass, Jim (Technical Monitor)

2001-01-01

A fundamental strategy in NASA's Earth Observing System's (EOS) monitoring of vegetation and its contribution to the global carbon cycle is to rely on deterministic, process-based ecosystem models to make predictions of carbon flux over large regions. These models are parameterized (that is, the input variables are derived) using remotely sensed images such as those from the Moderate Resolution Imaging Spectroradiometer (MODIS), ground measurements and interpolated maps. Since early applications of these models, investigators have noted that results depend partly on the spatial support of the input variables. In general, the larger the support of the input data, the greater the chance that the effects of important components of the ecosystem will be averaged out. A review of previous work shows that using large supports can cause either positive or negative bias in carbon flux predictions. To put the magnitude and direction of these biases in perspective, we must quantify the range of uncertainty on our best measurements of carbon-related variables made on equivalent areas. In other words, support-effect bias should be placed in the context of prediction uncertainty from other sources. If the range of uncertainty at the smallest support is less than the support-effect bias, more research emphasis should probably be placed on support sizes that are intermediate between those of field measurements and MODIS. If the uncertainty range at the smallest support is larger than the support-effect bias, the accuracy of MODIS-based predictions will be difficult to quantify and more emphasis should be placed on field-scale characterization and sampling. This talk will describe methods to address these issues using a field measurement campaign in North America and "upscaling" using geostatistical estimation and simulation.

Global Climate Impacts of Fixing the Southern Ocean Shortwave Radiation Bias in the Community Earth System Model (CESM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kay, Jennifer E.; Wall, Casey; Yettella, Vineel

Here, a large, long-standing, and pervasive climate model bias is excessive absorbed shortwave radiation (ASR) over the midlatitude oceans, especially the Southern Ocean. This study investigates both the underlying mechanisms for and climate impacts of this bias within the Community Earth System Model, version 1, with the Community Atmosphere Model, version 5 [CESM1(CAM5)]. Excessive Southern Ocean ASR in CESM1(CAM5) results in part because low-level clouds contain insufficient amounts of supercooled liquid. In a present-day atmosphere-only run, an observationally motivated modification to the shallow convection detrainment increases supercooled cloud liquid, brightens low-level clouds, and substantially reduces the Southern Ocean ASR bias.more » Tuning to maintain global energy balance enables reduction of a compensating tropical ASR bias. In the resulting preindustrial fully coupled run with a brighter Southern Ocean and dimmer tropics, the Southern Ocean cools and the tropics warm. As a result of the enhanced meridional temperature gradient, poleward heat transport increases in both hemispheres (especially the Southern Hemisphere), and the Southern Hemisphere atmospheric jet strengthens. Because northward cross-equatorial heat transport reductions occur primarily in the ocean (80%), not the atmosphere (20%), a proposed atmospheric teleconnection linking Southern Ocean ASR bias reduction and cooling with northward shifts in tropical precipitation has little impact. In summary, observationally motivated supercooled liquid water increases in shallow convective clouds enable large reductions in long-standing climate model shortwave radiation biases. Of relevance to both model bias reduction and climate dynamics, quantifying the influence of Southern Ocean cooling on tropical precipitation requires a model with dynamic ocean heat transport.« less

Global Climate Impacts of Fixing the Southern Ocean Shortwave Radiation Bias in the Community Earth System Model (CESM)

DOE PAGES

Kay, Jennifer E.; Wall, Casey; Yettella, Vineel; ...

2016-06-10

Here, a large, long-standing, and pervasive climate model bias is excessive absorbed shortwave radiation (ASR) over the midlatitude oceans, especially the Southern Ocean. This study investigates both the underlying mechanisms for and climate impacts of this bias within the Community Earth System Model, version 1, with the Community Atmosphere Model, version 5 [CESM1(CAM5)]. Excessive Southern Ocean ASR in CESM1(CAM5) results in part because low-level clouds contain insufficient amounts of supercooled liquid. In a present-day atmosphere-only run, an observationally motivated modification to the shallow convection detrainment increases supercooled cloud liquid, brightens low-level clouds, and substantially reduces the Southern Ocean ASR bias.more » Tuning to maintain global energy balance enables reduction of a compensating tropical ASR bias. In the resulting preindustrial fully coupled run with a brighter Southern Ocean and dimmer tropics, the Southern Ocean cools and the tropics warm. As a result of the enhanced meridional temperature gradient, poleward heat transport increases in both hemispheres (especially the Southern Hemisphere), and the Southern Hemisphere atmospheric jet strengthens. Because northward cross-equatorial heat transport reductions occur primarily in the ocean (80%), not the atmosphere (20%), a proposed atmospheric teleconnection linking Southern Ocean ASR bias reduction and cooling with northward shifts in tropical precipitation has little impact. In summary, observationally motivated supercooled liquid water increases in shallow convective clouds enable large reductions in long-standing climate model shortwave radiation biases. Of relevance to both model bias reduction and climate dynamics, quantifying the influence of Southern Ocean cooling on tropical precipitation requires a model with dynamic ocean heat transport.« less

The development of information processing biases in childhood anxiety: a review and exploration of its origins in parenting.

PubMed

Hadwin, Julie A; Garner, Matthew; Perez-Olivas, Gisela

2006-11-01

The aim of this paper is to explore parenting as one potential route through which information processing biases for threat develop in children. It reviews information processing biases in childhood anxiety in the context of theoretical models and empirical research in the adult anxiety literature. Specifically, it considers how adult models have been used and adapted to develop a theoretical framework with which to investigate information processing biases in children. The paper then considers research which specifically aims to understand the relationship between parenting and the development of information processing biases in children. It concludes that a clearer theoretical framework is required to understand the significance of information biases in childhood anxiety, as well as their origins in parenting.

Calibration results for the GEOS-3 altimeter

NASA Technical Reports Server (NTRS)

Martin, C. F.; Butler, M. L.

1977-01-01

Data from the GEOS-3 altimeter were analyzed, for both the intensive and global modes, to determine the altitude bias levels for each mode and to verify the accuracy of the time tags which have been applied to the data. The best estimates of the biases are -5.30 + or - .2 m (intensive mode) and -3.55 m + or - .4 m (global mode). These values include the approximately 1.6 m offset of the altimeter antenna focal point from the GEOS-3 spacecraft center-of-mass. The negative signs indicate that the measured altitudes are too short. The data is corrected by subtracting the above bias numbers for the respective modes. Timing corrections which should be applied to the altimeter data were calculated theoretically, and subsequently confirmed through crossover analysis for passes 6-8 revolutions apart. The time tag correction that should be applied consists of -20.8 msec + 1 interpulse period (10.240512 msec).

Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0

NASA Astrophysics Data System (ADS)

Fuhrer, Oliver; Chadha, Tarun; Hoefler, Torsten; Kwasniewski, Grzegorz; Lapillonne, Xavier; Leutwyler, David; Lüthi, Daniel; Osuna, Carlos; Schär, Christoph; Schulthess, Thomas C.; Vogt, Hannes

2018-05-01

The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non-hydrostatic climate model for a near-global setup running on the full Piz Daint supercomputer on 4888 GPUs (graphics processing units). The dynamical core of the model has been completely rewritten using a domain-specific language (DSL) for performance portability across different hardware architectures. Physical parameterizations and diagnostics have been ported using compiler directives. To our knowledge this represents the first complete atmospheric model being run entirely on accelerators on this scale. At a grid spacing of 930 m (1.9 km), we achieve a simulation throughput of 0.043 (0.23) simulated years per day and an energy consumption of 596 MWh per simulated year. Furthermore, we propose a new memory usage efficiency (MUE) metric that considers how efficiently the memory bandwidth - the dominant bottleneck of climate codes - is being used.

A meta-analysis of sex differences in human brain structure.

PubMed

Ruigrok, Amber N V; Salimi-Khorshidi, Gholamreza; Lai, Meng-Chuan; Baron-Cohen, Simon; Lombardo, Michael V; Tait, Roger J; Suckling, John

2014-02-01

The prevalence, age of onset, and symptomatology of many neuropsychiatric conditions differ between males and females. To understand the causes and consequences of sex differences it is important to establish where they occur in the human brain. We report the first meta-analysis of typical sex differences on global brain volume, a descriptive account of the breakdown of studies of each compartmental volume by six age categories, and whole-brain voxel-wise meta-analyses on brain volume and density. Gaussian-process regression coordinate-based meta-analysis was used to examine sex differences in voxel-based regional volume and density. On average, males have larger total brain volumes than females. Examination of the breakdown of studies providing total volumes by age categories indicated a bias towards the 18-59 year-old category. Regional sex differences in volume and tissue density include the amygdala, hippocampus and insula, areas known to be implicated in sex-biased neuropsychiatric conditions. Together, these results suggest candidate regions for investigating the asymmetric effect that sex has on the developing brain, and for understanding sex-biased neurological and psychiatric conditions. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Measuring cancer in indigenous populations.

PubMed

Sarfati, Diana; Garvey, Gail; Robson, Bridget; Moore, Suzanne; Cunningham, Ruth; Withrow, Diana; Griffiths, Kalinda; Caron, Nadine R; Bray, Freddie

2018-05-01

It is estimated that there are 370 million indigenous peoples in 90 countries globally. Indigenous peoples generally face substantial disadvantage and poorer health status compared with nonindigenous peoples. Population-level cancer surveillance provides data to set priorities, inform policies, and monitor progress over time. Measuring the cancer burden of vulnerable subpopulations, particularly indigenous peoples, is problematic. There are a number of practical and methodological issues potentially resulting in substantial underestimation of cancer incidence and mortality rates, and biased survival rates, among indigenous peoples. This, in turn, may result in a deprioritization of cancer-related programs and policies among these populations. This commentary describes key issues relating to cancer surveillance among indigenous populations including 1) suboptimal identification of indigenous populations, 2) numerator-denominator bias, 3) problems with data linkage in survival analysis, and 4) statistical analytic considerations. We suggest solutions that can be implemented to strengthen the visibility of indigenous peoples around the world. These include acknowledgment of the central importance of full engagement of indigenous peoples with all data-related processes, encouraging the use of indigenous identifiers in national and regional data sets and mitigation and/or careful assessment of biases inherent in cancer surveillance methods for indigenous peoples. Copyright © 2018 Elsevier Inc. All rights reserved.

Neural Network Technique for Global Ocean Color (Chl-a) Estimates Bridging Multiple Satellite Missions

NASA Astrophysics Data System (ADS)

Garraffo, Z. D.; Nadiga, S.; Krasnopolsky, V.; Mehra, A.; Bayler, E. J.; Kim, H. C.; Behringer, D.

2016-02-01

A Neural Network (NN) technique is used to produce consistent global ocean color estimates, bridging multiple satellite ocean color missions by linking ocean color variability - primarily driven by biological processes - with the physical processes of the upper ocean. Satellite-derived surface variables - sea-surface temperature (SST) and sea-surface height (SSH) fields - are used as signatures of upper-ocean dynamics. The NN technique employs adaptive weights that are tuned by applying statistical learning (training) algorithms to past data sets, providing robustness with respect to random noise, accuracy, fast emulations, and fault-tolerance. This study employs Sea-viewing Wide Field-of-View Sensor (SeaWiFS) chlorophyll-a data for 1998-2010 in conjunction with satellite SSH and SST fields. After interpolating all data sets to the same two-degree latitude-longitude grid, the annual mean was removed and monthly anomalies extracted . The NN technique wass trained for even years of that period and tested for errors and bias for the odd years. The NN output are assessed for: (i) bias, (ii) variability, (iii) root-mean-square error (RMSE), and (iv) cross-correlation. A Jacobian is evaluated to estimate the impact of each input (SSH, SST) on the NN chlorophyll-a estimates. The differences between an ensemble of NNs vs a single NN are examined. After the NN is trained for the SeaWiFS period, the NN is then applied and validated for 2005-2015, a period covered by other satellite missions — the Moderate Resolution Imaging Spectroradiometer (MODIS AQUA) and the Visible Imaging Infrared Radiometer Suite (VIIRS).

The TOMCAT global chemical transport model v1.6: description of chemical mechanism and model evaluation

NASA Astrophysics Data System (ADS)

Monks, Sarah A.; Arnold, Stephen R.; Hollaway, Michael J.; Pope, Richard J.; Wilson, Chris; Feng, Wuhu; Emmerson, Kathryn M.; Kerridge, Brian J.; Latter, Barry L.; Miles, Georgina M.; Siddans, Richard; Chipperfield, Martyn P.

2017-08-01

This paper documents the tropospheric chemical mechanism scheme used in the TOMCAT 3-D chemical transport model. The current scheme includes a more detailed representation of hydrocarbon chemistry than previously included in the model, with the inclusion of the emission and oxidation of ethene, propene, butane, toluene and monoterpenes. The model is evaluated against a range of surface, balloon, aircraft and satellite measurements. The model is generally able to capture the main spatial and seasonal features of high and low concentrations of carbon monoxide (CO), ozone (O3), volatile organic compounds (VOCs) and reactive nitrogen. However, model biases are found in some species, some of which are common to chemistry models and some that are specific to TOMCAT and warrant further investigation. The most notable of these biases are (1) a negative bias in Northern Hemisphere (NH) winter and spring CO and a positive bias in Southern Hemisphere (SH) CO throughout the year, (2) a positive bias in NH O3 in summer and a negative bias at high latitudes during SH winter and (3) a negative bias in NH winter C2 and C3 alkanes and alkenes. TOMCAT global mean tropospheric hydroxyl radical (OH) concentrations are higher than estimates inferred from observations of methyl chloroform but similar to, or lower than, multi-model mean concentrations reported in recent model intercomparison studies. TOMCAT shows peak OH concentrations in the tropical lower troposphere, unlike other models which show peak concentrations in the tropical upper troposphere. This is likely to affect the lifetime and transport of important trace gases and warrants further investigation.

Using GRADE as a framework to guide research on the sexual and reproductive health and rights (SRHR) of women living with HIV - methodological opportunities and challenges.

PubMed

Siegfried, Nandi; Narasimhan, Manjulaa; Kennedy, Caitlin E; Welbourn, Alice; Yuvraj, Anandi

2017-09-01

In March 2016, WHO reviewed evidence to develop global recommendations on the sexual and reproductive health and rights (SRHR) of women living with HIV. Systematic reviews and a global survey of women living with HIV informed the guideline development decision-making process. New recommendations covered abortion, Caesarean section, safe disclosure, and empowerment and self-efficacy interventions. Identification of key research gaps is part of the WHO guidelines development process, but consistent methods to do so are lacking. Our method aimed to ensure consistency and comprised the systematic application of a framework based on GRADE (Grading of Recommendations, Assessment, Development and Evaluation) to the process. The framework incorporates the strength and quality rating of recommendations and the priorities reported by women in the survey to inform research prioritisation. For each gap, we also articulated: (1) the most appropriate and robust study design to answer the question; (2) alternative pragmatic designs if the ideal design is not feasible; and (3) the methodological challenges facing researchers through identifying potential biases. We found 12 research gaps and identified five appropriate study designs to address the related questions: (1) Cross-sectional surveys; (2) Qualitative interview-driven studies; (3) Registries; (4) Randomised controlled trials; and (5) Medical record audit. Methodological challenges included selection, recruitment, misclassification, measurement and contextual biases, and confounding. In conclusion, a framework based on GRADE can provide a systematic approach to identifying research gaps from a WHO guideline. Incorporation of the priorities of women living with HIV into the framework systematically ensures that women living with HIV can shape future policy decisions affecting their lives. Implementation science and participatory research are appropriate over-arching approaches to enhance uptake of interventions and to ensure inclusion of women living with HIV at all stages of the research process.

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

2012-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

Contrast effects on speed perception for linear and radial motion.

PubMed

Champion, Rebecca A; Warren, Paul A

2017-11-01

Speed perception is vital for safe activity in the environment. However, considerable evidence suggests that perceived speed changes as a function of stimulus contrast, with some investigators suggesting that this might have meaningful real-world consequences (e.g. driving in fog). In the present study we investigate whether the neural effects of contrast on speed perception occur at the level of local or global motion processing. To do this we examine both speed discrimination thresholds and contrast-dependent speed perception for two global motion configurations that have matched local spatio-temporal structure. Specifically we compare linear and radial configurations, the latter of which arises very commonly due to self-movement. In experiment 1 the stimuli comprised circular grating patches. In experiment 2, to match stimuli even more closely, motion was presented in multiple local Gabor patches equidistant from central fixation. Each patch contained identical linear motion but the global configuration was either consistent with linear or radial motion. In both experiments 1 and 2, discrimination thresholds and contrast-induced speed biases were similar in linear and radial conditions. These results suggest that contrast-based speed effects occur only at the level of local motion processing, irrespective of global structure. This result is interpreted in the context of previous models of speed perception and evidence suggesting differences in perceived speed of locally matched linear and radial stimuli. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Multi-scale Modeling System: Developments, Applications and Critical Issues

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, Jiundar; Atlas, Robert; Randall, David; Lin, Xin; Khairoutdinov, Marat; Li, Jui-Lin; Waliser, Duane E.; Hou, Arthur; Peters-Lidard, Christa;

Elevation Change of the Southern Greenland Ice Sheet from Satellite Radar Altimeter Data

NASA Technical Reports Server (NTRS)

Haines, Bruce J.

1999-01-01

Long-term changes in the thickness of the polar ice sheets are important indicators of climate change. Understanding the contributions to the global water mass balance from the accumulation or ablation of grounded ice in Greenland and Antarctica is considered crucial for determining the source of the about 2 mm/yr sea-level rise in the last century. Though the Antarctic ice sheet is much larger than its northern counterpart, the Greenland ice sheet is more likely to undergo dramatic changes in response to a warming trend. This can be attributed to the warmer Greenland climate, as well as a potential for amplification of a global warming trend in the polar regions of the Northern Hemisphere. In collaboration with Drs. Curt Davis and Craig Kluever of the University of Missouri, we are using data from satellite radar altimeters to measure changes in the elevation of the Southern Greenland ice sheet from 1978 to the present. Difficulties with systematic altimeter measurement errors, particularly in intersatellite comparisons, beset earlier studies of the Greenland ice sheet thickness. We use altimeter data collected contemporaneously over the global ocean to establish a reference for correcting ice-sheet data. In addition, the waveform data from the ice-sheet radar returns are reprocessed to better determine the range from the satellite to the ice surface. At JPL, we are focusing our efforts principally on the reduction of orbit errors and range biases in the measurement systems on the various altimeter missions. Our approach emphasizes global characterization and reduction of the long-period orbit errors and range biases using altimeter data from NASA's Ocean Pathfinder program. Along-track sea-height residuals are sequentially filtered and backwards smoothed, and the radial orbit errors are modeled as sinusoids with a wavelength equal to one revolution of the satellite. The amplitudes of the sinusoids are treated as exponentially-correlated noise processes with a time-constant of six days. Measurement errors (e.g., altimeter range bias) are simultaneously recovered as constant parameters. The corrections derived from the global ocean analysis are then applied over the Greenland ice sheet. The orbit error and measurement bias corrections for different missions are developed in a single framework to enable robust linkage of ice-sheet measurements from 1978 to the present. In 1998, we completed our re-evaluation of the 1978 Seasat and 1985-1989 Geosat Exact Repeat Mission data. The estimates of ice thickness over Southern Greenland (south of 72N and above 2000 m) from 1978 to 1988 show large regional variations (+/-18 cm/yr), but yield an overall rate of +1.5 +/- 0.5 cm/yr (one standard error). Accounting for systematic errors, the estimate may not be significantly different from the null growth rate. The average elevation change from 1978 to 1988 is too small to assess whether the Greenland ice sheet is undergoing a long-term change.

A Nonlinear Spacecraft Attitude Controller and Observer with an Unknown Constant Gyro Bias and Gyro Noise

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Sanner, Robert M.

2001-01-01

A nonlinear control scheme for attitude control of a spacecraft is combined with a nonlinear gyro bias observer for the case of constant gyro bias, in the presence of gyro noise. The observer bias estimates converge exponentially to a mean square bound determined by the standard deviation of the gyro noise. The resulting coupled, closed loop dynamics are proven to be globally stable, with asymptotic tracking which is also mean square bounded. A simulation of the proposed observer-controller design is given for a rigid spacecraft tracking a specified, time-varying attitude sequence to illustrate the theoretical claims.

On the wintertime low bias of Northern Hemisphere carbon monoxide in global model studies

NASA Astrophysics Data System (ADS)

Stein, O.; Schultz, M. G.; Bouarar, I.; Clark, H.; Huijnen, V.; Gaudel, A.; George, M.; Clerbaux, C.

2014-01-01

The uncertainties in the global budget of carbon monoxide (CO) are assessed to explain causes for the long-standing issue of Northern Hemispheric wintertime underestimation of CO concentrations in global models. With a series of MOZART sensitivity simulations for the year 2008, the impacts from changing a variety of surface sources and sinks were analyzed. The model results were evaluated with monthly averages of surface station observations from the global CO monitoring network as well as with total columns observed from satellites and with vertical profiles from measurements on passenger aircraft. Our basic simulation using MACCity anthropogenic emissions underestimated Northern Hemispheric near-surface CO concentrations on average by more than 20 ppb from December to April with the largest bias over Europe of up to 75 ppb in January. An increase in global biomass burning or biogenic emissions of CO or volatile organic compounds (VOC) is not able to reduce the annual course of the model bias and yields too high concentrations over the Southern Hemisphere. Raising global annual anthropogenic emissions results in overestimations of surface concentrations in most regions all-year-round. Instead, our results indicate that anthropogenic emissions in the MACCity inventory are too low for the industrialized countries during winter and spring. Thus we found it necessary to adjust emissions seasonally with regionally varying scaling factors. Moreover, exchanging the original resistance-type dry deposition scheme with a parameterization for CO uptake by oxidation from soil bacteria and microbes reduced the boreal winter dry deposition fluxes and could partly correct for the model bias. When combining the modified dry deposition scheme with increased wintertime road traffic emissions over Europe and North America (factors up to 4.5 and 2, respectively) we were able to optimize the match to surface observations and to reduce the model bias significantly with respect to the satellite and aircraft observations. A reason for the apparent underestimation of emissions may be an exaggerated downward trend in the RCP8.5 scenario in these regions between 2000 and 2010, as this scenario was used to extrapolate the MACCity emissions from their base year 2000. This factor is potentially amplified by a lack of knowledge about the seasonality of emissions. A methane lifetime of 9.7 yr for our basic model and 9.8 yr for the optimized simulation agrees well with current estimates of global OH, but we cannot exclude a potential effect from errors in the geographical and seasonal distribution of OH concentrations. Finally, underestimated emissions from anthropogenic VOCs can also account for a small part of the missing CO concentrations.

Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

NASA Technical Reports Server (NTRS)

Adler, Robert; Gu, Guojun; Huffman, George

2012-01-01

A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a different number of input products. For the globe the calculated relative error estimate from this study is about 9%, which is also probably a slight overestimate. These tropical and global estimated bias errors provide one estimate of the current state of knowledge of the planet's mean precipitation.

Data assimilation of GNSS zenith total delays from a Nordic processing centre

NASA Astrophysics Data System (ADS)

Lindskog, Magnus; Ridal, Martin; Thorsteinsson, Sigurdur; Ning, Tong

2017-11-01

Atmospheric moisture-related information estimated from Global Navigation Satellite System (GNSS) ground-based receiver stations by the Nordic GNSS Analysis Centre (NGAA) have been used within a state-of-the-art kilometre-scale numerical weather prediction system. Different processing techniques have been implemented to derive the moisture-related GNSS information in the form of zenith total delays (ZTDs) and these are described and compared. In addition full-scale data assimilation and modelling experiments have been carried out to investigate the impact of utilizing moisture-related GNSS data from the NGAA processing centre on a numerical weather prediction (NWP) model initial state and on the ensuing forecast quality. The sensitivity of results to aspects of the data processing, station density, bias-correction and data assimilation have been investigated. Results show benefits to forecast quality when using GNSS ZTD as an additional observation type. The results also show a sensitivity to thinning distance applied for GNSS ZTD observations but not to modifications to the number of predictors used in the variational bias correction applied. In addition, it is demonstrated that the assimilation of GNSS ZTD can benefit from more general data assimilation enhancements and that there is an interaction of GNSS ZTD with other types of observations used in the data assimilation. Future plans include further investigation of optimal thinning distances and application of more advanced data assimilation techniques.

Marginalization: A Revisitation With Integration of Scholarship on Globalization, Intersectionality, Privilege, Microaggressions, and Implicit Biases.

PubMed

Hall, Joanne M; Carlson, Kelly

2016-01-01

In 1994, the concept of marginalization was explored in an article in Advances in Nursing Science. This is a revisitation of the concept incorporating new scholarship. This update is founded on feminism, postcolonialism, critical race theory, and discourse deconstruction, all viewpoints that have been explicated in nursing. The purpose of this analysis is to look at new scholarship and concepts useful to applying marginalization in nursing knowledge development from the standpoint of Bourdieu's macro, meso, and micro levels. New scholarship includes globalization, intersectionality, privilege, microaggressions, and implicit bias. Implications for decreasing health disparities through this new scholarship are discussed.

Evaluation of energy fluxes in the NCEP climate forecast system version 2.0 (CFSv2)

NASA Astrophysics Data System (ADS)

Rai, Archana; Saha, Subodh Kumar

2018-01-01

The energy fluxes at the surface and top of the atmosphere (TOA) from a long free run by the NCEP climate forecast system version 2.0 (CFSv2) are validated against several observation and reanalysis datasets. This study focuses on the annual mean energy fluxes and tries to link it with the systematic cold biases in the 2 m air temperature, particularly over the land regions. The imbalance in the long term mean global averaged energy fluxes are also evaluated. The global averaged imbalance at the surface and at the TOA is found to be 0.37 and 6.43 Wm-2, respectively. It is shown that CFSv2 overestimates the land surface albedo, particularly over the snow region, which in turn contributes to the cold biases in 2 m air temperature. On the other hand, surface albedo is highly underestimated over the coastal region around Antarctica and that may have contributed to the warm bias over that oceanic region. This study highlights the need for improvements in the parameterization of snow/sea-ice albedo scheme for a realistic simulation of surface temperature and that may have implications on the global energy imbalance in the model.

Sensitivity of Hydrologic Response to Climate Model Debiasing Procedures

NASA Astrophysics Data System (ADS)

Channell, K.; Gronewold, A.; Rood, R. B.; Xiao, C.; Lofgren, B. M.; Hunter, T.

2017-12-01

Climate change is already having a profound impact on the global hydrologic cycle. In the Laurentian Great Lakes, changes in long-term evaporation and precipitation can lead to rapid water level fluctuations in the lakes, as evidenced by unprecedented change in water levels seen in the last two decades. These fluctuations often have an adverse impact on the region's human, environmental, and economic well-being, making accurate long-term water level projections invaluable to regional water resources management planning. Here we use hydrological components from a downscaled climate model (GFDL-CM3/WRF), to obtain future water supplies for the Great Lakes. We then apply a suite of bias correction procedures before propagating these water supplies through a routing model to produce lake water levels. Results using conventional bias correction methods suggest that water levels will decline by several feet in the coming century. However, methods that reflect the seasonal water cycle and explicitly debias individual hydrological components (overlake precipitation, overlake evaporation, runoff) imply that future water levels may be closer to their historical average. This discrepancy between debiased results indicates that water level forecasts are highly influenced by the bias correction method, a source of sensitivity that is commonly overlooked. Debiasing, however, does not remedy misrepresentation of the underlying physical processes in the climate model that produce these biases and contribute uncertainty to the hydrological projections. This uncertainty coupled with the differences in water level forecasts from varying bias correction methods are important for water management and long term planning in the Great Lakes region.

Collaborative Project: The problem of bias in defining uncertainty in computationally enabled strategies for data-driven climate model development. Final Technical Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huerta, Gabriel

The objective of the project is to develop strategies for better representing scientific sensibilities within statistical measures of model skill that then can be used within a Bayesian statistical framework for data-driven climate model development and improved measures of model scientific uncertainty. One of the thorny issues in model evaluation is quantifying the effect of biases on climate projections. While any bias is not desirable, only those biases that affect feedbacks affect scatter in climate projections. The effort at the University of Texas is to analyze previously calculated ensembles of CAM3.1 with perturbed parameters to discover how biases affect projectionsmore » of global warming. The hypothesis is that compensating errors in the control model can be identified by their effect on a combination of processes and that developing metrics that are sensitive to dependencies among state variables would provide a way to select version of climate models that may reduce scatter in climate projections. Gabriel Huerta at the University of New Mexico is responsible for developing statistical methods for evaluating these field dependencies. The UT effort will incorporate these developments into MECS, which is a set of python scripts being developed at the University of Texas for managing the workflow associated with data-driven climate model development over HPC resources. This report reflects the main activities at the University of New Mexico where the PI (Huerta) and the Postdocs (Nosedal, Hattab and Karki) worked on the project.« less

Weight Bias in Schools and How Physical Educators Can Assist in Its Demise

ERIC Educational Resources Information Center

Ehlert, Chris; Marston, Rip; Fontana, Fabio; Waldron, Jennifer

2015-01-01

One of the unfortunate side effects of the current global obesity pandemic is an increasing anti-fat bias toward overweight and obese individuals. The teaching profession is not immune from having its members included in the ranks of those possessing negative stereotypes associated with overweight or obese individuals. We provide the reader with a…

The CAMS interim Reanalysis of Carbon Monoxide, Ozone and Aerosol for 2003-2015

NASA Astrophysics Data System (ADS)

Flemming, Johannes; Benedetti, Angela; Inness, Antje; Engelen, Richard J.; Jones, Luke; Huijnen, Vincent; Remy, Samuel; Parrington, Mark; Suttie, Martin; Bozzo, Alessio; Peuch, Vincent-Henri; Akritidis, Dimitris; Katragkou, Eleni

2017-02-01

A new global reanalysis data set of atmospheric composition (AC) for the period 2003-2015 has been produced by the Copernicus Atmosphere Monitoring Service (CAMS). Satellite observations of total column (TC) carbon monoxide (CO) and aerosol optical depth (AOD), as well as several TC and profile observations of ozone, have been assimilated with the Integrated Forecasting System for Composition (C-IFS) of the European Centre for Medium-Range Weather Forecasting. Compared to the previous Monitoring Atmospheric Composition and Climate (MACC) reanalysis (MACCRA), the new CAMS interim reanalysis (CAMSiRA) is of a coarser horizontal resolution of about 110 km, compared to 80 km, but covers a longer period with the intent to be continued to present day. This paper compares CAMSiRA with MACCRA and a control run experiment (CR) without assimilation of AC retrievals. CAMSiRA has smaller biases than the CR with respect to independent observations of CO, AOD and stratospheric ozone. However, ozone at the surface could not be improved by the assimilation because of the strong impact of surface processes such as dry deposition and titration with nitrogen monoxide (NO), which were both unchanged by the assimilation. The assimilation of AOD led to a global reduction of sea salt and desert dust as well as an exaggerated increase in sulfate. Compared to MACCRA, CAMSiRA had smaller biases for AOD, surface CO and TC ozone as well as for upper stratospheric and tropospheric ozone. Finally, the temporal consistency of CAMSiRA was better than the one of MACCRA. This was achieved by using a revised emission data set as well as by applying careful selection and bias correction to the assimilated retrievals. CAMSiRA is therefore better suited than MACCRA for the study of interannual variability, as demonstrated for trends in surface CO.

Quantifying the clear-sky bias of satellite-derived infrared LST

NASA Astrophysics Data System (ADS)

Ermida, S. L.; Trigo, I. F.; DaCamara, C.

2017-12-01

Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Gao, Chujie

2018-02-01

This study assesses the performance of 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of rainfall over East Africa (EA) against reanalyzed datasets during 1951-2005. The datasets were sourced from Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU). The metrics used to rank CMIP5 Global Circulation Models (GCMs) based on their performance in reproducing the observed rainfall include correlation coefficient, standard deviation, bias, percentage bias, root mean square error, and trend. Performances of individual models vary widely. The overall performance of the models over EA is generally low. The models reproduce the observed bimodal rainfall over EA. However, majority of them overestimate and underestimate the October-December (OND) and March-May (MAM) rainfall, respectively. The monthly (inter-annual) correlation between model and reanalyzed is high (low). More than a third of the models show a positive bias of the annual rainfall. High standard deviation in rainfall is recorded in the Lake Victoria Basin, central Kenya, and eastern Tanzania. A number of models reproduce the spatial standard deviation of rainfall during MAM season as compared to OND. The top eight models that produce rainfall over EA relatively well are as follows: CanESM2, CESM1-CAM5, CMCC-CESM, CNRM-CM5, CSIRO-Mk3-6-0, EC-EARTH, INMCM4, and MICROC5. Although these results form a fairly good basis for selection of GCMs for carrying out climate projections and downscaling over EA, it is evident that there is still need for critical improvement in rainfall-related processes in the models assessed. Therefore, climate users are advised to use the projections of rainfall from CMIP5 models over EA cautiously when making decisions on adaptation to or mitigation of climate change.

Atlas-based analysis of cardiac shape and function: correction of regional shape bias due to imaging protocol for population studies.

PubMed

Medrano-Gracia, Pau; Cowan, Brett R; Bluemke, David A; Finn, J Paul; Kadish, Alan H; Lee, Daniel C; Lima, Joao A C; Suinesiaputra, Avan; Young, Alistair A

2013-09-13

Cardiovascular imaging studies generate a wealth of data which is typically used only for individual study endpoints. By pooling data from multiple sources, quantitative comparisons can be made of regional wall motion abnormalities between different cohorts, enabling reuse of valuable data. Atlas-based analysis provides precise quantification of shape and motion differences between disease groups and normal subjects. However, subtle shape differences may arise due to differences in imaging protocol between studies. A mathematical model describing regional wall motion and shape was used to establish a coordinate system registered to the cardiac anatomy. The atlas was applied to data contributed to the Cardiac Atlas Project from two independent studies which used different imaging protocols: steady state free precession (SSFP) and gradient recalled echo (GRE) cardiovascular magnetic resonance (CMR). Shape bias due to imaging protocol was corrected using an atlas-based transformation which was generated from a set of 46 volunteers who were imaged with both protocols. Shape bias between GRE and SSFP was regionally variable, and was effectively removed using the atlas-based transformation. Global mass and volume bias was also corrected by this method. Regional shape differences between cohorts were more statistically significant after removing regional artifacts due to imaging protocol bias. Bias arising from imaging protocol can be both global and regional in nature, and is effectively corrected using an atlas-based transformation, enabling direct comparison of regional wall motion abnormalities between cohorts acquired in separate studies.

The Effect of an Increased Convective Entrainment Rate on Indian Monsoon Biases in the Met Office Unified Model

NASA Astrophysics Data System (ADS)

Bush, Stephanie; Turner, Andrew; Woolnough, Steve; Martin, Gill

2013-04-01

Global circulation models (GCMs) are a key tool for understanding and predicting monsoon rainfall, now and under future climate change. However, many GCMs show significant, systematic biases in their simulation of monsoon rainfall and dynamics that spin up over very short time scales and persist in the climate mean state. We describe several of these biases as simulated in the Met Office Unified Model and show they are sensitive to changes in the convective parameterization's entrainment rate. To improve our understanding of the biases and inform efforts to improve convective parameterizations, we explore the reasons for this sensitivity. We show the results of experiments where we increase the entrainment rate in regions of especially large bias: the western equatorial Indian Ocean, western north Pacific and India itself. We use the results to determine whether improvements in biases are due to the local increase in entrainment or are the remote response of the entrainment increase elsewhere in the GCM. We find that feedbacks usually strengthen the local response, but the local response leads to a different mean state change in different regions. We also show results from experiments which demonstrate the spin-up of the local response, which we use to further understand the response in complex regions such as the Western North Pacific. Our work demonstrates that local application of parameterization changes is a powerful tool for understanding their global impact.

Efficient global biopolymer sampling with end-transfer configurational bias Monte Carlo

NASA Astrophysics Data System (ADS)

Arya, Gaurav; Schlick, Tamar

2007-01-01

We develop an "end-transfer configurational bias Monte Carlo" method for efficient thermodynamic sampling of complex biopolymers and assess its performance on a mesoscale model of chromatin (oligonucleosome) at different salt conditions compared to other Monte Carlo moves. Our method extends traditional configurational bias by deleting a repeating motif (monomer) from one end of the biopolymer and regrowing it at the opposite end using the standard Rosenbluth scheme. The method's sampling efficiency compared to local moves, pivot rotations, and standard configurational bias is assessed by parameters relating to translational, rotational, and internal degrees of freedom of the oligonucleosome. Our results show that the end-transfer method is superior in sampling every degree of freedom of the oligonucleosomes over other methods at high salt concentrations (weak electrostatics) but worse than the pivot rotations in terms of sampling internal and rotational sampling at low-to-moderate salt concentrations (strong electrostatics). Under all conditions investigated, however, the end-transfer method is several orders of magnitude more efficient than the standard configurational bias approach. This is because the characteristic sampling time of the innermost oligonucleosome motif scales quadratically with the length of the oligonucleosomes for the end-transfer method while it scales exponentially for the traditional configurational-bias method. Thus, the method we propose can significantly improve performance for global biomolecular applications, especially in condensed systems with weak nonbonded interactions and may be combined with local enhancements to improve local sampling.

Climate Impacts of CALIPSO-Guided Corrections to Black Carbon Aerosol Vertical Distributions in a Global Climate Model

NASA Astrophysics Data System (ADS)

Kovilakam, Mahesh; Mahajan, Salil; Saravanan, R.; Chang, Ping

2017-10-01

We alleviate the bias in the tropospheric vertical distribution of black carbon aerosols (BC) in the Community Atmosphere Model (CAM4) using the Cloud-Aerosol and Infrared Pathfinder Satellite Observations (CALIPSO)-derived vertical profiles. A suite of sensitivity experiments are conducted with 1x, 5x, and 10x the present-day model estimated BC concentration climatology, with (corrected, CC) and without (uncorrected, UC) CALIPSO-corrected BC vertical distribution. The globally averaged top of the atmosphere radiative flux perturbation of CC experiments is ˜8-50% smaller compared to uncorrected (UC) BC experiments largely due to an increase in low-level clouds. The global average surface temperature increases, the global average precipitation decreases, and the ITCZ moves northward with the increase in BC radiative forcing, irrespective of the vertical distribution of BC. Further, tropical expansion metrics for the poleward extent of the Northern Hemisphere Hadley cell (HC) indicate that simulated HC expansion is not sensitive to existing model biases in BC vertical distribution.

MERIT DEM: A new high-accuracy global digital elevation model and its merit to global hydrodynamic modeling

NASA Astrophysics Data System (ADS)

Yamazaki, D.; Ikeshima, D.; Neal, J. C.; O'Loughlin, F.; Sampson, C. C.; Kanae, S.; Bates, P. D.

2017-12-01

Digital Elevation Models (DEM) are fundamental data for flood modelling. While precise airborne DEMs are available in developed regions, most parts of the world rely on spaceborne DEMs which include non-negligible height errors. Here we show the most accurate global DEM to date at 90m resolution by eliminating major error components from the SRTM and AW3D DEMs. Using multiple satellite data and multiple filtering techniques, we addressed absolute bias, stripe noise, speckle noise and tree height bias from spaceborne DEMs. After the error removal, significant improvements were found in flat regions where height errors were larger than topography variability, and landscapes features such as river networks and hill-valley structures became clearly represented. We found the topography slope of the previous DEMs was largely distorted in most of world major floodplains (e.g. Ganges, Nile, Niger, Mekong) and swamp forests (e.g. Amazon, Congo, Vasyugan). The developed DEM will largely reduce the uncertainty in both global and regional flood modelling.

Passive Microwave Rainfall Estimates from the GPM Mission

NASA Astrophysics Data System (ADS)

Kummerow, Christian; Petkovic, Veljko

2017-04-01

The Global Precipitation Measurement (GPM) mission was launched in February 2014 as a joint mission between JAXA from Japan and NASA from the United States. GPM carries a state of the art dual-frequency precipitation radar and a multi-channel passive microwave radiometer that acts not only to enhance the radar's retrieval capability, but also as a reference for a constellation of existing satellites carrying passive microwave sensors. In March of 2016, GPM released Version 4 of its precipitation products that consists of radar, radiometer, and combined radar/radiometer products. The precipitation products from these sensors or sensor combination are consistent by design and show relatively minor differences in the mean global sense. Closer examination of the biases, however, reveals regional biases between active and passive sensors that can be directly related top the nature of the convection. By looking at cloud systems instead of individual satellite pixels, the relationship between biases and the large scale environmental state become obvious. Organized convection, which occurs more readily in regimes with large Convective Available Potential Energy (CAPE) and shear tend to drive biases in different directions than isolated convection. This is true over both land and ocean. This talk will present the latest findings and explore these discrepancies from a physical perspective in order to gain some understanding between cloud structures, information content, and retrieval differences. This analysis will be used to then drive a bigger picture of how GPM's latest results inform the Global Water and Energy budgets.

The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements

NASA Astrophysics Data System (ADS)

Lucas, S. E.; Todd, J. F.

2015-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). The CVP Program currently supports multiple projects in areas that are aimed at improved representation of physical processes in global models. Some of the topics that are currently funded include: i) Improved Understanding of Intraseasonal Tropical Variability - DYNAMO field campaign and post -field projects, and the new climate model improvement teams focused on MJO processes; ii) Climate Process Teams (CPTs, co-funded with NSF) with projects focused on Cloud macrophysical parameterization and its application to aerosol indirect effects, and Internal-Wave Driven Mixing in Global Ocean Models; iii) Improved Understanding of Tropical Pacific Processes, Biases, and Climatology; iv) Understanding Arctic Sea Ice Mechanism and Predictability;v) AMOC Mechanisms and Decadal Predictability Recent results from CVP-funded projects will be summarized. Additional information can be found at http://cpo.noaa.gov/CVP.

Cognitive and neural mechanisms of decision biases in recognition memory.

PubMed

Windmann, Sabine; Urbach, Thomas P; Kutas, Marta

2002-08-01

In recognition memory tasks, stimuli can be classified as "old" either on the basis of accurate memory or a bias to respond "old", yet bias has received little attention in the cognitive neuroscience literature. Here we examined the pattern and timing of bias-related effects in event-related brain potentials (ERPs) to determine whether the bias is linked more to memory retrieval or to response verification processes. Participants were divided into a High Bias and a Low Bias group according to their bias to respond "old". These groups did not differ in recognition accuracy or in the ERP pattern to items that actually were old versus new (Objective Old/New Effect). However, when the old/new distinction was based on each subject's perspective, i.e. when items judged "old" were compared with those judged "new" (Subjective Old/New Effect), significant group differences were observed over prefrontal sites with a timing (300-500 ms poststimulus) more consistent with bias acting early on memory retrieval processes than on post-retrieval response verification processes. In the standard old/new effect (Hits vs Correct Rejections), these group differences were intermediate to those for the Objective and the Subjective comparisons, indicating that such comparisons are confounded by response bias. We propose that these biases are top-down controlled processes mediated by prefrontal cortex areas.

Tree demography dominates long-term growth trends inferred from tree rings.

PubMed

Brienen, Roel J W; Gloor, Manuel; Ziv, Guy

2017-02-01

Understanding responses of forests to increasing CO 2 and temperature is an important challenge, but no easy task. Tree rings are increasingly used to study such responses. In a recent study, van der Sleen et al. (2014) Nature Geoscience, 8, 4 used tree rings from 12 tropical tree species and find that despite increases in intrinsic water use efficiency, no growth stimulation is observed. This challenges the idea that increasing CO 2 would stimulate growth. Unfortunately, tree ring analysis can be plagued by biases, resulting in spurious growth trends. While their study evaluated several biases, it does not account for all. In particular, one bias may have seriously affected their results. Several of the species have recruitment patterns, which are not uniform, but clustered around one specific year. This results in spurious negative growth trends if growth rates are calculated in fixed size classes, as 'fast-growing' trees reach the sampling diameter earlier compared to slow growers and thus fast growth rates tend to have earlier calendar dates. We assessed the effect of this 'nonuniform age bias' on observed growth trends and find that van der Sleen's conclusions of a lack of growth stimulation do not hold. Growth trends are - at least partially - driven by underlying recruitment or age distributions. Species with more clustered age distributions show more negative growth trends, and simulations to estimate the effect of species' age distributions show growth trends close to those observed. Re-evaluation of the growth data and correction for the bias result in significant positive growth trends of 1-2% per decade for the full period, and 3-7% since 1950. These observations, however, should be taken cautiously as multiple biases affect these trend estimates. In all, our results highlight that tree ring studies of long-term growth trends can be strongly influenced by biases if demographic processes are not carefully accounted for. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

The Presentation Location of the Reference Stimuli Affects the Left-Side Bias in the Processing of Faces and Chinese Characters

PubMed Central

Li, Chenglin; Cao, Xiaohua

2017-01-01

For faces and Chinese characters, a left-side processing bias, in which observers rely more heavily on information conveyed by the left side of stimuli than the right side of stimuli, has been frequently reported in previous studies. However, it remains unclear whether this left-side bias effect is modulated by the reference stimuli's location. The present study adopted the chimeric stimuli task to investigate the influence of the presentation location of the reference stimuli on the left-side bias in face and Chinese character processing. The results demonstrated that when a reference face was presented in the left visual field of its chimeric images, which are centrally presented, the participants showed a preference higher than the no-bias threshold for the left chimeric face; this effect, however, was not observed in the right visual field. This finding indicates that the left-side bias effect in face processing is stronger when the reference face is in the left visual field. In contrast, the left-side bias was observed in Chinese character processing when the reference Chinese character was presented in either the left or right visual field. Together, these findings suggest that although faces and Chinese characters both have a left-side processing bias, the underlying neural mechanisms of this left-side bias might be different. PMID:29018391

The Presentation Location of the Reference Stimuli Affects the Left-Side Bias in the Processing of Faces and Chinese Characters.

PubMed

Li, Chenglin; Cao, Xiaohua

2017-01-01

For faces and Chinese characters, a left-side processing bias, in which observers rely more heavily on information conveyed by the left side of stimuli than the right side of stimuli, has been frequently reported in previous studies. However, it remains unclear whether this left-side bias effect is modulated by the reference stimuli's location. The present study adopted the chimeric stimuli task to investigate the influence of the presentation location of the reference stimuli on the left-side bias in face and Chinese character processing. The results demonstrated that when a reference face was presented in the left visual field of its chimeric images, which are centrally presented, the participants showed a preference higher than the no-bias threshold for the left chimeric face; this effect, however, was not observed in the right visual field. This finding indicates that the left-side bias effect in face processing is stronger when the reference face is in the left visual field. In contrast, the left-side bias was observed in Chinese character processing when the reference Chinese character was presented in either the left or right visual field. Together, these findings suggest that although faces and Chinese characters both have a left-side processing bias, the underlying neural mechanisms of this left-side bias might be different.

Terrestrial nitrogen cycling in Earth system models revisited

USGS Publications Warehouse

Stocker, Benjamin D; Prentice, I. Colin; Cornell, Sarah; Davies-Barnard, T; Finzi, Adrien; Franklin, Oskar; Janssens, Ivan; Larmola, Tuula; Manzoni, Stefano; Näsholm, Torgny; Raven, John; Rebel, Karin; Reed, Sasha C.; Vicca, Sara; Wiltshire, Andy; Zaehle, Sönke

2016-01-01

Understanding the degree to which nitrogen (N) availability limits land carbon (C) uptake under global environmental change represents an unresolved challenge. First-generation ‘C-only’vegetation models, lacking explicit representations of N cycling,projected a substantial and increasing land C sink under rising atmospheric CO2 concentrations. This prediction was questioned for not taking into account the potentially limiting effect of N availability, which is necessary for plant growth (Hungate et al.,2003). More recent global models include coupled C and N cycles in land ecosystems (C–N models) and are widely assumed to be more realistic. However, inclusion of more processes has not consistently improved their performance in capturing observed responses of the global C cycle (e.g. Wenzel et al., 2014). With the advent of a new generation of global models, including coupled C, N, and phosphorus (P) cycling, model complexity is sure to increase; but model reliability may not, unless greater attention is paid to the correspondence of model process representations ande mpirical evidence. It was in this context that the ‘Nitrogen Cycle Workshop’ at Dartington Hall, Devon, UK was held on 1–5 February 2016. Organized by I. Colin Prentice and Benjamin D. Stocker (Imperial College London, UK), the workshop was funded by the European Research Council,project ‘Earth system Model Bias Reduction and assessing Abrupt Climate change’ (EMBRACE). We gathered empirical ecologists and ecosystem modellers to identify key uncertainties in terrestrial C–N cycling, and to discuss processes that are missing or poorly represented in current models.

Perceptual Biases in Processing Facial Identity and Emotion

ERIC Educational Resources Information Center

Coolican, Jamesie; Eskes, Gail A.; McMullen, Patricia A.; Lecky, Erin

2008-01-01

Normal observers demonstrate a bias to process the left sides of faces during perceptual judgments about identity or emotion. This effect suggests a right cerebral hemisphere processing bias. To test the role of the right hemisphere and the involvement of configural processing underlying this effect, young and older control observers and patients…

The source of the truth bias: Heuristic processing?

PubMed

Street, Chris N H; Masip, Jaume

2015-06-01

People believe others are telling the truth more often than they actually are; this is called the truth bias. Surprisingly, when a speaker is judged at multiple points across their statement the truth bias declines. Previous claims argue this is evidence of a shift from (biased) heuristic processing to (reasoned) analytical processing. In four experiments we contrast the heuristic-analytic model (HAM) with alternative accounts. In Experiment 1, the decrease in truth responding was not the result of speakers appearing more deceptive, but was instead attributable to the rater's processing style. Yet contrary to HAMs, across three experiments we found the decline in bias was not related to the amount of processing time available (Experiments 1-3) or the communication channel (Experiment 2). In Experiment 4 we found support for a new account: that the bias reflects whether raters perceive the statement to be internally consistent. © 2015 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Analysis of Soot Propensity in Combustion Processes Using Optical Sensors and Video Magnification.

PubMed

Garcés, Hugo O; Fuentes, Andrés; Reszka, Pedro; Carvajal, Gonzalo

2018-05-11

Industrial combustion processes are an important source of particulate matter, causing significant pollution problems that affect human health, and are a major contributor to global warming. The most common method for analyzing the soot emission propensity in flames is the Smoke Point Height (SPH) analysis, which relates the fuel flow rate to a critical flame height at which soot particles begin to leave the reactive zone through the tip of the flame. The SPH and is marked by morphological changes on the flame tip. SPH analysis is normally done through flame observations with the naked eye, leading to high bias. Other techniques are more accurate, but are not practical to implement in industrial settings, such as the Line Of Sight Attenuation (LOSA), which obtains soot volume fractions within the flame from the attenuation of a laser beam. We propose the use of Video Magnification techniques to detect the flame morphological changes and thus determine the SPH minimizing observation bias. We have applied for the first time Eulerian Video Magnification (EVM) and Phase-based Video Magnification (PVM) on an ethylene laminar diffusion flame. The results were compared with LOSA measurements, and indicate that EVM is the most accurate method for SPH determination.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson M.; Feng, Zhe; Burleyson, Casey D.

Regional cloud permitting model simulations of cloud populations observed during the 2011 ARM Madden Julian Oscillation Investigation Experiment/ Dynamics of Madden-Julian Experiment (AMIE/DYNAMO) field campaign are evaluated against radar and ship-based measurements. Sensitivity of model simulated surface rain rate statistics to parameters and parameterization of hydrometeor sizes in five commonly used WRF microphysics schemes are examined. It is shown that at 2 km grid spacing, the model generally overestimates rain rate from large and deep convective cores. Sensitivity runs involving variation of parameters that affect rain drop or ice particle size distribution (more aggressive break-up process etc) generally reduce themore » bias in rain-rate and boundary layer temperature statistics as the smaller particles become more vulnerable to evaporation. Furthermore significant improvement in the convective rain-rate statistics is observed when the horizontal grid-spacing is reduced to 1 km and 0.5 km, while it is worsened when run at 4 km grid spacing as increased turbulence enhances evaporation. The results suggest modulation of evaporation processes, through parameterization of turbulent mixing and break-up of hydrometeors may provide a potential avenue for correcting cloud statistics and associated boundary layer temperature biases in regional and global cloud permitting model simulations.« less

Long-Term Quantitative Precipitation Estimates (QPE) at High Spatial and Temporal Resolution over CONUS: Bias-Adjustment of the Radar-Only National Mosaic and Multi-sensor QPE (NMQ/Q2) Precipitation Reanalysis (2001-2012)

NASA Astrophysics Data System (ADS)

Prat, Olivier; Nelson, Brian; Stevens, Scott; Seo, Dong-Jun; Kim, Beomgeun

2015-04-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is completed for the period covering from 2001 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Several in-situ datasets are available to assess the biases of the radar-only product and to adjust for those biases to provide a multi-sensor QPE. The rain gauge networks that are used such as the Global Historical Climatology Network-Daily (GHCN-D), the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), and the Climate Reference Network (CRN), have different spatial density and temporal resolution. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. The objective of this work is threefold. First, we investigate how the different in-situ networks can impact the precipitation estimates as a function of the spatial density, sensor type, and temporal resolution. Second, we assess conditional and un-conditional biases of the radar-only QPE for various time scales (daily, hourly, 5-min) using in-situ precipitation observations. Finally, after assessing the bias and applying reduction or elimination techniques, we are using a unique in-situ dataset merging the different RG networks (CRN, ASOS, HADS, GHCN-D) to adjust the radar-only QPE product via an Inverse Distance Weighting (IDW) approach. In addition, we also investigate alternate adjustment techniques such as the kriging method and its variants (Simple Kriging: SK; Ordinary Kriging: OK; Conditional Bias-Penalized Kriging: CBPK). From this approach, we also hope to generate estimates of uncertainty for the gridded bias-adjusted QPE. Further comparison with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) is also provided in order to give a detailed picture of the improvements and remaining challenges.

Evaluation of the MACC operational forecast system - potential and challenges of global near-real-time modelling with respect to reactive gases in the troposphere

NASA Astrophysics Data System (ADS)

Wagner, A.; Blechschmidt, A.-M.; Bouarar, I.; Brunke, E.-G.; Clerbaux, C.; Cupeiro, M.; Cristofanelli, P.; Eskes, H.; Flemming, J.; Flentje, H.; George, M.; Gilge, S.; Hilboll, A.; Inness, A.; Kapsomenakis, J.; Richter, A.; Ries, L.; Spangl, W.; Stein, O.; Weller, R.; Zerefos, C.

2015-12-01

The Monitoring Atmospheric Composition and Climate (MACC) project represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu/), which became fully operational during 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5-day forecasts of atmospheric composition fields. It is the only assimilation system worldwide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases covering the period between 2009 and 2012. A validation was performed based on carbon monoxide (CO), nitrogen dioxide (NO2) and ozone (O3) surface observations from the Global Atmosphere Watch (GAW) network, the O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and, furthermore, NO2 tropospheric columns, as well as CO total columns, derived from satellite sensors. The MACC system proved capable of reproducing reactive gas concentrations with consistent quality; however, with a seasonally dependent bias compared to surface and satellite observations - for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the year, with monthly modified normalised mean biases (MNMBs) ranging between -30 and 30 % at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterisation. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at their highest level, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range from values between -110 and 40 % for NO2 and at most -20 % for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterisation and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

The influence of anticipatory processing on attentional biases in social anxiety.

PubMed

Mills, Adam C; Grant, DeMond M; Judah, Matt R; White, Evan J

2014-09-01

Research on cognitive theories of social anxiety disorder (SAD) has identified individual processes that influence this condition (e.g., cognitive biases, repetitive negative thinking), but few studies have attempted to examine the interaction between these processes. For example, attentional biases and anticipatory processing are theoretically related and have been found to influence symptoms of SAD, but they rarely have been studied together (i.e., Clark & Wells, 1995). Therefore, the goal of the current study was to examine the effect of anticipatory processing on attentional bias for internal (i.e., heart rate feedback) and external (i.e., emotional faces) threat information. A sample of 59 participants high (HSA) and low (LSA) in social anxiety symptoms engaged in a modified dot-probe task prior to (Time 1) and after (Time 2) an anticipatory processing or distraction task. HSAs who anticipated experienced an increase in attentional bias for internal information from Time 1 to Time 2, whereas HSAs in the distraction condition and LSAs in either condition experienced no changes. No changes in biases were found for HSAs for external biases, but LSAs who engaged in the distraction task became less avoidant of emotional faces from Time 1 to Time 2. This suggests that anticipatory processing results in an activation of attentional biases for physiological information as suggested by Clark and Wells. Copyright © 2014. Published by Elsevier Ltd.

Malodorous volatile organic sulfur compounds: Sources, sinks and significance in inland waters.

PubMed

Watson, Susan B; Jüttner, Friedrich

2017-03-01

Volatile Organic Sulfur Compounds (VOSCs) are instrumental in global S-cycling and greenhouse gas production. VOSCs occur across a diversity of inland waters, and with widespread eutrophication and climate change, are increasingly linked with malodours in organic-rich waterbodies and drinking-water supplies. Compared with marine systems, the role of VOSCs in biogeochemical processes is far less well characterized for inland waters, and often involves different physicochemical and biological processes. This review provides an updated synthesis of VOSCs in inland waters, focusing on compounds known to cause malodours. We examine the major limnological and biochemical processes involved in the formation and degradation of alkylthiols, dialkylsulfides, dialkylpolysulfides, and other organosulfur compounds under different oxygen, salinity and mixing regimes, and key phototropic and heterotrophic microbial producers and degraders (bacteria, cyanobacteria, and algae) in these environs. The data show VOSC levels which vary significantly, sometimes far exceeding human odor thresholds, generated by a diversity of biota, biochemical pathways, enzymes and precursors. We also draw attention to major issues in sampling and analytical artifacts which bias and preclude comparisons among studies, and highlight significant knowledge gaps that need addressing with careful, appropriate methods to provide a more robust understanding of the potential effects of continued global development.

Estimation of the electromagnetic bias from retracked TOPEX data

NASA Technical Reports Server (NTRS)

Rodriguez, Ernesto; Martin, Jan M.

1994-01-01

We examine the electromagnetic (EM) bias by using retracked TOPEX altimeter data. In contrast to previous studies, we use a parameterization of the EM bias which does not make stringent assumptions about the form of the correction or its global behavior. We find that the most effective single parameter correction uses the altimeter-estimated wind speed but that other parameterizations, using a wave age related parameter of significant wave height, may also significantly reduce the repeat pass variance. The different corrections are compared, and their improvement of the TOPEX height variance is quantified.

Anxiety-linked attentional bias and its modification: Illustrating the importance of distinguishing processes and procedures in experimental psychopathology research.

PubMed

MacLeod, Colin; Grafton, Ben

2016-11-01

In this review of research concerning anxiety-linked attentional bias, we seek to illustrate a general principle that we contend applies across the breadth of experimental psychopathology. Specifically, we highlight how maintenance of a clear distinction between process and procedure serves to enhance the advancement of knowledge and understanding, while failure to maintain this distinction can foster confusion and misconception. We show how such clear differentiation has permitted the continuous refinement of assessment procedures, in ways that have led to growing confidence in the existence of the putative attentional bias process of interest, and also increasing understanding of its nature. In contrast, we show how a failure to consistently differentiate between process and procedure has contributed to confusion concerning whether or not attentional bias modification reliably alters anxiety vulnerability and dysfunction. As we demonstrate, such confusion can be avoided by distinguishing the process of attentional bias modification from the procedures that have been employed with the intention of evoking this target process. Such an approach reveals that procedures adopted with the intention of eliciting the attentional bias modification process do not always do so, but that successful evocation of the attentional bias modification process quite reliably alters anxiety symptomatology. We consider some of the specific implications for future research concerning attentional bias modification, while also pointing to the broader implications for experimental psychopathology research in general. Copyright © 2016 Elsevier Ltd. All rights reserved.

Taxonomic bias in biodiversity data and societal preferences.

PubMed

Troudet, Julien; Grandcolas, Philippe; Blin, Amandine; Vignes-Lebbe, Régine; Legendre, Frédéric

2017-08-22

Studying and protecting each and every living species on Earth is a major challenge of the 21 st century. Yet, most species remain unknown or unstudied, while others attract most of the public, scientific and government attention. Although known to be detrimental, this taxonomic bias continues to be pervasive in the scientific literature, but is still poorly studied and understood. Here, we used 626 million occurrences from the Global Biodiversity Information Facility (GBIF), the biggest biodiversity data portal, to characterize the taxonomic bias in biodiversity data. We also investigated how societal preferences and taxonomic research relate to biodiversity data gathering. For each species belonging to 24 taxonomic classes, we used the number of publications from Web of Science and the number of web pages from Bing searches to approximate research activity and societal preferences. Our results show that societal preferences, rather than research activity, strongly correlate with taxonomic bias, which lead us to assert that scientists should advertise less charismatic species and develop societal initiatives (e.g. citizen science) that specifically target neglected organisms. Ensuring that biodiversity is representatively sampled while this is still possible is an urgent prerequisite for achieving efficient conservation plans and a global understanding of our surrounding environment.

Evaluating the need for integrated land use and land cover analysis for robust assessment of climate adaptation and mitigation strategies

NASA Astrophysics Data System (ADS)

Di Vittorio, Alan; Mao, Jiafu; Shi, Xiaoying

2016-04-01

Several climate adaptation and mitigation strategies incorporate land use and land cover change to address global carbon balance and also food, fuel, fiber, and water resource sustainability. However, Land Use and Land Cover Change (LULCC) are not consistent across the CMIP5 model simulations because only the land use input was harmonized. Differences in LULCC impede understanding of global change because such differences can dramatically alter land-atmosphere mass and energy exchange in response to differences in associated use and distribution of land resources. For example, the Community Earth System Model (CESM) overestimates 2005 atmospheric CO2 concentration by 18 ppmv, and we explore the contribution of historical LULCC to this bias in relation to the effects of CO2 fertilization and nitrogen deposition on terrestrial carbon. Using identical land use input, a chronologically referenced LULCC that accounts for pasture, as opposed to the default year-2000 referenced LULCC, increases this bias to 27 ppmv because more forest needs to be cleared for land use. Assuming maximum forest retention for all land conversion reduces the new bias to ~21 ppmv, while minimum forest retention increases the new bias to ~32 ppmv. Corresponding ecosystem carbon changes from the default in 2005 are approximately -28 PgC, -10 PgC, and -43 PgC, respectively. This 33 PgC uncertainty range due to maximizing versus minimizing forest area is 66% of the estimated 50 PgC gain in ecosystem carbon due to CO2 fertilization from 1850-2005, and 150% of the estimated 22 PgC gain due to nitrogen deposition. This range is also similar to the 28 PgC difference generated by changing the LULCC reference year and accounting for pasture. These results indicate that LULCC uncertainty is not only a major driver of bias in simulated atmospheric CO2, but that it could contribute even more to this bias than uncertainty in CO2 fertilization or nitrogen deposition. This highlights the need for more accurate LULCC scenarios in earth system simulations to provide robust historical and future projections of carbon and climate, especially when incorporating climate feedbacks on human and environmental systems. More accurate LULCC scenarios will also improve impact and resource sustainability analyses in the context of climate adaptation and mitigation strategies. These new scenarios will need to be developed and implemented as an integrated process with interdependent land use and land cover to adequately incorporate human and environmental drivers of LULCC.

Smokers exhibit biased neural processing of smoking and affective images.

PubMed

Oliver, Jason A; Jentink, Kade G; Drobes, David J; Evans, David E

2016-08-01

There has been growing interest in the role that implicit processing of drug cues can play in motivating drug use behavior. However, the extent to which drug cue processing biases relate to the processing biases exhibited to other types of evocative stimuli is largely unknown. The goal of the present study was to determine how the implicit cognitive processing of smoking cues relates to the processing of affective cues using a novel paradigm. Smokers (n = 50) and nonsmokers (n = 38) completed a picture-viewing task, in which participants were presented with a series of smoking, pleasant, unpleasant, and neutral images while engaging in a distractor task designed to direct controlled resources away from conscious processing of image content. Electroencephalogram recordings were obtained throughout the task for extraction of event-related potentials (ERPs). Smokers exhibited differential processing of smoking cues across 3 different ERP indices compared with nonsmokers. Comparable effects were found for pleasant cues on 2 of these indices. Late cognitive processing of smoking and pleasant cues was associated with nicotine dependence and cigarette use. Results suggest that cognitive biases may extend across classes of stimuli among smokers. This raises important questions about the fundamental meaning of cognitive biases, and suggests the need to consider generalized cognitive biases in theories of drug use behavior and interventions based on cognitive bias modification. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Validation of the Land-Surface Energy Budget and Planetary Boundary Layer for Several Intensive field Experiments

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Schubert, Siegfried; Molod, Andrea; Houser, Paul R.

1999-01-01

Land-surface processes in a data assimilation system influence the lower troposphere and must be properly represented. With the recent incorporation of the Mosaic Land-surface Model (LSM) into the GEOS Data Assimilation System (DAS), the detailed land-surface processes require strict validation. While global data sources can identify large-scale systematic biases at the monthly timescale, the diurnal cycle is difficult to validate. Moreover, global data sets rarely include variables such as evaporation, sensible heat and soil water. Intensive field experiments, on the other hand, can provide high temporal resolution energy budget and vertical profile data for sufficiently long periods, without global coverage. Here, we evaluate the GEOS DAS against several intensive field experiments. The field experiments are First ISLSCP Field Experiment (FIFE, Kansas, summer 1987), Cabauw (as used in PILPS, Netherlands, summer 1987), Atmospheric Radiation Measurement (ARM, Southern Great Plains, winter and summer 1998) and the Surface Heat Budget of the Arctic Ocean (SHEBA, Arctic ice sheet, winter and summer 1998). The sites provide complete surface energy budget data for periods of at least one year, and some periods of vertical profiles. This comparison provides a detailed validation of the Mosaic LSM within the GEOS DAS for a variety of climatologic and geographic conditions.

Using temporal ICA to selectively remove global noise while preserving global signal in functional MRI data.

PubMed

Glasser, Matthew F; Coalson, Timothy S; Bijsterbosch, Janine D; Harrison, Samuel J; Harms, Michael P; Anticevic, Alan; Van Essen, David C; Smith, Stephen M

2018-06-02

Temporal fluctuations in functional Magnetic Resonance Imaging (fMRI) have been profitably used to study brain activity and connectivity for over two decades. Unfortunately, fMRI data also contain structured temporal "noise" from a variety of sources, including subject motion, subject physiology, and the MRI equipment. Recently, methods have been developed to automatically and selectively remove spatially specific structured noise from fMRI data using spatial Independent Components Analysis (ICA) and machine learning classifiers. Spatial ICA is particularly effective at removing spatially specific structured noise from high temporal and spatial resolution fMRI data of the type acquired by the Human Connectome Project and similar studies. However, spatial ICA is mathematically, by design, unable to separate spatially widespread "global" structured noise from fMRI data (e.g., blood flow modulations from subject respiration). No methods currently exist to selectively and completely remove global structured noise while retaining the global signal from neural activity. This has left the field in a quandary-to do or not to do global signal regression-given that both choices have substantial downsides. Here we show that temporal ICA can selectively segregate and remove global structured noise while retaining global neural signal in both task-based and resting state fMRI data. We compare the results before and after temporal ICA cleanup to those from global signal regression and show that temporal ICA cleanup removes the global positive biases caused by global physiological noise without inducing the network-specific negative biases of global signal regression. We believe that temporal ICA cleanup provides a "best of both worlds" solution to the global signal and global noise dilemma and that temporal ICA itself unlocks interesting neurobiological insights from fMRI data. Copyright © 2018 Elsevier Inc. All rights reserved.

Demonstration of Tuning to Stimulus Orientation in the Human Visual Cortex: A High-Resolution fMRI Study with a Novel Continuous and Periodic Stimulation Paradigm

PubMed Central

Sun, Pei; Gardner, Justin L.; Costagli, Mauro; Ueno, Kenichi; Waggoner, R. Allen; Tanaka, Keiji; Cheng, Kang

2013-01-01

Cells in the animal early visual cortex are sensitive to contour orientations and form repeated structures known as orientation columns. At the behavioral level, there exist 2 well-known global biases in orientation perception (oblique effect and radial bias) in both animals and humans. However, their neural bases are still under debate. To unveil how these behavioral biases are achieved in the early visual cortex, we conducted high-resolution functional magnetic resonance imaging experiments with a novel continuous and periodic stimulation paradigm. By inserting resting recovery periods between successive stimulation periods and introducing a pair of orthogonal stimulation conditions that differed by 90° continuously, we focused on analyzing a blood oxygenation level-dependent response modulated by the change in stimulus orientation and reliably extracted orientation preferences of single voxels. We found that there are more voxels preferring horizontal and vertical orientations, a physiological substrate underlying the oblique effect, and that these over-representations of horizontal and vertical orientations are prevalent in the cortical regions near the horizontal- and vertical-meridian representations, a phenomenon related to the radial bias. Behaviorally, we also confirmed that there exists perceptual superiority for horizontal and vertical orientations around horizontal and vertical meridians, respectively. Our results, thus, refined the neural mechanisms of these 2 global biases in orientation perception. PMID:22661413

Counter-regulation in affective attentional biases: a basic mechanism that warrants flexibility in emotion and motivation.

PubMed

Rothermund, Klaus; Voss, Andreas; Wentura, Dirk

2008-02-01

We investigated whether anticipating positive or negative future outcomes during goal pursuit has a modulatory effect on attentional biases for affectively congruent and incongruent distractor stimuli. In two experiments using a flanker task, we found that distractor interference of stimuli signaling opportunities or dangers was stronger after inducing an outcome focus of the opposite valence. The second experiment provided additional evidence that the incongruency effect reflects a global shift in affective attentional biases and is not mediated by changes in strategies or in the perceived valence of the stimuli. It is argued that counter-regulation in affective attentional biases serves an important function for the regulation of emotion and action.

“Modeling Trends in Air Pollutant Concentrations over the Northern Hemisphere Using the Coupled WRF-CMAQ Model”

EPA Science Inventory

Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate and influence regional calculatio...

Perceptual expertise: can sensorimotor experience change holistic processing and left-side bias?

PubMed

Tso, Ricky Van-yip; Au, Terry Kit-fong; Hsiao, Janet Hui-wen

2014-09-01

Holistic processing and left-side bias are both behavioral markers of expert face recognition. By contrast, expert recognition of characters in Chinese orthography involves left-side bias but reduced holistic processing, although faces and Chinese characters share many visual properties. Here, we examined whether this reduction in holistic processing of Chinese characters can be better explained by writing experience than by reading experience. Compared with Chinese nonreaders, Chinese readers who had limited writing experience showed increased holistic processing, whereas Chinese readers who could write characters fluently showed reduced holistic processing. This result suggests that writing and sensorimotor experience can modulate holistic-processing effects and that the reduced holistic processing observed in expert Chinese readers may depend mostly on writing experience. However, both expert writers and writers with limited experience showed similarly stronger left-side bias than novices did in processing mirror-symmetric Chinese characters; left-side bias may therefore be a robust expertise marker for object recognition that is uninfluenced by sensorimotor experience. © The Author(s) 2014.

Projecting one’s own spatial bias onto others during a theory-of-mind task

PubMed Central

Bio, Branden J.; Webb, Taylor W.; Graziano, Michael S. A.

2018-01-01

Many people show a left-right bias in visual processing. We measured spatial bias in neurotypical participants using a variant of the line bisection task. In the same participants, we measured performance in a social cognition task. This theory-of-mind task measured whether each participant had a processing-speed bias toward the right of, or left of, a cartoon agent about which the participant was thinking. Crucially, the cartoon was rotated such that what was left and right with respect to the cartoon was up and down with respect to the participant. Thus, a person’s own left-right bias could not align directly onto left and right with respect to the cartoon head. Performance on the two tasks was significantly correlated. People who had a natural bias toward processing their own left side of space were quicker to process how the cartoon might think about objects to the left side of its face, and likewise for a rightward bias. One possible interpretation of these results is that the act of processing one’s own personal space shares some of the same underlying mechanisms as the social cognitive act of reconstructing someone else’s processing of their space. PMID:29339513

Working memory regulates trait anxiety-related threat processing biases.

PubMed

Booth, Robert W; Mackintosh, Bundy; Sharma, Dinkar

2017-06-01

High trait anxious individuals tend to show biased processing of threat. Correlational evidence suggests that executive control could be used to regulate such threat-processing. On this basis, we hypothesized that trait anxiety-related cognitive biases regarding threat should be exaggerated when executive control is experimentally impaired by loading working memory. In Study 1, 68 undergraduates read ambiguous vignettes under high and low working memory load; later, their interpretations of these vignettes were assessed via a recognition test. Trait anxiety predicted biased interpretation of social threat vignettes under high working memory load, but not under low working memory load. In Study 2, 53 undergraduates completed a dot probe task with fear-conditioned Japanese characters serving as threat stimuli. Trait anxiety predicted attentional bias to the threat stimuli but, again, this only occurred under high working memory load. Interestingly however, actual eye movements toward the threat stimuli were only associated with state anxiety, and this was not moderated by working memory load, suggesting that executive control regulates biased threat-processing downstream of initial input processes such as orienting. These results suggest that cognitive loads can exacerbate trait anxiety-related cognitive biases, and therefore represent a useful tool for assessing cognitive biases in future research. More importantly, since biased threat-processing has been implicated in the etiology and maintenance of anxiety, poor executive control may be a risk factor for anxiety disorders. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as "field" or "global" significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Monthly temperature climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

Global health education in United States anesthesiology residency programs: a survey of resident opportunities and program director attitudes.

PubMed

Kaur, Gunisha; Tabaie, Sheida; Brar, Jasmit; Tangel, Virginia; Pryor, Kane O

2017-11-16

Interest in global health during postgraduate residency training is increasing across medical specialties, and multiple disciplines have categorized global health training opportunities in their arena. No such cataloging exists for anesthesiology residency programs. The aim of this study was to assess and characterize global health opportunities and the attitudes of program directors (PDs) in U.S. anesthesiology residency programs towards this training. A cross-sectional 20-question survey on global health opportunities was distributed to 128 ACGME accredited anesthesiology residency program directors via email between October 2015 and January 2016. Descriptive statistics and exploratory inferential analyses were applied. Maximal nonresponse selection bias was estimated. The overall response rate was 44%. Of those who responded, 61% reported that their residency program had a global health elective, with a maximal bias estimate of 6.5%. 45% of program directors with no global health elective reported wanting to offer one. 77% of electives have articulated educational goals, but there is substantial heterogeneity in curricula offered. Program director attitudes regarding the value of global health programs differed significantly between those with and without existing programs. The proportion of U.S. anesthesiology residency programs offering global health electives is similar to that in other medical specialties. There is inconsistency in program structure, goals, curriculum, and funding. Attitudes of program directors differ between programs with and without electives, which may reflect bidirectional influence to be investigated further. Further studies are needed to codify curricula, assess effectiveness, and validate methodologies.

Applications of DC-Self Bias in CCP Deposition Systems

NASA Astrophysics Data System (ADS)

Keil, D. L.; Augustyniak, E.; Sakiyama, Y.

2013-09-01

In many commercial CCP plasma process systems the DC-self bias is available as a reported process parameter. Since commercial systems typically limit the number of onboard diagnostics, there is great incentive to understand how DC-self bias can be expected to respond to various system perturbations. This work reviews and examines DC self bias changes in response to tool aging, chamber film accumulation and wafer processing. The diagnostic value of the DC self bias response to transient and various steady state current draw schemes are examined. Theoretical models and measured experimental results are compared and contrasted.

Going global: the transnationalization of care.

PubMed

Yeates, Nicola

2011-01-01

This article critically examines the contours of ‘care transnationalization’ as an ongoing social process and a field of enquiry. Care transnationalization scholarship combines structural understandings of global power relations with an emphasis on social interactions between defined actors in ways that keep sight of human agency, material welfare and wider social development. It has, however, tended to privilege particular forms, dynamics and sites of care transnationalization over others. The body of research on care labour migration, which is otherwise the most developed literature on care transnationalization to date, contains a number of biases and omissions in its coverage of border-spanning relations and their mediation across country contexts. At the same time, other significant forms of care transnationalization, such as those involving consumer-based care migration, corporate restructuring and the formation of care policy, have suffered from comparative neglect. Working towards an integrated agenda that addresses these diverse expressions of care transnationalization and how they ‘touch down’ in a range of sectoral, social and country contexts is of prime importance to policy research agendas directed at understanding the wider development impacts of processes of social and economic restructuring.

Estimation of the daily global solar radiation based on the Gaussian process regression methodology in the Saharan climate

NASA Astrophysics Data System (ADS)

Guermoui, Mawloud; Gairaa, Kacem; Rabehi, Abdelaziz; Djafer, Djelloul; Benkaciali, Said

2018-06-01

Accurate estimation of solar radiation is the major concern in renewable energy applications. Over the past few years, a lot of machine learning paradigms have been proposed in order to improve the estimation performances, mostly based on artificial neural networks, fuzzy logic, support vector machine and adaptive neuro-fuzzy inference system. The aim of this work is the prediction of the daily global solar radiation, received on a horizontal surface through the Gaussian process regression (GPR) methodology. A case study of Ghardaïa region (Algeria) has been used in order to validate the above methodology. In fact, several combinations have been tested; it was found that, GPR-model based on sunshine duration, minimum air temperature and relative humidity gives the best results in term of mean absolute bias error (MBE), root mean square error (RMSE), relative mean square error (rRMSE), and correlation coefficient ( r) . The obtained values of these indicators are 0.67 MJ/m2, 1.15 MJ/m2, 5.2%, and 98.42%, respectively.

Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes

NASA Astrophysics Data System (ADS)

Iizumi, Toshichika; Takikawa, Hiroki; Hirabayashi, Yukiko; Hanasaki, Naota; Nishimori, Motoki

2017-08-01

The use of different bias-correction methods and global retrospective meteorological forcing data sets as the reference climatology in the bias correction of general circulation model (GCM) daily data is a known source of uncertainty in projected climate extremes and their impacts. Despite their importance, limited attention has been given to these uncertainty sources. We compare 27 projected temperature and precipitation indices over 22 regions of the world (including the global land area) in the near (2021-2060) and distant future (2061-2100), calculated using four Representative Concentration Pathways (RCPs), five GCMs, two bias-correction methods, and three reference forcing data sets. To widen the variety of forcing data sets, we developed a new forcing data set, S14FD, and incorporated it into this study. The results show that S14FD is more accurate than other forcing data sets in representing the observed temperature and precipitation extremes in recent decades (1961-2000 and 1979-2008). The use of different bias-correction methods and forcing data sets contributes more to the total uncertainty in the projected precipitation index values in both the near and distant future than the use of different GCMs and RCPs. However, GCM appears to be the most dominant uncertainty source for projected temperature index values in the near future, and RCP is the most dominant source in the distant future. Our findings encourage climate risk assessments, especially those related to precipitation extremes, to employ multiple bias-correction methods and forcing data sets in addition to using different GCMs and RCPs.

Asian summer monsoon seasonal prediction skill in the Met Office GloSea5 model and its dependence on mean state biases

NASA Astrophysics Data System (ADS)

Bush, Stephanie; Turner, Andrew; Martin, Gill; Woolnough, Steve

2015-04-01

Predicting the circulation and precipitation features of the Asian monsoon on time scales of weeks to the season ahead remains a challenge for prediction centres. Current state-of-the-art models retain large biases, particularly dryness over India, which evolve rapidly from initialization and persist into centennial length climate integrations, illustrating the seamless nature of the monsoon problem. We present initial results from our Ministry of Earth Sciences Indian Monsoon Mission collaboration project to assess and improve weekly-to-seasonal forecasts in the Met Office Unified Model (MetUM) coupled initialized Global Seasonal Prediction System (GloSea5). Using a 14-year hindcast ensemble of integrations in which atmosphere, ocean and sea-ice components are initialized from May start dates, we assess the monsoon seasonal prediction skill and global mean state biases of GloSea5. Initial May and June biases include a lack of precipitation over the Indian peninsula, and a weakened monsoon flow, and these give way to a more robust pattern of excess precipitation in the western north Pacific, lack of precipitation over the Maritime Continent, excess westerlies across the Indian peninsula and Indochina, and cool SSTs in the eastern equatorial Indian Ocean and western north Pacific in July and August. Despite these mean state biases, the interannual correlation of predicted JJA all India rainfall from 1998 to 2009 with TRMM is fairly high at 0.68. Future work will focus on the prospects for further improving this skill with bias correction techniques.

Interpersonal beliefs related to suicide and facial emotion processing in psychotic disorders.

PubMed

Villa, Jennifer; Pinkham, Amy E; Kaufmann, Christopher N; Granholm, Eric; Harvey, Philip D; Depp, Colin A

2018-05-01

Deficits in social cognition are present in psychotic disorders; moreover, maladaptive interpersonal beliefs have been posited to underlie risk of suicidal ideation and behavior. However, the association between social cognition and negative appraisals as potential risk factors for suicidal ideation and behavior in psychotic disorders has not been assessed. In a pilot study, we assessed accuracy and error biases in facial emotion recognition (Penn ER-40), maladaptive interpersonal beliefs as measured by the Interpersonal Needs Questionnaire (INQ), and current suicide ideation and history of past attempts in a sample of 101 outpatients with psychotic disorders (75 schizophrenia/schizoaffective; 26 bipolar disorder). INQ scores were positively associated with history of suicide attempts and current ideation. INQ scores were inversely related with emotion recognition accuracy yet positively correlated with bias toward perceiving anger in neutral expressions. The association between biases pertaining to anger and INQ scores persisted after adjusting for global cognitive ability and were more evident in schizophrenia than in bipolar disorder. The present findings suggest that maladaptive beliefs are associated with a tendency to misperceive neutral stimuli as threatening and are associated with suicidal ideation and behavior. Although better cognitive ability is associated with higher rates of suicide attempts in psychotic disorders, biases in misinterpreting anger in others may be a specific deficit related to formation of maladaptive beliefs about others, which, in turn, are associated with history of suicide attempts. Copyright © 2018. Published by Elsevier Ltd.

Evaluation of global horizontal irradiance to plane-of-array irradiance models at locations across the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lave, Matthew; Hayes, William; Pohl, Andrew

2015-02-02

We report an evaluation of the accuracy of combinations of models that estimate plane-of-array (POA) irradiance from measured global horizontal irradiance (GHI). This estimation involves two steps: 1) decomposition of GHI into direct and diffuse horizontal components and 2) transposition of direct and diffuse horizontal irradiance (DHI) to POA irradiance. Measured GHI and coincident measured POA irradiance from a variety of climates within the United States were used to evaluate combinations of decomposition and transposition models. A few locations also had DHI measurements, allowing for decoupled analysis of either the decomposition or the transposition models alone. Results suggest that decompositionmore » models had mean bias differences (modeled versus measured) that vary with climate. Transposition model mean bias differences depended more on the model than the location. Lastly, when only GHI measurements were available and combinations of decomposition and transposition models were considered, the smallest mean bias differences were typically found for combinations which included the Hay/Davies transposition model.« less

A New Global Vertical Land Movement Data Set from the TIGA Combined Solution

NASA Astrophysics Data System (ADS)

Hunegnaw, Addisu; Teferle, Felix Norman; Ebuy Abraha, Kibrom; Santamaría-Gómez, Alvaro; Gravelle, Médéric; Wöppelman, Guy; Schöne, Tilo; Deng, Zhiguo; Bingley, Richard; Hansen, Dionne Nicole; Sanchez, Laura; Moore, Michael; Jia, Minghai

2017-04-01

Globally averaged sea level has been estimated from the network of tide gauges installed around the world since the 19th century. These mean sea level (MSL) records provide sea level relative to a nearby tide gauge benchmark (TGBM), which allows for the continuation of the instrumental record in time. Any changes in the benchmark levels, induced by vertical land movements (VLM) affect the MSL records and hence sea level estimates. Over the last two decades sea level has also been observed using satellite altimeters. While the satellite observations are globally more homogeneous providing a picture of sea level not confined to coastlines, they require the VLM-corrected MSL records for the bias calibration of instrumental drifts. Without this calibration altimeter instruments from different missions cannot be combined. GPS has made it possible to obtain highly accurate estimates of VLM in a geocentric reference frame for stations at or close to tide gauges. Under the umbrella of the International GNSS Service (IGS), the Tide Gauge Benchmark Monitoring (TIGA) Working Group (WG) has been established to apply the expertise of the GNSS community to solving issues related to the accuracy and reliability of the vertical component to provide estimates of VLM in a well-defined global reference frame. To achieve this objective, five TIGA Analysis Centers (TACs) contributed re-processed global GPS network solutions to TIGA, employing the latest bias models and processing strategies in accordance with the second re-processing campaign (repro2) of the IGS. These solutions include those of the British Isles continuous GNSS Facility - University of Luxembourg consortium (BLT), the German Research Centre for Geosciences (GFZ) Potsdam, the German Geodetic Research Institute (DGF) at the Technical University of Munich, Geoscience Australia (AUT) and the University of La Rochelle (ULR). In this study we present to the sea level community an evaluation of the VLM estimates from the first combined solution from the IGS TIGA WG. The TAC solutions include more than 700 stations and span the common period 1995-2014. The combined solution was computed by the TIGA Combination Centre (TCC) at the University of Luxembourg, which used the Combination and Analysis of Terrestrial Reference Frame (CATREF) software package for this purpose. This first solution forms Release 1.0 and further releases will be made available after further reprocessing campaigns. We evaluate the combined solution internally using the TAC solutions and externally using solutions from the IGS and the ITRF2008. The derived VLM estimates have undergone an initial evaluation and should be considered as the primary TIGA product for the sea level community to correct MSL records for land level changes.

Characterizing Satellite Rainfall Errors based on Land Use and Land Cover and Tracing Error Source in Hydrologic Model Simulation

NASA Astrophysics Data System (ADS)

Gebregiorgis, A. S.; Peters-Lidard, C. D.; Tian, Y.; Hossain, F.

2011-12-01

Hydrologic modeling has benefited from operational production of high resolution satellite rainfall products. The global coverage, near-real time availability, spatial and temporal sampling resolutions have advanced the application of physically based semi-distributed and distributed hydrologic models for wide range of environmental decision making processes. Despite these successes, the existence of uncertainties due to indirect way of satellite rainfall estimates and hydrologic models themselves remain a challenge in making meaningful and more evocative predictions. This study comprises breaking down of total satellite rainfall error into three independent components (hit bias, missed precipitation and false alarm), characterizing them as function of land use and land cover (LULC), and tracing back the source of simulated soil moisture and runoff error in physically based distributed hydrologic model. Here, we asked "on what way the three independent total bias components, hit bias, missed, and false precipitation, affect the estimation of soil moisture and runoff in physically based hydrologic models?" To understand the clear picture of the outlined question above, we implemented a systematic approach by characterizing and decomposing the total satellite rainfall error as a function of land use and land cover in Mississippi basin. This will help us to understand the major source of soil moisture and runoff errors in hydrologic model simulation and trace back the information to algorithm development and sensor type which ultimately helps to improve algorithms better and will improve application and data assimilation in future for GPM. For forest and woodland and human land use system, the soil moisture was mainly dictated by the total bias for 3B42-RT, CMORPH, and PERSIANN products. On the other side, runoff error was largely dominated by hit bias than the total bias. This difference occurred due to the presence of missed precipitation which is a major contributor to the total bias both during the summer and winter seasons. Missed precipitation, most likely light rain and rain over snow cover, has significant effect on soil moisture and are less capable of producing runoff that results runoff dependency on the hit bias only.

Decadal trends in global pelagic ocean chlorophyll: A new assessment integrating multiple satellites, in situ data, and models.

PubMed

Gregg, Watson W; Rousseaux, Cécile S

2014-09-01

Quantifying change in ocean biology using satellites is a major scientific objective. We document trends globally for the period 1998-2012 by integrating three diverse methodologies: ocean color data from multiple satellites, bias correction methods based on in situ data, and data assimilation to provide a consistent and complete global representation free of sampling biases. The results indicated no significant trend in global pelagic ocean chlorophyll over the 15 year data record. These results were consistent with previous findings that were based on the first 6 years and first 10 years of the SeaWiFS mission. However, all of the Northern Hemisphere basins (north of 10° latitude), as well as the Equatorial Indian basin, exhibited significant declines in chlorophyll. Trend maps showed the local trends and their change in percent per year. These trend maps were compared with several other previous efforts using only a single sensor (SeaWiFS) and more limited time series, showing remarkable consistency. These results suggested the present effort provides a path forward to quantifying global ocean trends using multiple satellite missions, which is essential if we are to understand the state, variability, and possible changes in the global oceans over longer time scales.

Timing of the departure of ocean biogeochemical cycles from the preindustrial state.

PubMed

Christian, James R

2014-01-01

Changes in ocean chemistry and climate induced by anthropogenic CO2 affect a broad range of ocean biological and biogeochemical processes; these changes are already well underway. Direct effects of CO2 (e.g. on pH) are prominent among these, but climate model simulations with historical greenhouse gas forcing suggest that physical and biological processes only indirectly forced by CO2 (via the effect of atmospheric CO2 on climate) begin to show anthropogenically-induced trends as early as the 1920s. Dates of emergence of a number of representative ocean fields from the envelope of natural variability are calculated for global means and for spatial 'fingerprints' over a number of geographic regions. Emergence dates are consistent among these methods and insensitive to the exact choice of regions, but are generally earlier with more spatial information included. Emergence dates calculated for individual sampling stations are more variable and generally later, but means across stations are generally consistent with global emergence dates. The last sign reversal of linear trends calculated for periods of 20 or 30 years also functions as a diagnostic of emergence, and is generally consistent with other measures. The last sign reversal among 20 year trends is found to be a conservative measure (biased towards later emergence), while for 30 year trends it is found to have an early emergence bias, relative to emergence dates calculated by departure from the preindustrial mean. These results are largely independent of emission scenario, but the latest-emerging fields show a response to mitigation. A significant anthropogenic component of ocean variability has been present throughout the modern era of ocean observation.

Timing of the Departure of Ocean Biogeochemical Cycles from the Preindustrial State

PubMed Central

Christian, James R.

2014-01-01

Changes in ocean chemistry and climate induced by anthropogenic CO2 affect a broad range of ocean biological and biogeochemical processes; these changes are already well underway. Direct effects of CO2 (e.g. on pH) are prominent among these, but climate model simulations with historical greenhouse gas forcing suggest that physical and biological processes only indirectly forced by CO2 (via the effect of atmospheric CO2 on climate) begin to show anthropogenically-induced trends as early as the 1920s. Dates of emergence of a number of representative ocean fields from the envelope of natural variability are calculated for global means and for spatial ‘fingerprints’ over a number of geographic regions. Emergence dates are consistent among these methods and insensitive to the exact choice of regions, but are generally earlier with more spatial information included. Emergence dates calculated for individual sampling stations are more variable and generally later, but means across stations are generally consistent with global emergence dates. The last sign reversal of linear trends calculated for periods of 20 or 30 years also functions as a diagnostic of emergence, and is generally consistent with other measures. The last sign reversal among 20 year trends is found to be a conservative measure (biased towards later emergence), while for 30 year trends it is found to have an early emergence bias, relative to emergence dates calculated by departure from the preindustrial mean. These results are largely independent of emission scenario, but the latest-emerging fields show a response to mitigation. A significant anthropogenic component of ocean variability has been present throughout the modern era of ocean observation. PMID:25386910

A Time Series of Mean Global Sea Surface Temperature from the Along-Track Scanning Radiometers

NASA Astrophysics Data System (ADS)

Veal, Karen L.; Corlett, Gary; Remedios, John; Llewellyn-Jones, David

2010-12-01

A climate data set requires a long time series of consistently processed data with suitably long periods of overlap of different instruments which allows characterization of any inter-instrument biases. The data obtained from ESA's three Along-Track Scanning Radiometers (ATSRs) together comprise an 18 year record of SST with overlap periods of at least 6 months. The data from all three ATSRs has been consistently processed. These factors together with the stability of the instruments and the precision of the derived SST makes this data set eminently suitable for the construction of a time series of SST that complies with many of the GCOS requirements for a climate data set. A time series of global and regional average SST anomalies has been constructed from the ATSR version 2 data set. An analysis of the overlap periods of successive instruments was used to remove intra-series biases and align the series to a common reference. An ATSR climatology has been developed and has been used to calculate the SST anomalies. The ATSR-1 time series and the AATSR time series have been aligned to ATSR-2. The largest adjustment is ~0.2 K between ATSR-2 and AATSR which is suspected to be due to a shift of the 12 μm filter function for AATSR. An uncertainty of 0.06 K is assigned to the relative anomaly record that is derived from the dual three-channel night-time data. A relative uncertainty of 0.07 K is assigned to the dual night-time two-channel record, except in the ATSR-1 period (1994-1996) where it is larger.

Subseasonal forecast skills and biases of global summer monsoons in the NCEP Climate Forecast System version 2

NASA Astrophysics Data System (ADS)

Liu, Xiangwen; Yang, Song; Li, Qiaoping; Kumar, Arun; Weaver, Scott; Liu, Shi

2014-03-01

Subseasonal forecast skills and biases of global summer monsoons are diagnosed using daily data from the hindcasts of 45-day integrations by the NCEP Climate Forecast System version 2. Predictions for subseasonal variability of zonal wind and precipitation are generally more skillful over the Asian and Australian monsoon regions than other monsoon regions. Climatologically, forecasts for the variations of dynamical monsoon indices have high skills at leads of about 2 weeks. However, apparent interannual differences exist, with high skills up to 5 weeks in exceptional cases. Comparisons for the relationships of monsoon indices with atmospheric circulation and precipitation patterns between skillful and unskillful forecasts indicate that skills for subseasonal variability of a monsoon index depend partially on the degree to which the observed variability of the index attributes to the variation of large-scale circulation. Thus, predictions are often more skillful when the index is closely linked to atmospheric circulation over a broad region than over a regional and narrow range. It is also revealed that, the subseasonal variations of biases of winds, precipitation, and surface temperature over various monsoon regions are captured by a first mode with seasonally independent biases and a second mode with apparent phase transition of biases during summer. The first mode indicates the dominance of overall weaker-than-observed summer monsoons over major monsoon regions. However, at certain stages of monsoon evolution, these underestimations are regionally offset or intensified by the time evolving biases portrayed by the second mode. This feature may be partially related to factors such as the shifts of subtropical highs and intertropical convergence zones, the reversal of biases of surface temperature over some monsoon regions, and the transition of regional circulation system. The significant geographical differences in bias growth with increasing lead time reflect the distinctions of initial memory capability of the climate system over different monsoon regions.

Improving Treatment Response for Paediatric Anxiety Disorders: An Information-Processing Perspective.

PubMed

Ege, Sarah; Reinholdt-Dunne, Marie Louise

2016-12-01

Cognitive behavioural therapy (CBT) is considered the treatment of choice for paediatric anxiety disorders, yet there remains substantial room for improvement in treatment outcomes. This paper examines whether theory and research into the role of information-processing in the underlying psychopathology of paediatric anxiety disorders indicate possibilities for improving treatment response. Using a critical review of recent theoretical, empirical and academic literature, the paper examines the role of information-processing biases in paediatric anxiety disorders, the extent to which CBT targets information-processing biases, and possibilities for improving treatment response. The literature reviewed indicates a role for attentional and interpretational biases in anxious psychopathology. While there is theoretical grounding and limited empirical evidence to indicate that CBT ameliorates interpretational biases, evidence regarding the effects of CBT on attentional biases is mixed. Novel treatment methods including attention bias modification training, attention feedback awareness and control training, and mindfulness-based therapy may hold potential in targeting attentional biases, and thereby in improving treatment response. The integration of novel interventions into an existing evidence-based protocol is a complex issue and faces important challenges with regard to determining the optimal treatment package. Novel interventions targeting information-processing biases may hold potential in improving response to CBT for paediatric anxiety disorders. Many important questions remain to be answered.

Global grey matter volume in adult bipolar patients with and without lithium treatment: A meta-analysis.

PubMed

Sun, Yue Ran; Herrmann, Nathan; Scott, Christopher J M; Black, Sandra E; Khan, Maisha M; Lanctôt, Krista L

2018-01-01

The goal of this meta-analysis was to quantitatively summarize the evidence available on the differences in grey matter volume between lithium-treated and lithium-free bipolar patients. A systematic search was conducted in Cochrane Central, Embase, MEDLINE, and PsycINFO databases for original peer-reviewed journal articles that reported on global grey matter volume in lithium-medicated and lithium-free bipolar patients. Standard mean difference and Hedges' g were used to calculate effect size in a random-effects model. Risk of publication bias was assessed using Egger's test and quality of evidence was assessed using standard criteria. There were 15 studies with a total of 854 patients (368 lithium-medicated, 486 lithium-free) included in the meta-analysis. Global grey matter volume was significantly larger in lithium-treated bipolar patients compared to lithium-free patients (SMD: 0.17, 95% CI: 0.01-0.33; z = 2.11, p = 0.035). Additionally, there was a difference in global grey matter volume between groups in studies that employed semi-automated segmentation methods (SMD: 0.66, 95% CI: 0.01-1.31; z = 1.99, p = 0.047), but no significant difference in studies that used fully-automated segmentation. No publication bias was detected (bias coefficient = - 0.65, p = 0.46). Variability in imaging methods and lack of high-quality evidence limits the interpretation of the findings. Results suggest that lithium-treated patients have a greater global grey matter volume than those who were lithium-free. Further study of the relationship between lithium and grey matter volume may elucidate the therapeutic potential of lithium in conditions characterized by abnormal changes in brain structure. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Precise Point Positioning Using Triple GNSS Constellations in Various Modes

PubMed Central

Afifi, Akram; El-Rabbany, Ahmed

2016-01-01

This paper introduces a new dual-frequency precise point positioning (PPP) model, which combines the observations from three different global navigation satellite system (GNSS) constellations, namely GPS, Galileo, and BeiDou. Combining measurements from different GNSS systems introduces additional biases, including inter-system bias and hardware delays, which require rigorous modelling. Our model is based on the un-differenced and between-satellite single-difference (BSSD) linear combinations. BSSD linear combination cancels out some receiver-related biases, including receiver clock error and non-zero initial phase bias of the receiver oscillator. Forming the BSSD linear combination requires a reference satellite, which can be selected from any of the GPS, Galileo, and BeiDou systems. In this paper three BSSD scenarios are tested; each considers a reference satellite from a different GNSS constellation. Natural Resources Canada’s GPSPace PPP software is modified to enable a combined GPS, Galileo, and BeiDou PPP solution and to handle the newly introduced biases. A total of four data sets collected at four different IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) network are used to correct the GPS, Galileo, and BeiDou measurements in the post-processing PPP mode. A real-time PPP solution is also obtained, which is referred to as RT-PPP in the sequel, through the use of the IGS real-time service (RTS) for satellite orbit and clock corrections. However, only GPS and Galileo observations are used for the RT-PPP solution, as the RTS-IGS satellite products are not presently available for BeiDou system. All post-processed and real-time PPP solutions are compared with the traditional un-differenced GPS-only counterparts. It is shown that combining the GPS, Galileo, and BeiDou observations in the post-processing mode improves the PPP convergence time by 25% compared with the GPS-only counterpart, regardless of the linear combination used. The use of BSSD linear combination improves the precision of the estimated positioning parameters by about 25% in comparison with the GPS-only PPP solution. Additionally, the solution convergence time is reduced to 10 minutes for the BSSD model, which represents about 50% reduction, in comparison with the GPS-only PPP solution. The GNSS RT-PPP solution, on the other hand, shows a similar convergence time and precision to the GPS-only counterpart. PMID:27240376

Precise Point Positioning Using Triple GNSS Constellations in Various Modes.

PubMed

Afifi, Akram; El-Rabbany, Ahmed

2016-05-28

This paper introduces a new dual-frequency precise point positioning (PPP) model, which combines the observations from three different global navigation satellite system (GNSS) constellations, namely GPS, Galileo, and BeiDou. Combining measurements from different GNSS systems introduces additional biases, including inter-system bias and hardware delays, which require rigorous modelling. Our model is based on the un-differenced and between-satellite single-difference (BSSD) linear combinations. BSSD linear combination cancels out some receiver-related biases, including receiver clock error and non-zero initial phase bias of the receiver oscillator. Forming the BSSD linear combination requires a reference satellite, which can be selected from any of the GPS, Galileo, and BeiDou systems. In this paper three BSSD scenarios are tested; each considers a reference satellite from a different GNSS constellation. Natural Resources Canada's GPSPace PPP software is modified to enable a combined GPS, Galileo, and BeiDou PPP solution and to handle the newly introduced biases. A total of four data sets collected at four different IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) network are used to correct the GPS, Galileo, and BeiDou measurements in the post-processing PPP mode. A real-time PPP solution is also obtained, which is referred to as RT-PPP in the sequel, through the use of the IGS real-time service (RTS) for satellite orbit and clock corrections. However, only GPS and Galileo observations are used for the RT-PPP solution, as the RTS-IGS satellite products are not presently available for BeiDou system. All post-processed and real-time PPP solutions are compared with the traditional un-differenced GPS-only counterparts. It is shown that combining the GPS, Galileo, and BeiDou observations in the post-processing mode improves the PPP convergence time by 25% compared with the GPS-only counterpart, regardless of the linear combination used. The use of BSSD linear combination improves the precision of the estimated positioning parameters by about 25% in comparison with the GPS-only PPP solution. Additionally, the solution convergence time is reduced to 10 minutes for the BSSD model, which represents about 50% reduction, in comparison with the GPS-only PPP solution. The GNSS RT-PPP solution, on the other hand, shows a similar convergence time and precision to the GPS-only counterpart.

Cognitive-Processing Bias in Chinese Student Teachers with Strong and Weak Professional Identity.

PubMed

Wang, Xin-Qiang; Zhu, Jun-Cheng; Liu, Lu; Chen, Xiang-Yu

2017-01-01

Professional identity plays an important role in career development. Although many studies have examined professional identity, differences in cognitive-processing biases between Chinese student teachers with strong and weak professional identity are poorly understood. The current study adopted Tversky's social-cognitive experimental paradigm to explore cognitive-processing biases in Chinese student teachers with strong and weak professional identity. Experiment 1 showed that participants with strong professional identity exhibited stronger positive-coding bias toward positive profession-related life events, relative to that observed in those with weak professional identity. Experiment 2 showed that participants with strong professional identity exhibited greater recognition bias for previously read items, relative to that observed in those with weak professional identity. Overall, the results suggested that participants with strong professional identity exhibited greater positive cognitive-processing bias relative to that observed in those with weak professional identity.

Cognitive-Processing Bias in Chinese Student Teachers with Strong and Weak Professional Identity

PubMed Central

Wang, Xin-qiang; Zhu, Jun-cheng; Liu, Lu; Chen, Xiang-yu

2017-01-01

Professional identity plays an important role in career development. Although many studies have examined professional identity, differences in cognitive-processing biases between Chinese student teachers with strong and weak professional identity are poorly understood. The current study adopted Tversky’s social-cognitive experimental paradigm to explore cognitive-processing biases in Chinese student teachers with strong and weak professional identity. Experiment 1 showed that participants with strong professional identity exhibited stronger positive-coding bias toward positive profession-related life events, relative to that observed in those with weak professional identity. Experiment 2 showed that participants with strong professional identity exhibited greater recognition bias for previously read items, relative to that observed in those with weak professional identity. Overall, the results suggested that participants with strong professional identity exhibited greater positive cognitive-processing bias relative to that observed in those with weak professional identity. PMID:28555123

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

NASA Technical Reports Server (NTRS)

Epperson, David L.; Davis, Jerry M.; Bloomfield, Peter; Karl, Thomas R.; Mcnab, Alan L.; Gallo, Kevin P.

1995-01-01

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal problems for global application once global NDVI and DMSP data become available.

Bias Reduction as Guidance for Developing Convection and Cloud Parameterization in GFDL AM4/CM4

NASA Astrophysics Data System (ADS)

Zhao, M.; Held, I.; Golaz, C.

2016-12-01

The representations of moist convection and clouds are challenging in global climate models and they are known to be important to climate simulations at all spatial and temporal scales. Many climate simulation biases can be traced to deficiencies in convection and cloud parameterizations. I will present some key biases that we are concerned about and the efforts that we have made to reduce the biases during the development of NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) new generation global climate model AM4/CM4. In particular, I will present a modified version of the moist convection scheme that is based on the University of Washington Shallow Cumulus scheme (UWShCu, Bretherton et. al 2004). The new scheme produces marked improvement in simulation of the Madden-Julian Oscillation (MJO) and the El Niño-Southern Oscillation (ENSO) compared to that used in AM3 and HIRAM. AM4/CM4 also produces high quality simulation of global distribution of cloud radiative effects and the precipitation with realistic mean climate state. This differs from models of improved MJO but with a much deteriorated mean state. The modifications to the UWShCu include an additional bulk plume for representing deep convection. The entrainment rate in the deep plume is parameterized to be a function of column-integrated relative humidity. The deep convective closure is based on relaxation of the convective available potential energy (CAPE) or cloud work function. The plumes' precipitation efficiency is optimized for better simulations of the cloud radiative effects. Precipitation re-evaporation is included in both shallow and deep plumes. In addition, a parameterization of convective gustiness is included with an energy source driven by cold pool derived from precipitation re-evaporation within the boundary layer and energy sink due to dissipation. I will present the motivations of these changes which are driven by reducing some aspects of the AM4/CM4 biases. Finally, I will also present the biases in current AM4/CM4 and challenges to further reduce them.

Implications of CO Bias for Ozone and Methane Lifetime in a CCM

NASA Technical Reports Server (NTRS)

Strode, Sarah; Duncan, Bryan Neal; Yegorova, Elena; Douglass, Anne

2013-01-01

A low bias in carbon monoxide compared to observations at high latitudes is a common feature of chemistry climate models. CO bias can both indicate and contribute to a bias in modeled OH and methane lifetime. This study examines possible causes of CO bias in the ACCMIP simulation of the GEOSCCM, and considers how attributing the CO bias to uncertainty in CO emissions versus biases in other constituents impacts the relationship between CO bias and methane lifetime. We use a simplified model of CO tagged by source with specified OH to quantify the sensitivity of the CO bias to changes in CO emissions or OH concentration, comparing the modeled CO to surface and MOPITT observations. The simplified model shows that decreasing OH in the northern hemisphere removes most of the global mean and inter-hemispheric bias in surface CO. We then use results from this analysis to explore how adjusting CO sources in the CCM impacts the concentrations of ozone, OH and methane. The CCM simulation also exhibits biases in ozone and water vapor compared to observations. We use a parameterized CO-OH-CH4 model that takes ozone and water vapor as inputs to the parameterization to examine whether correcting water and ozone biases can alter OH enough to remove the CO bias. Through this analysis, we aim to better quantify the relationship between CO bias and model biases in ozone concentrations and methane lifetime.

Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?

NASA Astrophysics Data System (ADS)

Manzanas, R.; Lucero, A.; Weisheimer, A.; Gutiérrez, J. M.

2018-02-01

Statistical downscaling methods are popular post-processing tools which are widely used in many sectors to adapt the coarse-resolution biased outputs from global climate simulations to the regional-to-local scale typically required by users. They range from simple and pragmatic Bias Correction (BC) methods, which directly adjust the model outputs of interest (e.g. precipitation) according to the available local observations, to more complex Perfect Prognosis (PP) ones, which indirectly derive local predictions (e.g. precipitation) from appropriate upper-air large-scale model variables (predictors). Statistical downscaling methods have been extensively used and critically assessed in climate change applications; however, their advantages and limitations in seasonal forecasting are not well understood yet. In particular, a key problem in this context is whether they serve to improve the forecast quality/skill of raw model outputs beyond the adjustment of their systematic biases. In this paper we analyze this issue by applying two state-of-the-art BC and two PP methods to downscale precipitation from a multimodel seasonal hindcast in a challenging tropical region, the Philippines. To properly assess the potential added value beyond the reduction of model biases, we consider two validation scores which are not sensitive to changes in the mean (correlation and reliability categories). Our results show that, whereas BC methods maintain or worsen the skill of the raw model forecasts, PP methods can yield significant skill improvement (worsening) in cases for which the large-scale predictor variables considered are better (worse) predicted by the model than precipitation. For instance, PP methods are found to increase (decrease) model reliability in nearly 40% of the stations considered in boreal summer (autumn). Therefore, the choice of a convenient downscaling approach (either BC or PP) depends on the region and the season.

Radiometric traceability diagnosis and bias correction for the Suomi NPP VIIRS long-wave infrared channels during blackbody unsteady states

NASA Astrophysics Data System (ADS)

Cao, Changyong; Wang, Wenhui; Blonski, Slawomir; Zhang, Bin

2017-05-01

The Suomi National Polar-orbiting Partnership Program (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Emissive Bands (TEBs) have been performing well since the data became available on 20 January 2012, and the Sensor Data Record data reached validated maturity on 18 March 2014. While overall the validation has shown that these channels have an estimated absolute uncertainty on the order of 0.1 K based on extensive comparisons, there is a remaining issue that persisted over the years. A calibration bias on the order of 0.1 K is introduced in channels such as M15 during the quarterly blackbody temperature warm-up/cooldown, and the bias is further amplified by the sea surface temperature (SST) retrieval algorithm up to 0.3 K in the global daily-averaged products which causes an apparent spike in the SST time series. Our investigation reveals that this bias is caused by a fundamental but flawed theoretical assumption in the VIIRS calibration equation, which states that the shape of the calibration curve is assumed unchanged from prelaunch to postlaunch without any constrains. While the assumption may work to account for long-term degradation, it has a shortcoming during the blackbody unsteady state. In this study, we present a diagnostic and correction method with a compensatory term (Ltrace) to reconcile the assumption such that it removes the calibration bias during the blackbody temperature changes. The methodology has been tested using historical data, and the results are very positive. The implementation has minimal impacts on the operational data processing system and is readily available for use in operations.

Cognitive Biases and Nonverbal Cue Availability in Detecting Deception

ERIC Educational Resources Information Center

Burgoon, Judee K.; Blair, J. Pete; Strom, Renee E.

2008-01-01

In potentially deceptive situations, people rely on mental shortcuts to help process information. These heuristic judgments are often biased and result in inaccurate assessments of sender veracity. Four such biases--truth bias, visual bias, demeanor bias, and expectancy violation bias--were examined in a judgment experiment that varied nonverbal…

Relating GRACE terrestrial water storage variations to global fields of atmospheric forcing

NASA Astrophysics Data System (ADS)

Humphrey, Vincent; Gudmundsson, Lukas; Isabelle Seneviratne, Sonia

2015-04-01

Synoptic, seasonal and inter-annual fluctuations in atmospheric dynamics all influence terrestrial water storage, with impacts on ecosystems functions, human activities and land-climate interactions. Here we explore to which degree atmospheric variables can explain GRACE estimates of terrestrial water storage on different time scales. Since 2012, the most recent GRACE gravity field solutions (Release 05) can be used to monitor global changes in terrestrial water storage with an unprecedented level of accuracy over more than a decade. In addition, the release of associated gridded and post-processed products facilitates comparisons with other global datasets such as land surface model outputs or satellite observations. We investigate how decadal trends, inter-annual fluctuations as well as monthly anomalies of the seasonal cycle of terrestrial water storage can be related to fields of atmospheric forcing, including e.g. precipitation and temperature as estimated in global reanalysis products using statistical techniques. In the majority of the locations with high signal to noise ratio, both short and long-term fluctuations of total terrestrial water storage can be reconstructed to a large degree based on available atmospheric forcing. However, in some locations atmospheric forcing alone is not sufficient to explain the total change in water storage, suggesting strong influence of other processes. Within that framework, the question of an amplification or attenuation of atmospheric forcing through land-surface feedbacks and changes in long term water storage is discussed, also with respect to uncertainties and potential systematic biases in the results.

CMIP5 land surface models systematically underestimate inter-annual variability of net ecosystem exchange in semi-arid southwestern North America.

NASA Astrophysics Data System (ADS)

MacBean, N.; Scott, R. L.; Biederman, J. A.; Vuichard, N.; Hudson, A.; Barnes, M.; Fox, A. M.; Smith, W. K.; Peylin, P. P.; Maignan, F.; Moore, D. J.

2017-12-01

Recent studies based on analysis of atmospheric CO2 inversions, satellite data and terrestrial biosphere model simulations have suggested that semi-arid ecosystems play a dominant role in the interannual variability and long-term trend in the global carbon sink. These studies have largely cited the response of vegetation activity to changing moisture availability as the primary mechanism of variability. However, some land surface models (LSMs) used in these studies have performed poorly in comparison to satellite-based observations of vegetation dynamics in semi-arid regions. Further analysis is therefore needed to ensure semi-arid carbon cycle processes are well represented in global scale LSMs before we can fully establish their contribution to the global carbon cycle. In this study, we evaluated annual net ecosystem exchange (NEE) simulated by CMIP5 land surface models using observations from 20 Ameriflux sites across semi-arid southwestern North America. We found that CMIP5 models systematically underestimate the magnitude and sign of NEE inter-annual variability; therefore, the true role of semi-arid regions in the global carbon cycle may be even more important than previously thought. To diagnose the factors responsible for this bias, we used the ORCHIDEE LSM to test different climate forcing data, prescribed vegetation fractions and model structures. Climate and prescribed vegetation do contribute to uncertainty in annual NEE simulations, but the bias is primarily caused by incorrect timing and magnitude of peak gross carbon fluxes. Modifications to the hydrology scheme improved simulations of soil moisture in comparison to data. This in turn improved the seasonal cycle of carbon uptake due to a more realistic limitation on photosynthesis during water stress. However, the peak fluxes are still too low, and phenology is poorly represented for desert shrubs and grasses. We provide suggestions on model developments needed to tackle these issues in the future.

An Empirical Approach to Ocean Color Data: Reducing Bias and the Need for Post-Launch Radiometric Re-Calibration

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Casey, Nancy W.; O'Reilly, John E.; Esaias, Wayne E.

2009-01-01

A new empirical approach is developed for ocean color remote sensing. Called the Empirical Satellite Radiance-In situ Data (ESRID) algorithm, the approach uses relationships between satellite water-leaving radiances and in situ data after full processing, i.e., at Level-3, to improve estimates of surface variables while relaxing requirements on post-launch radiometric re-calibration. The approach is evaluated using SeaWiFS chlorophyll, which is the longest time series of the most widely used ocean color geophysical product. The results suggest that ESRID 1) drastically reduces the bias of ocean chlorophyll, most impressively in coastal regions, 2) modestly improves the uncertainty, and 3) reduces the sensitivity of global annual median chlorophyll to changes in radiometric re-calibration. Simulated calibration errors of 1% or less produce small changes in global median chlorophyll (less than 2.7%). In contrast, the standard NASA algorithm set is highly sensitive to radiometric calibration: similar 1% calibration errors produce changes in global median chlorophyll up to nearly 25%. We show that 0.1% radiometric calibration error (about 1% in water-leaving radiance) is needed to prevent radiometric calibration errors from changing global annual median chlorophyll more than the maximum interannual variability observed in the SeaWiFS 9-year record (+/- 3%), using the standard method. This is much more stringent than the goal for SeaWiFS of 5% uncertainty for water leaving radiance. The results suggest ocean color programs might consider less emphasis of expensive efforts to improve post-launch radiometric re-calibration in favor of increased efforts to characterize in situ observations of ocean surface geophysical products. Although the results here are focused on chlorophyll, in principle the approach described by ESRID can be applied to any surface variable potentially observable by visible remote sensing.

Effects of Recent Regional Soil Moisture Variability on Global Net Ecosystem CO2 Exchange

NASA Astrophysics Data System (ADS)

Jones, L. A.; Madani, N.; Kimball, J. S.; Reichle, R. H.; Colliander, A.

2017-12-01

Soil moisture exerts a major regional control on the inter-annual variability of the global land sink for atmospheric CO2. In semi-arid regions, annual biomass production is closely coupled to variability in soil moisture availability, while in cold-season-affected regions, summer drought offsets the effects of advancing spring phenology. Availability of satellite solar-induced fluorescence (SIF) observations and improvements in atmospheric inversions has led to unprecedented ability to monitor atmospheric sink strength. However, discrepancies still exist between such top-down estimates as atmospheric inversion and bottom-up process and satellite driven models, indicating that relative strength, mechanisms, and interaction of driving factors remain poorly understood. We use soil moisture fields informed by Soil Moisture Active Passive Mission (SMAP) observations to compare recent (2015-2017) and historic (2000-2014) variability in net ecosystem land-atmosphere CO2 exchange (NEE). The operational SMAP Level 4 Carbon (L4C) product relates ground-based flux tower measurements to other bottom-up and global top-down estimates to underlying soil moisture and other driving conditions using data-assimilation-based SMAP Level 4 Soil Moisture (L4SM). Droughts in coastal Brazil, South Africa, Eastern Africa, and an anomalous wet period in Eastern Australia were observed by L4C. A seasonal seesaw pattern of below-normal sink strength at high latitudes relative to slightly above-normal sink strength for mid-latitudes was also observed. Whereas SMAP-based soil moisture is relatively informative for short-term temporal variability, soil moisture biases that vary in space and with season constrain the ability of the L4C estimates to accurately resolve NEE. Such biases might be caused by irrigation and plant-accessible ground-water. Nevertheless, SMAP L4C daily NEE estimates connect top-down estimates to variability of effective driving factors for accurate estimates of regional-to-global land-atmosphere CO2 exchange.

Drift-Free Indoor Navigation Using Simultaneous Localization and Mapping of the Ambient Heterogeneous Magnetic Field

NASA Astrophysics Data System (ADS)

Chow, J. C. K.

2017-09-01

In the absence of external reference position information (e.g. surveyed targets or Global Navigation Satellite Systems) Simultaneous Localization and Mapping (SLAM) has proven to be an effective method for indoor navigation. The positioning drift can be reduced with regular loop-closures and global relaxation as the backend, thus achieving a good balance between exploration and exploitation. Although vision-based systems like laser scanners are typically deployed for SLAM, these sensors are heavy, energy inefficient, and expensive, making them unattractive for wearables or smartphone applications. However, the concept of SLAM can be extended to non-optical systems such as magnetometers. Instead of matching features such as walls and furniture using some variation of the Iterative Closest Point algorithm, the local magnetic field can be matched to provide loop-closure and global trajectory updates in a Gaussian Process (GP) SLAM framework. With a MEMS-based inertial measurement unit providing a continuous trajectory, and the matching of locally distinct magnetic field maps, experimental results in this paper show that a drift-free navigation solution in an indoor environment with millimetre-level accuracy can be achieved. The GP-SLAM approach presented can be formulated as a maximum a posteriori estimation problem and it can naturally perform loop-detection, feature-to-feature distance minimization, global trajectory optimization, and magnetic field map estimation simultaneously. Spatially continuous features (i.e. smooth magnetic field signatures) are used instead of discrete feature correspondences (e.g. point-to-point) as in conventional vision-based SLAM. These position updates from the ambient magnetic field also provide enough information for calibrating the accelerometer bias and gyroscope bias in-use. The only restriction for this method is the need for magnetic disturbances (which is typically not an issue for indoor environments); however, no assumptions are required for the general motion of the sensor (e.g. static periods).

An inverter-based capacitive trans-impedance amplifier readout with offset cancellation and temporal noise reduction for IR focal plane array

NASA Astrophysics Data System (ADS)

Chen, Hsin-Han; Hsieh, Chih-Cheng

2013-09-01

This paper presents a readout integrated circuit (ROIC) with inverter-based capacitive trans-impedance amplifier (CTIA) and pseudo-multiple sampling technique for infrared focal plane array (IRFPA). The proposed inverter-based CTIA with a coupling capacitor [1], executing auto-zeroing technique to cancel out the varied offset voltage from process variation, is used to substitute differential amplifier in conventional CTIA. The tunable detector bias is applied from a global external bias before exposure. This scheme not only retains stable detector bias voltage and signal injection efficiency, but also reduces the pixel area as well. Pseudo-multiple sampling technique [2] is adopted to reduce the temporal noise of readout circuit. The noise reduction performance is comparable to the conventional multiple sampling operation without need of longer readout time proportional to the number of samples. A CMOS image sensor chip with 55×65 pixel array has been fabricated in 0.18um CMOS technology. It achieves a 12um×12um pixel size, a frame rate of 72 fps, a power-per-pixel of 0.66uW/pixel, and a readout temporal noise of 1.06mVrms (16 times of pseudo-multiple sampling), respectively.

Exploring the functional nature of synaesthetic colour: Dissociations from colour perception and imagery.

PubMed

Chiou, Rocco; Rich, Anina N; Rogers, Sebastian; Pearson, Joel

2018-08-01

Individuals with grapheme-colour synaesthesia experience anomalous colours when reading achromatic text. These unusual experiences have been said to resemble 'normal' colour perception or colour imagery, but studying the nature of synaesthesia remains difficult. In the present study, we report novel evidence that synaesthetic colour impacts conscious vision in a way that is different from both colour perception and imagery. Presenting 'normal' colour prior to binocular rivalry induces a location-dependent suppressive bias reflecting local habituation. By contrast, a grapheme that evokes synaesthetic colour induces a facilitatory bias reflecting priming that is not constrained to the inducing grapheme's location. This priming does not occur in non-synaesthetes and does not result from response bias. It is sensitive to diversion of visual attention away from the grapheme, but resistant to sensory perturbation, reflecting a reliance on cognitive rather than sensory mechanisms. Whereas colour imagery in non-synaesthetes causes local priming that relies on the locus of imagined colour, imagery in synaesthetes caused global priming not dependent on the locus of imagery. These data suggest a unique psychophysical profile of high-level colour processing in synaesthetes. Our novel findings and method will be critical to testing theories of synaesthesia and visual awareness. Copyright © 2018 Elsevier B.V. All rights reserved.

Are the World's Oceans Optically Different?

NASA Technical Reports Server (NTRS)

Szeto, M.; Werdell, P. J.; Moore, T. S.; Campbell, J. W.

2011-01-01

Regional differences in the Sea-viewing Wide Field-of-view Sensor chlorophyll algorithm uncertainty were observed in a large global data set containing coincident in situ measurements of chlorophyll a concentration (Chla) and spectral radiometry. The uncertainty was found to be systematic when the data were sorted by ocean: Atlantic, Pacific, Southern, and Indian Oceans. Artifacts associated with different instrumentation and analytical methods had been previously ruled out. Given these oceanic biases in the chlorophyll algorithm, we hypothesized that the oceans may be optically different, and their optical differences may be intrinsically related to regional differences in phytoplankton community structure or biogeochemical processes. The oceanic biases, originally observed using radiometric measurements, were independently verified using total absorption measurements in a subset of the data. Moreover, they were explained through oceanic differences in the absorption of colored detrital matter (CDM) and phytoplankton. Both effects were considered together in explaining the ocean biases through a stepwise linear regression analysis. Significant oceanic differences in the amount of CDM and in phytoplankton cell sizes and pigmentation would give rise to optical differences, but we raise a concern for the spatial coverage of the data. We do not suggest the application of ocean-based algorithms but rather emphasize the importance of consolidating regional data sets before reaching this conclusion.

Did hydrographic sampling capture global and regional deep ocean heat content trends accurately between 1990-2010?

NASA Astrophysics Data System (ADS)

Garry, Freya; McDonagh, Elaine; Blaker, Adam; Roberts, Chris; Desbruyères, Damien; King, Brian

2017-04-01

Estimates of heat content change in the deep oceans (below 2000 m) over the last thirty years are obtained from temperature measurements made by hydrographic survey ships. Cruises occupy the same tracks across an ocean basin approximately every 5+ years. Measurements may not be sufficiently frequent in time or space to allow accurate evaluation of total ocean heat content (OHC) and its rate of change. It is widely thought that additional deep ocean sampling will also aid understanding of the mechanisms for OHC change on annual to decadal timescales, including how OHC varies regionally under natural and anthropogenically forced climate change. Here a 0.25˚ ocean model is used to investigate the magnitude of uncertainties and biases that exist in estimates of deep ocean temperature change from hydrographic sections due to their infrequent timing and sparse spatial distribution during 1990 - 2010. Biases in the observational data may be due to lack of spatial coverage (not enough sections covering the basin), lack of data between occupations (typically 5-10 years apart) and due to occupations not closely spanning the time period of interest. Between 1990 - 2010, the modelled biases globally are comparatively small in the abyssal ocean below 3500 m although regionally certain biases in heat flux into the 4000 - 6000 m layer can be up to 0.05 Wm-2. Biases in the heat flux into the deep 2000 - 4000 m layer due to either temporal or spatial sampling uncertainties are typically much larger and can be over 0.1 Wm-2 across an ocean. Overall, 82% of the warming trend below 2000 m is captured by observational-style sampling in the model. However, at 2500 m (too deep for additional temperature information to be inferred from upper ocean Argo) less than two thirds of the magnitude of the global warming trend is obtained, and regionally large biases exist in the Atlantic, Southern and Indian Oceans, highlighting the need for widespread improved deep ocean temperature sampling. In addition to bias due to infrequent sampling, moving the timings of occupations by a few months generates relatively large uncertainty due to intra-annual variability in deep ocean model temperature, further strengthening the case for high temporal frequency observations in the deep ocean (as could be achieved using deep ocean autonomous float technologies). Biases due to different uncertainties can have opposing signs and differ in relative importance both regionally and with depth revealing the importance of reducing all uncertainties (both spatial and temporal) simultaneously in future deep ocean observing design.

Land surface energy budget during dry spells: global CMIP5 AMIP simulations vs. satellite observations

NASA Astrophysics Data System (ADS)

Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Folwell, Sonja S.

2015-04-01

During extended periods without rain (dry spells), the soil can dry out due to vegetation transpiration and soil evaporation. At some point in this drying cycle, land surface conditions change from energy-limited to water-limited evapotranspiration, and this is accompanied by an increase of the ground and overlying air temperatures. Regionally, the characteristics of this transition determine the influence of soil moisture on air temperature and rainfall. Global Climate Models (GCMs) disagree on where and how strongly the surface energy budget is limited by soil moisture. Flux tower observations are improving our understanding of these dry down processes, but typical heterogeneous landscapes are too sparsely sampled to ascertain a representative regional response. Alternatively, satellite observations of land surface temperature (LST) provide indirect information about the surface energy partition at 1km resolution globally. In our study, we analyse how well the dry spell dynamics of LST are represented by GCMs across the globe. We use a spatially and temporally aggregated diagnostic to describe the composite response of LST during surface dry down in rain-free periods in distinct climatic regions. The diagnostic is derived from daytime MODIS-Terra LST observations and bias-corrected meteorological re-analyses, and compared against the outputs of historical climate simulations of seven models running the CMIP5 AMIP experiment. Dry spell events are stratified by antecedent precipitation, land cover type and geographic regions to assess the sensitivity of surface warming rates to soil moisture levels at the onset of a dry spell for different surface and climatic zones. In a number of drought-prone hot spot regions, we find important differences in simulated dry spell behaviour, both between models, and compared to observations. These model biases are likely to compromise seasonal forecasts and future climate projections.

Assessment of terrestrial water contributions to polar motion from GRACE and hydrological models

NASA Astrophysics Data System (ADS)

Jin, S. G.; Hassan, A. A.; Feng, G. P.

2012-12-01

The hydrological contribution to polar motion is a major challenge in explaining the observed geodetic residual of non-atmospheric and non-oceanic excitations since hydrological models have limited input of comprehensive global direct observations. Although global terrestrial water storage (TWS) estimated from the Gravity Recovery and Climate Experiment (GRACE) provides a new opportunity to study the hydrological excitation of polar motion, the GRACE gridded data are subject to the post-processing de-striping algorithm, spatial gridded mapping and filter smoothing effects as well as aliasing errors. In this paper, the hydrological contributions to polar motion are investigated and evaluated at seasonal and intra-seasonal time scales using the recovered degree-2 harmonic coefficients from all GRACE spherical harmonic coefficients and hydrological models data with the same filter smoothing and recovering methods, including the Global Land Data Assimilation Systems (GLDAS) model, Climate Prediction Center (CPC) model, the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis products and European Center for Medium-Range Weather Forecasts (ECMWF) operational model (opECMWF). It is shown that GRACE is better in explaining the geodetic residual of non-atmospheric and non-oceanic polar motion excitations at the annual period, while the models give worse estimates with a larger phase shift or amplitude bias. At the semi-annual period, the GRACE estimates are also generally closer to the geodetic residual, but with some biases in phase or amplitude due mainly to some aliasing errors at near semi-annual period from geophysical models. For periods less than 1-year, the hydrological models and GRACE are generally worse in explaining the intraseasonal polar motion excitations.

Electrochemical force microscopy

DOEpatents

Kalinin, Sergei V.; Jesse, Stephen; Collins, Liam F.; Rodriguez, Brian J.

2017-01-10

A system and method for electrochemical force microscopy are provided. The system and method are based on a multidimensional detection scheme that is sensitive to forces experienced by a biased electrode in a solution. The multidimensional approach allows separation of fast processes, such as double layer charging, and charge relaxation, and slow processes, such as diffusion and faradaic reactions, as well as capturing the bias dependence of the response. The time-resolved and bias measurements can also allow probing both linear (small bias range) and non-linear (large bias range) electrochemical regimes and potentially the de-convolution of charge dynamics and diffusion processes from steric effects and electrochemical reactivity.

High-resolution CSR GRACE RL05 mascons

NASA Astrophysics Data System (ADS)

Save, Himanshu; Bettadpur, Srinivas; Tapley, Byron D.

2016-10-01

The determination of the gravity model for the Gravity Recovery and Climate Experiment (GRACE) is susceptible to modeling errors, measurement noise, and observability issues. The ill-posed GRACE estimation problem causes the unconstrained GRACE RL05 solutions to have north-south stripes. We discuss the development of global equal area mascon solutions to improve the GRACE gravity information for the study of Earth surface processes. These regularized mascon solutions are developed with a 1° resolution using Tikhonov regularization in a geodesic grid domain. These solutions are derived from GRACE information only, and no external model or data is used to inform the constraints. The regularization matrix is time variable and will not bias or attenuate future regional signals to some past statistics from GRACE or other models. The resulting Center for Space Research (CSR) mascon solutions have no stripe errors and capture all the signals observed by GRACE within the measurement noise level. The solutions are not tailored for specific applications and are global in nature. This study discusses the solution approach and compares the resulting solutions with postprocessed results from the RL05 spherical harmonic solutions and other global mascon solutions for studies of Arctic ice sheet processes, ocean bottom pressure variation, and land surface total water storage change. This suite of comparisons leads to the conclusion that the mascon solutions presented here are an enhanced representation of the RL05 GRACE solutions and provide accurate surface-based gridded information that can be used without further processing.

Tropical Convective Responses to Microphysical and Radiative Processes: A Sensitivity Study With a 2D Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Li, Xiao-Fan; Sui, C.-H.; Lau, K.-M.; Tao, W.-K.

2004-01-01

Prognostic cloud schemes are increasingly used in weather and climate models in order to better treat cloud-radiation processes. Simplifications are often made in such schemes for computational efficiency, like the scheme being used in the National Centers for Environment Prediction models that excludes some microphysical processes and precipitation-radiation interaction. In this study, sensitivity tests with a 2D cloud resolving model are carried out to examine effects of the excluded microphysical processes and precipitation-radiation interaction on tropical thermodynamics and cloud properties. The model is integrated for 10 days with the imposed vertical velocity derived from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The experiment excluding the depositional growth of snow from cloud ice shows anomalous growth of cloud ice and more than 20% increase of fractional cloud cover, indicating that the lack of the depositional snow growth causes unrealistically large mixing ratio of cloud ice. The experiment excluding the precipitation-radiation interaction displays a significant cooling and drying bias. The analysis of heat and moisture budgets shows that the simulation without the interaction produces more stable upper troposphere and more unstable mid and lower troposphere than does the simulation with the interaction. Thus, the suppressed growth of ice clouds in upper troposphere and stronger radiative cooling in mid and lower troposphere are responsible for the cooling bias, and less evaporation of rain associated with the large-scale subsidence induces the drying in mid and lower troposphere.

Attachment anxiety moderates the relationship between childhood maltreatment and attention bias for emotion in adults

PubMed Central

Davis, Jennifer S; Fani, Negar; Ressler, Kerry; Jovanovic, Tanja; Tone, Erin B.; Bradley, Bekh

2014-01-01

Research indicates that some individuals who were maltreated in childhood demonstrate biases in social information processing. However, the mechanisms through which these biases develop remain unclear—one possible mechanism is via attachment-related processes. Childhood maltreatment increases risk for insecure attachment. The internal working models of self and others associated with insecure attachment may impact the processing of socially relevant information, particularly emotion conveyed in facial expressions. We investigated associations among child abuse, attachment anxiety and avoidance, and attention biases for emotion in an adult population. Specifically, we examined how self-reported attachment influences the relationship between childhood abuse and attention bias for emotion. A dot probe task consisting of happy, threatening, and neutral female facial stimuli was used to assess possible biases in attention for socially relevant stimuli. Our findings indicate that attachment anxiety moderated the relationship between maltreatment and attention bias for happy emotion; among individuals with a child abuse history, attachment anxiety significantly predicted an attention bias away from happy facial stimuli. PMID:24680873

Selective visual working memory in fear of spiders: the role of automaticity and material-specificity.

PubMed

Reinecke, Andrea; Becker, Eni S; Rinck, Mike

2009-12-01

Following cognitive models of anxiety, biases occur if threat processing is automatic versus strategic. Therefore, most of these models predict attentional bias, but not explicit memory bias. We suggest dividing memory into the highly automatic working memory (WM) component versus long-term memory when investigating bias in anxiety. WM for threat has rarely been investigated although its main function is stimulus monitoring, particularly important in anxiety. We investigated WM for spiders in spider fearfuls (SFs) versus non-anxious controls (NACs). In Experiment 1 (23 SFs/24 NACs), we replicated an earlier WM study, reducing strategic processing options. This led to stronger group differences and, thus, clearer WM threat biases. There were no group differences in Experiment 2 (18 SFs/19 NACs), using snakes instead of spiders to test whether WM biases are material-specific. This article supports cognitive models of anxiety in that biases are more likely to occur when reducing strategic processing. However, it contradicts the assumption that explicit memory biases are not characteristic of anxiety.

Macroecological patterns of sexual size dimorphism in turtles of the world

USGS Publications Warehouse

Agha, Mickey; Ennen, Joshua R.; Nowakowski, A. Justin; Lovich, Jeffrey E.; Sweat, Sarah C.; Todd, Brian D.

2018-01-01

Sexual size dimorphism (SSD) is a well-documented phenomenon in both plants and animals; however, the ecological and evolutionary mechanisms that drive and maintain SSD patterns across geographic space at regional and global scales are understudied, especially for reptiles. Our goal was to examine geographic variation of turtle SSD and to explore ecological and environmental correlates using phylogenetic comparative methods. We use published body size data on 135 species from nine turtle families to examine how geographic patterns and the evolution of SSD are influenced by habitat specialization, climate (annual mean temperature and annual precipitation) and climate variability, latitude, or a combination of these predictor variables. We found that geographic variation, magnitude and direction of turtle SSD are best explained by habitat association, annual temperature variance and annual precipitation. Use of semi-aquatic and terrestrial habitats was associated with male-biased SSD, whereas use of aquatic habitat was associated with female-biased SSD. Our results also suggest that greater temperature variability is associated with female-biased SSD. In contrast, wetter climates are associated with male-biased SSD compared with arid climates that are associated with female-biased SSD. We also show support for a global latitudinal trend in SSD, with females being larger than males towards the poles, especially in the families Emydidae and Geoemydidae. Estimates of phylogenetic signal for both SSD and habitat type indicate that closely related species occupy similar habitats and exhibit similar direction and magnitude of SSD. These global patterns of SSD may arise from sex-specific reproductive behaviour, fecundity and sex-specific responses to environmental factors that differ among habitats and vary systematically across latitude. Thus, this study adds to our current understanding that while SSD can vary dramatically across and within turtle species under phylogenetic constraints, it may be driven, maintained and exaggerated by habitat type, climate and geographic location.

Evaluation of hydrologic components of community land model 4 and bias identification

DOE PAGES

Du, Enhao; Vittorio, Alan Di; Collins, William D.

2015-04-01

Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. Here, we have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties inmore » the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Finally, our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation.« less

Medical journal peer review: process and bias.

PubMed

Manchikanti, Laxmaiah; Kaye, Alan D; Boswell, Mark V; Hirsch, Joshua A

2015-01-01

Scientific peer review is pivotal in health care research in that it facilitates the evaluation of findings for competence, significance, and originality by qualified experts. While the origins of peer review can be traced to the societies of the eighteenth century, it became an institutionalized part of the scholarly process in the latter half of the twentieth century. This was a response to the growth of research and greater subject specialization. With the current increase in the number of specialty journals, the peer review process continues to evolve to meet the needs of patients, clinicians, and policy makers. The peer review process itself faces challenges. Unblinded peer review might suffer from positive or negative bias towards certain authors, specialties, and institutions. Peer review can also suffer when editors and/or reviewers might be unable to understand the contents of the submitted manuscript. This can result in an inability to detect major flaws, or revelations of major flaws after acceptance of publication by the editors. Other concerns include potentially long delays in publication and challenges uncovering plagiarism, duplication, corruption and scientific misconduct. Conversely, a multitude of these challenges have led to claims of scientific misconduct and an erosion of faith. These challenges have invited criticism of the peer review process itself. However, despite its imperfections, the peer review process enjoys widespread support in the scientific community. Peer review bias is one of the major focuses of today's scientific assessment of the literature. Various types of peer review bias include content-based bias, confirmation bias, bias due to conservatism, bias against interdisciplinary research, publication bias, and the bias of conflicts of interest. Consequently, peer review would benefit from various changes and improvements with appropriate training of reviewers to provide quality reviews to maintain the quality and integrity of research without bias. Thus, an appropriate, transparent peer review is not only ideal, but necessary for the future to facilitate scientific progress.

Long-Term Large-Scale Bias-Adjusted Precipitation Estimates at High Spatial and Temporal Resolution Derived from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Precipitation Reanalysis over CONUS

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Seo, D. J.; Kim, B.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over Continental United States (CONUS) is nearly completed for the period covering from 2000 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network - Daily (GHCN-D) are used to adjust for those biases and to merge with the radar only product to provide a multi-sensor estimate. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. After assessing the bias and applying reduction or elimination techniques, we are investigating the kriging method and its variants such as simple kriging (SK), ordinary kriging (OK), and conditional bias-penalized Kriging (CBPK) among others. In addition we hope to generate estimates of uncertainty for the gridded estimate. In this work the methodology is presented as well as a comparison between the radar-only product and the final multi-sensor QPE product. The comparison is performed at various time scales from the sub-hourly, to annual. In addition, comparisons over the same period with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) are provided in order to give a detailed picture of the improvements and remaining challenges.

Dynamics of flows, fluctuations, and global instability under electrode biasing in a linear plasma device

NASA Astrophysics Data System (ADS)

Desjardins, T. R.; Gilmore, M.

2016-05-01

Grid biasing is utilized in a large-scale helicon plasma to modify an existing instability. It is shown both experimentally and with a linear stability analysis to be a hybrid drift-Kelvin-Helmholtz mode. At low magnetic field strengths, coherent fluctuations are present, while at high magnetic field strengths, the plasma is broad-band turbulent. Grid biasing is used to drive the once-coherent fluctuations to a broad-band turbulent state, as well as to suppress them. There is a corresponding change in the flow shear. When a high positive bias (10Te) is applied to the grid electrode, a large-scale ( n ˜/n ≈50 % ) is excited. This mode has been identified as the potential relaxation instability.

Encapsulation of small ionic molecules within alpha-cyclodextrins.

PubMed

Rodriguez, Javier; Elola, M Dolores

2009-02-05

Results from molecular dynamics experiments pertaining to the encapsulation of ClO4- within the hydrophobic cavity of an aqueous alpha-cyclodextrin (alpha-CD) are presented. Using a biased sampling procedure, we constructed the Gibbs free energy profile associated with the complexation process. The profile presents a global minimum at the vicinity of the primary hydroxyl groups, where the ion remains tightly coordinated to four water molecules via hydrogen bonds. Our estimate for the global free energy of encapsulation yields DeltaGenc approximately -2.5 kBT. The decomposition of the average forces acting on the trapped ion reveals that the encapsulation is controlled by Coulomb interactions between the ion and OH groups in the CD, with a much smaller contribution from the solvent molecules. Changes in the previous results, arising from the partial methylation of the host CD and modifications in the charge distribution of the guest molecule are also discussed. The global picture that emerges from our results suggests that the stability of the ClO4- encapsulation involves not only the individual ion but also its first solvation shell.

Is There Room for "Development" in Developmental Models of Information Processing Biases to Threat in Children and Adolescents?

ERIC Educational Resources Information Center

Field, Andy P.; Lester, Kathryn J.

2010-01-01

Clinical and experimental theories assume that processing biases in attention and interpretation are a causal mechanism through which anxiety develops. Despite growing evidence that these processing biases are present in children and, therefore, develop long before adulthood, these theories ignore the potential role of child development. This…

Bias in the Counseling Process: How to Recognize and Avoid It.

ERIC Educational Resources Information Center

Morrow, Kelly A.; Deidan, Cecilia T.

1992-01-01

Notes that counselors' vulnerability to inferential bias during counseling process may result in misdiagnosis and improper interventions. Discusses these inferential biases: availability and representativeness heuristics; fundamental attribution error; anchoring, prior knowledge, and labeling; confirmatory hypothesis testing; and reconstructive…

On the nature of bias and defects in the software specification process

NASA Technical Reports Server (NTRS)

Straub, Pablo A.; Zelkowitz, Marvin V.

1992-01-01

Implementation bias in a specification is an arbitrary constraint in the solution space. This paper describes the problem of bias. Additionally, this paper presents a model of the specification and design processes describing individual subprocesses in terms of precision/detail diagrams and a model of bias in multi-attribute software specifications. While studying how bias is introduced into a specification we realized that software defects and bias are dual problems of a single phenomenon. This was used to explain the large proportion of faults found during the coding phase at the Software Engineering Laboratory at NASA/GSFC.

Facial expression movement enhances the measurement of temporal dynamics of attentional bias in the dot-probe task.

PubMed

Caudek, Corrado; Ceccarini, Francesco; Sica, Claudio

2017-08-01

The facial dot-probe task is one of the most common experimental paradigms used to assess attentional bias toward emotional information. In recent years, however, the psychometric properties of this paradigm have been questioned. In the present study, attentional bias to emotional face stimuli was measured with dynamic and static images of realistic human faces in 97 college students (63 women) who underwent either a positive or a negative mood-induction prior to the experiment. We controlled the bottom-up salience of the stimuli in order to dissociate the top-down orienting of attention from the effects of the bottom-up physical properties of the stimuli. A Bayesian analysis of our results indicates that 1) the traditional global attentional bias index shows a low reliability, 2) reliability increases dramatically when biased attention is analyzed by extracting a series of bias estimations from trial-to-trial (Zvielli, Bernstein, & Koster, 2015), 3) dynamic expression of emotions strengthens biased attention to emotional information, and 4) mood-congruency facilitates the measurement of biased attention to emotional stimuli. These results highlight the importance of using ecologically valid stimuli in attentional bias research, together with the importance of estimating biased attention at the trial level. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of global longitudinal strain using standardized myocardial deformation imaging: a modality independent software approach.

PubMed

Riffel, Johannes H; Keller, Marius G P; Aurich, Matthias; Sander, Yannick; Andre, Florian; Giusca, Sorin; Aus dem Siepen, Fabian; Seitz, Sebastian; Galuschky, Christian; Korosoglou, Grigorios; Mereles, Derliz; Katus, Hugo A; Buss, Sebastian J

2015-07-01

Myocardial deformation measurement is superior to left ventricular ejection fraction in identifying early changes in myocardial contractility and prediction of cardiovascular outcome. The lack of standardization hinders its clinical implementation. The aim of the study is to investigate a novel standardized deformation imaging approach based on the feature tracking algorithm for the assessment of global longitudinal (GLS) and global circumferential strain (GCS) in echocardiography and cardiac magnetic resonance imaging (CMR). 70 subjects undergoing CMR were consecutively investigated with echocardiography within a median time of 30 min. GLS and GCS were analyzed with a post-processing software incorporating the same standardized algorithm for both modalities. Global strain was defined as the relative shortening of the whole endocardial contour length and calculated according to the strain formula. Mean GLS values were -16.2 ± 5.3 and -17.3 ± 5.3 % for echocardiography and CMR, respectively. GLS did not differ significantly between the two imaging modalities, which showed strong correlation (r = 0.86), a small bias (-1.1 %) and narrow 95 % limits of agreement (LOA ± 5.4 %). Mean GCS values were -17.9 ± 6.3 and -24.4 ± 7.8 % for echocardiography and CMR, respectively. GCS was significantly underestimated by echocardiography (p < 0.001). A weaker correlation (r = 0.73), a higher bias (-6.5 %) and wider LOA (± 10.5 %) were observed for GCS. GLS showed a strong correlation (r = 0.92) when image quality was good, while correlation dropped to r = 0.82 with poor acoustic windows in echocardiography. GCS assessment revealed only a strong correlation (r = 0.87) when echocardiographic image quality was good. No significant differences for GLS between two different echocardiographic vendors could be detected. Quantitative assessment of GLS using a standardized software algorithm allows the direct comparison of values acquired irrespective of the imaging modality. GLS may, therefore, serve as a reliable parameter for the assessment of global left ventricular function in clinical routine besides standard evaluation of the ejection fraction.

Information processing biases concurrently and prospectively predict depressive symptoms in adolescents: Evidence from a self-referent encoding task.

PubMed

Connolly, Samantha L; Abramson, Lyn Y; Alloy, Lauren B

2016-01-01

Negative information processing biases have been hypothesised to serve as precursors for the development of depression. The current study examined negative self-referent information processing and depressive symptoms in a community sample of adolescents (N = 291, Mage at baseline = 12.34 ± 0.61, 53% female, 47.4% African-American, 49.5% Caucasian and 3.1% Biracial). Participants completed a computerised self-referent encoding task (SRET) and a measure of depressive symptoms at baseline and completed an additional measure of depressive symptoms nine months later. Several negative information processing biases on the SRET were associated with concurrent depressive symptoms and predicted increases in depressive symptoms at follow-up. Findings partially support the hypothesis that negative information processing biases are associated with depressive symptoms in a nonclinical sample of adolescents, and provide preliminary evidence that these biases prospectively predict increases in depressive symptoms.

Single- and Dual-Process Models of Biased Contingency Detection.

PubMed

Vadillo, Miguel A; Blanco, Fernando; Yarritu, Ion; Matute, Helena

2016-01-01

Decades of research in causal and contingency learning show that people's estimations of the degree of contingency between two events are easily biased by the relative probabilities of those two events. If two events co-occur frequently, then people tend to overestimate the strength of the contingency between them. Traditionally, these biases have been explained in terms of relatively simple single-process models of learning and reasoning. However, more recently some authors have found that these biases do not appear in all dependent variables and have proposed dual-process models to explain these dissociations between variables. In the present paper we review the evidence for dissociations supporting dual-process models and we point out important shortcomings of this literature. Some dissociations seem to be difficult to replicate or poorly generalizable and others can be attributed to methodological artifacts. Overall, we conclude that support for dual-process models of biased contingency detection is scarce and inconclusive.

Assessment of simulation of radiation in NCEP Climate Forecasting System (CFS V2)

NASA Astrophysics Data System (ADS)

Goswami, Tanmoy; Rao, Suryachandra A.; Hazra, Anupam; Chaudhari, Hemantkumar S.; Dhakate, Ashish; Salunke, Kiran; Mahapatra, Somnath

2017-09-01

The objective of this study is to identify and document the radiation biases in the latest National Centers for Environment Prediction (NCEP), Climate Forecasting System (CFSv2) and to investigate the probable reasons for these biases. This analysis is made over global and Indian domain under all-sky and clear-sky conditions. The impact of increasing the horizontal resolution of the atmospheric model on these biases is also investigated by comparing results of two different horizontal resolution versions of CFSv2 namely T126 and T382. The difference between the top of the atmosphere and surface energy imbalance in T126 (T382) is 3.49 (2.78) W/m2. This reduction of bias in the high resolution model is achieved due to lesser low cloud cover, resulting more surface insolation, and due to more latent heat fluxes at the surface. Compared to clear sky simulations, all sky simulations exhibit larger biases suggesting that the cloud covers are not simulated well in the model. The annual mean high level cloud cover is over estimated over the global as well as the Indian domain. This overestimation over the Indian domain is also present during JJAS. There is also evidence that both of the models have insufficient water vapour in their atmosphere. This study suggests that in order to improve the model's mean radiation climatology, simulation of clouds in the model also needs to be improved, and future model development activities should focus on this aspect.

Bias in Estimation of Hippocampal Atrophy using Deformation-Based Morphometry Arises from Asymmetric Global Normalization: An Illustration in ADNI 3 Tesla MRI Data

PubMed Central

Yushkevich, Paul A.; Avants, Brian B.; Das, Sandhitsu R.; Pluta, John; Altinay, Murat; Craige, Caryne

2009-01-01

Measurement of brain change due to neurodegenerative disease and treatment is one of the fundamental tasks of neuroimaging. Deformation-based morphometry (DBM) has been long recognized as an effective and sensitive tool for estimating the change in the volume of brain regions over time. This paper demonstrates that a straightforward application of DBM to estimate the change in the volume of the hippocampus can result in substantial bias, i.e., an overestimation of the rate of change in hippocampal volume. In ADNI data, this bias is manifested as a non-zero intercept of the regression line fitted to the 6 and 12 month rates of hippocampal atrophy. The bias is further confirmed by applying DBM to repeat scans of subjects acquired on the same day. This bias appears to be the result of asymmetry in the interpolation of baseline and followup images during longitudinal image registration. Correcting this asymmetry leads to bias-free atrophy estimation. PMID:20005963

Comparison of codon usage bias across Leishmania and Trypanosomatids to understand mRNA secondary structure, relative protein abundance and pathway functions.

PubMed

Subramanian, Abhishek; Sarkar, Ram Rup

2015-10-01

Understanding the variations in gene organization and its effect on the phenotype across different Leishmania species, and to study differential clinical manifestations of parasite within the host, we performed large scale analysis of codon usage patterns between Leishmania and other known Trypanosomatid species. We present the causes and consequences of codon usage bias in Leishmania genomes with respect to mutational pressure, translational selection and amino acid composition bias. We establish GC bias at wobble position that governs codon usage bias across Leishmania species, rather than amino acid composition bias. We found that, within Leishmania, homogenous codon context coding for less frequent amino acid pairs and codons avoiding formation of folding structures in mRNA are essentially chosen. We predicted putative differences in global expression between genes belonging to specific pathways across Leishmania. This explains the role of evolution in shaping the otherwise conserved genome to demonstrate species-specific function-level differences for efficient survival. Copyright © 2015 Elsevier Inc. All rights reserved.

Development of pile foundation bias factors using observed behavior of platforms during Hurricane Andrew

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aggarwal, R.K.; Litton, R.W.; Cornell, C.A.

1996-12-31

The performance of more than 3,000 offshore platforms in the Gulf of Mexico was observed during the passage of Hurricane Andrew in August 1992. This event provided an opportunity to test the procedures used for platform analysis and design. A global bias was inferred for overall platform capacity and loads in the Andrew Joint Industry Project (JIP) Phase 1. It was predicted that the pile foundations of several platforms should have failed, but did not. These results indicated that the biases specific to foundation failure modes may be higher than those of jacket failure modes. The biases in predictions ofmore » foundation failure modes were therefore investigated further in this study. The work included capacity analysis and calibration of predictions with the observed behavior for 3 jacket platforms and 3 caissons using Bayesian updating. Bias factors for two foundation failure modes, lateral shear and overturning, were determined for each structure. Foundation capacity estimates using conventional methods were found to be conservatively biased overall.« less

Evaluation of normalization methods for cDNA microarray data by k-NN classification

PubMed Central

Wu, Wei; Xing, Eric P; Myers, Connie; Mian, I Saira; Bissell, Mina J

2005-01-01

Background Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Results Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV) classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN), was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect) or intensity-dependent dye bias (referred later as intensity effect) moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Conclusion Using LOOCV error of k-NNs as the evaluation criterion, three double-bias-removal normalization strategies, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, outperform other strategies for removing spatial effect, intensity effect and scale differences from cDNA microarray data. The apparent sensitivity of k-NN LOOCV classification error to dye biases suggests that this criterion provides an informative measure for evaluating normalization methods. All the computational tools used in this study were implemented using the R language for statistical computing and graphics. PMID:16045803

Evaluation of normalization methods for cDNA microarray data by k-NN classification.

PubMed

Wu, Wei; Xing, Eric P; Myers, Connie; Mian, I Saira; Bissell, Mina J

2005-07-26

Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV) classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN), was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect) or intensity-dependent dye bias (referred later as intensity effect) moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Using LOOCV error of k-NNs as the evaluation criterion, three double-bias-removal normalization strategies, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, outperform other strategies for removing spatial effect, intensity effect and scale differences from cDNA microarray data. The apparent sensitivity of k-NN LOOCV classification error to dye biases suggests that this criterion provides an informative measure for evaluating normalization methods. All the computational tools used in this study were implemented using the R language for statistical computing and graphics.

Evaluation of the MACC operational forecast system - potential and challenges of global near-real-time modelling with respect to reactive gases in the troposphere

NASA Astrophysics Data System (ADS)

Wagner, A.; Blechschmidt, A.-M.; Bouarar, I.; Brunke, E.-G.; Clerbaux, C.; Cupeiro, M.; Cristofanelli, P.; Eskes, H.; Flemming, J.; Flentje, H.; George, M.; Gilge, S.; Hilboll, A.; Inness, A.; Kapsomenakis, J.; Richter, A.; Ries, L.; Spangl, W.; Stein, O.; Weller, R.; Zerefos, C.

2015-03-01

Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between -30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between -110 and 40% for NO2 and at most -20% for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterization and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

Galileo FOC Satellite Group Delay Estimation based on Raw Method and published IOV Metadata

NASA Astrophysics Data System (ADS)

Reckeweg, Florian; Schönemann, Erik; Springer, Tim; Enderle, Werner

2017-04-01

In December 2016, the European GNSS Agency (GSA) published the Galileo In-Orbit Validation (IOV) satellite metadata. These metadata include among others the so-called Galileo satellite group delays, which were measured in an absolute sense by the satellite manufacturer on-ground for all three Galileo frequency bands E1, E5 and E6. Therewith Galileo is the first Global Navigation Satellite System (GNSS) for which absolute calibration values for satellite on-board group delays have been published. The different satellite group delays for the three frequency bands lead to the fact that the signals will not be transmitted at exactly the same epoch. Up to now, due to the lack of absolute group delays, it is common practice in GNSS analyses to estimate and apply the differences of these satellite group delays, commonly known as differential code biases (DCBs). However, this has the drawback that the determination of the "raw" clock and the absolute ionosphere is not possible. The use of absolute bias calibrations for satellites and receivers is a major step into the direction of more realistic (in a physical sense) clock and atmosphere estimates. The Navigation Support Office at the European Space Operation Centre (ESOC) was from the beginning involved in the validation process of the Galileo metadata. For the work presented in this presentation we will use the absolute bias calibrations of the Galileo IOV satellites to estimate and validate the absolute receiver group delays of the ESOC GNSS network and vice versa. The receiver group delays have exemplarily been calibrated in a calibration campaign with an IFEN GNSS Signal-Simulator at ESOC. Based on the calibrated network, making use of the ionosphere constraints given by the IOV satellites, GNSS raw observations are processed to estimate satellite group delays for the operational Galileo (Full Operational Capability) FOC satellites. In addition, "raw" satellite clock offsets are estimated, which are free of the ionosphere-free bias, which is inherent to all common satellite clock products, generated with the standard ionosphere-free linear combination processing approach. In the raw observation processing method, developed by the Navigation Support Office at ESOC, no differences or linear combinations of GNSS observations are formed and ionosphere parameters and multi-signal group delay parameters can be jointly estimated by making use of all available code and phase observations on multiple frequencies.

Effect of forest canopy on GPS-based movement data

Treesearch

Nicholas J. DeCesare; John R. Squires; Jay A. Kolbe

2005-01-01

The advancing role of Global Positioning System (GPS) technology in ecology has made studies of animal movement possible for larger and more vagile species. A simple field test revealed that lengths of GPS-based movement data were strongly biased (P<0.001) by effects of forest canopy. Global Positioning System error added an average of 27.5% additional...

Internationalising Colleges of Education through the Dialectic of the Global and the Local? A Perspective and Possible Pathways from the American South

ERIC Educational Resources Information Center

Stevick, E. Doyle; Brown, Kara D.

2016-01-01

Most schooling disproportionately emphasises national affairs at the expense of more global and local phenomena. Students' resulting nation bias can be resituated both internationally and more locally by integrating internationalisation policies with place-based education approaches, which help to illuminate these different levels and,…

Improving long-term global precipitation dataset using multi-sensor surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)

USDA-ARS?s Scientific Manuscript database

Using multiple historical satellite surface soil moisture products, the Kalman Filtering-based Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain g...

Cognitions and emotions in eating disorders.

PubMed

Siep, Nicolette; Jansen, Anita; Havermans, Remco; Roefs, Anne

2011-01-01

The cognitive model of eating disorders (EDs) states that the processing of external and internal stimuli might be biased in mental disorders. These biases, or cognitive errors, systematically distort the individual's experiences and, in that way, maintains the eating disorder. This chapter presents an updated literature review of experimental studies investigating these cognitive biases. Results indicate that ED patients show biases in attention, interpretation, and memory when it comes to the processing of food-, weight-, and body shape-related cues. Some recent studies show that they also demonstrate errors in general cognitive abilities such as set shifting, central coherence, and decision making. A future challenge is whether cognitive biases and processes can be manipulated. Few preliminary studies suggest that an attention retraining and training in the cognitive modulation of food reward processing might be effective strategies to change body satisfaction, food cravings, and eating behavior.

Maritime Continent seasonal climate biases in AMIP experiments of the CMIP5 multimodel ensemble

NASA Astrophysics Data System (ADS)

Toh, Ying Ying; Turner, Andrew G.; Johnson, Stephanie J.; Holloway, Christopher E.

2018-02-01

The fidelity of 28 Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating mean climate over the Maritime Continent in the Atmospheric Model Intercomparison Project (AMIP) experiment is evaluated in this study. The performance of AMIP models varies greatly in reproducing seasonal mean climate and the seasonal cycle. The multi-model mean has better skill at reproducing the observed mean climate than the individual models. The spatial pattern of 850 hPa wind is better simulated than the precipitation in all four seasons. We found that model horizontal resolution is not a good indicator of model performance. Instead, a model's local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon. The comparison with coupled models in CMIP5 shows that AMIP models generally performed better than coupled models in the simulation of the global monsoon and local Hadley circulation but less well at simulating the Maritime Continent annual cycle of precipitation. To characterize model systematic biases in the AMIP runs, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I models are able to capture both the winter monsoon and summer monsoon shift, but they overestimate the precipitation; especially during the JJA and SON seasons. Cluster II models simulate weaker seasonal migration than observed, and the maximum rainfall position stays closer to the equator throughout the year. The tropics-wide properties of these clusters suggest a connection between the skill of simulating global properties of the monsoon circulation and the skill of simulating the regional scale of Maritime Continent precipitation.

Analysis of Soot Propensity in Combustion Processes Using Optical Sensors and Video Magnification

PubMed Central

Fuentes, Andrés; Reszka, Pedro; Carvajal, Gonzalo

2018-01-01

Industrial combustion processes are an important source of particulate matter, causing significant pollution problems that affect human health, and are a major contributor to global warming. The most common method for analyzing the soot emission propensity in flames is the Smoke Point Height (SPH) analysis, which relates the fuel flow rate to a critical flame height at which soot particles begin to leave the reactive zone through the tip of the flame. The SPH and is marked by morphological changes on the flame tip. SPH analysis is normally done through flame observations with the naked eye, leading to high bias. Other techniques are more accurate, but are not practical to implement in industrial settings, such as the Line Of Sight Attenuation (LOSA), which obtains soot volume fractions within the flame from the attenuation of a laser beam. We propose the use of Video Magnification techniques to detect the flame morphological changes and thus determine the SPH minimizing observation bias. We have applied for the first time Eulerian Video Magnification (EVM) and Phase-based Video Magnification (PVM) on an ethylene laminar diffusion flame. The results were compared with LOSA measurements, and indicate that EVM is the most accurate method for SPH determination. PMID:29751625

How trait anxiety, interpretation bias and memory affect acquired fear in children learning about new animals.

PubMed

Field, Zoë C; Field, Andy P

2013-06-01

Cognitive models of vulnerability to anxiety propose that information processing biases such as interpretation bias play a part in the etiology and maintenance of anxiety disorders. However, at present little is known about the role of memory in information processing accounts of child anxiety. The current study investigates the relationships between interpretation biases, memory and fear responses when learning about new stimuli. Children (aged 8-11 years) were presented with ambiguous information regarding a novel animal, and their fear, interpretation bias, and memory for the information was measured. The main findings were: (1) trait anxiety and interpretation bias significantly predicted acquired fear; (2) interpretation bias did not significantly mediate the relationship between trait anxiety and acquired fear; (3) interpretation bias appeared to be a more important predictor of acquired fear than trait anxiety per se; and (4) the relationship between interpretation bias and acquired fear was not mediated by the number of negative memories but was mediated by the number of positive and false-positive memories. The findings suggest that information processing models of child anxiety need to explain the role of positive memory in the formation of fear responses.

Decision-making heuristics and biases across the life span.

PubMed

Strough, Jonell; Karns, Tara E; Schlosnagle, Leo

2011-10-01

We outline a contextual and motivational model of judgment and decision-making (JDM) biases across the life span. Our model focuses on abilities and skills that correspond to deliberative, experiential, and affective decision-making processes. We review research that addresses links between JDM biases and these processes as represented by individual differences in specific abilities and skills (e.g., fluid and crystallized intelligence, executive functioning, emotion regulation, personality traits). We focus on two JDM biases-the sunk-cost fallacy (SCF) and the framing effect. We trace the developmental trajectory of each bias from preschool through middle childhood, adolescence, early adulthood, and later adulthood. We conclude that life-span developmental trajectories differ depending on the bias investigated. Existing research suggests relative stability in the framing effect across the life span and decreases in the SCF with age, including in later life. We highlight directions for future research on JDM biases across the life span, emphasizing the need for process-oriented research and research that increases our understanding of JDM biases in people's everyday lives. © 2011 New York Academy of Sciences.

Cognitive debiasing 1: origins of bias and theory of debiasing.

PubMed

Croskerry, Pat; Singhal, Geeta; Mamede, Sílvia

2013-10-01

Numerous studies have shown that diagnostic failure depends upon a variety of factors. Psychological factors are fundamental in influencing the cognitive performance of the decision maker. In this first of two papers, we discuss the basics of reasoning and the Dual Process Theory (DPT) of decision making. The general properties of the DPT model, as it applies to diagnostic reasoning, are reviewed. A variety of cognitive and affective biases are known to compromise the decision-making process. They mostly appear to originate in the fast intuitive processes of Type 1 that dominate (or drive) decision making. Type 1 processes work well most of the time but they may open the door for biases. Removing or at least mitigating these biases would appear to be an important goal. We will also review the origins of biases. The consensus is that there are two major sources: innate, hard-wired biases that developed in our evolutionary past, and acquired biases established in the course of development and within our working environments. Both are associated with abbreviated decision making in the form of heuristics. Other work suggests that ambient and contextual factors may create high risk situations that dispose decision makers to particular biases. Fatigue, sleep deprivation and cognitive overload appear to be important determinants. The theoretical basis of several approaches towards debiasing is then discussed. All share a common feature that involves a deliberate decoupling from Type 1 intuitive processing and moving to Type 2 analytical processing so that eventually unexamined intuitive judgments can be submitted to verification. This decoupling step appears to be the critical feature of cognitive and affective debiasing.

Process-Oriented Diagnostics of Tropical Cyclones in Global Climate Models

NASA Astrophysics Data System (ADS)

Moon, Y.; Kim, D.; Camargo, S. J.; Wing, A. A.; Sobel, A. H.; Bosilovich, M. G.; Murakami, H.; Reed, K. A.; Vecchi, G. A.; Wehner, M. F.; Zarzycki, C. M.; Zhao, M.

2017-12-01

Simulating tropical cyclone (TC) activity with global climate models (GCMs) remains a challenging problem. While some GCMs are able to simulate TC activity that is in good agreement with the observations, many other models exhibit strong biases. Decreasing horizontal grid spacing of the GCM simulations tends to improve the characteristics of simulated TCs, but this enhancement alone does not necessarily lead to greater skill in simulating TC activity. This study uses process-based diagnostics to identify model characteristics that could explain why some GCM simulations are able to produce more realistic TC activity than others. The diagnostics examine how convection, moisture, clouds and related processes are coupled at individual grid points, which yields useful information into how convective parameterizations interact with resolved model dynamics. These diagnostics share similarities with those originally developed to examine the Madden-Julian Oscillations in climate models. This study will examine TCs in eight different GCM simulations performed at NOAA/GFDL, NCAR and NASA that have different horizontal resolutions and ocean coupling. Preliminary results suggest that stronger TCs are closely associated with greater rainfall - thus greater diabatic heating - in the inner-core regions of the storms, which is consistent with previous theoretical studies. Other storm characteristics that can be used to infer why GCM simulations with comparable horizontal grid spacings produce different TC activity will be examined.

Evaluation of bias in lower and middle tropospheric GOSAT/TANSO-FTS TIR V1.0 CO2 data through comparisons with aircraft and NICAM-TM CO2 data

NASA Astrophysics Data System (ADS)

Saitoh, N.; Hatta, H.; Imasu, R.; Shiomi, K.; Kuze, A.; Niwa, Y.; Machida, T.; Sawa, Y.; Matsueda, H.

2016-12-01

Thermal and Near Infrared Sensor for Carbon Observation (TANSO)-Fourier Transform Spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing carbon dioxide (CO2) concentrations in several atmospheric layers in the thermal infrared (TIR) band since its launch on 23 January 2009. We have compared TANSO-FTS TIR Version 1 (V1) CO2 data from 2010 to 2012 and CO2 data obtained by the Continuous CO2 Measuring Equipment (CME) installed on several JAL aircraft in the framework of the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project to evaluate bias in the TIR CO2 data in the lower and middle troposphere. Here, we have regarded the CME data obtained during the ascent and descent flights over several airports as part of CO2 vertical profiles there. The comparisons showed that the TIR V1 CO2 data had a negative bias against the CME CO2 data; the magnitude of the bias varied depending on season and latitude. We have estimated bias correction values for the TIR V1 lower and middle tropospheric CO2 data in each latitude band from 40°S to 60°N in each season on the basis of the comparisons with the CME CO2 profiles in limited areas over airports, applied the bias correction values to the TIR V1 CO2 data, and evaluated the quality of the bias-corrected TIR CO2 data globally through comparisons with CO2 data taken from the Nonhydrostatic Icosahedral Atmospheric Model (NICAM)-based Transport Model (TM). The bias-corrected TIR CO2 data showed a better agreement with the NICAM-TM CO2 than the original TIR data, which suggests that the bias correction values estimated in the limited areas are basically applicable to global TIR CO2 data. We have compared XCO2 data calculated from both the original and bias-corrected TIR CO2 data with TANSO-FTS SWIR and NICAM-TM XCO2 data; both the TIR XCO2 data agreed with SWIR and NICAM-TM XCO2 data within 1% except over the Sahara desert and strong source and sink regions.

Retrieving vertical ozone profiles from measurements of global spectral irradiance

NASA Astrophysics Data System (ADS)

Bernhard, Germar; Petropavlovskikh, Irina; Mayer, Bernhard

2017-12-01

A new method is presented to determine vertical ozone profiles from measurements of spectral global (direct Sun plus upper hemisphere) irradiance in the ultraviolet. The method is similar to the widely used Umkehr technique, which inverts measurements of zenith sky radiance. The procedure was applied to measurements of a high-resolution spectroradiometer installed near the centre of the Greenland ice sheet. Retrieved profiles were validated with balloon-sonde observations and ozone profiles from the space-borne Microwave Limb Sounder (MLS). Depending on altitude, the bias between retrieval results presented in this paper and MLS observations ranges between -5 and +3 %. The magnitude of this bias is comparable, if not smaller, to values reported in the literature for the standard Dobson Umkehr method. Total ozone columns (TOCs) calculated from the retrieved profiles agree to within 0.7±2.0 % (±1σ) with TOCs measured by the Ozone Monitoring Instrument on board the Aura satellite. The new method is called the Global-Umkehr method.

Assessment of satellite rainfall products over the Andean plateau

NASA Astrophysics Data System (ADS)

Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

2016-01-01

Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a negative bias becomes positive for GSMaP. TMPA-3B42 Adjusted (Adj) version 7 demonstrates the best overall agreement with gauges in terms of correlation, rain rate distribution and bias. However, PERSIANN-Adj's bias in the southern part of the domain is very low.

Connecting to Get Things Done: A Conceptual Model of the Process Used to Respond to Bias Incidents

ERIC Educational Resources Information Center

LePeau, Lucy A.; Morgan, Demetri L.; Zimmerman, Hilary B.; Snipes, Jeremy T.; Marcotte, Beth A.

2016-01-01

In this study, we interviewed victims of bias incidents and members of a bias response team to investigate the process the team used to respond to incidents. Incidents included acts of sexism, homophobia, and racism on a large, predominantly White research university in the Midwest. Data were analyzed using a 4-stage coding process. The emergent…

Sex ratio estimations of loggerhead sea turtle hatchlings at Kuriat islands, Tunisia: can minor nesting sites contribute to compensate globally female-biased sex ratio?

PubMed

Jribi, Imed; Bradai, Mohamed Nejmeddine

2014-01-01

Hatchling sex ratios in the loggerhead turtle Caretta caretta were estimated by placing electronic temperature recorders in seven nests at Kuriat islands (Tunisia) during the 2013 nesting season. Based on the mean temperatures during the middle third of the incubation period, and on incubation duration, the sex ratio of hatchlings at Kuriat islands was highly male-biased. Presently, the majority of hatchling sex ratio studies are focused on major nesting areas, whereby the sex ratios are universally believed to be heavily female-biased. Here we present findings from a minor nesting site in the Mediterranean, where the hatchling sex ratio was found to be male-biased, suggesting a potential difference between major and minor nesting sites.

A statistical characterization of the Galileo-to-GPS inter-system bias

NASA Astrophysics Data System (ADS)

Gioia, Ciro; Borio, Daniele

2016-11-01

Global navigation satellite system operates using independent time scales and thus inter-system time offsets have to be determined to enable multi-constellation navigation solutions. GPS/Galileo inter-system bias and drift are evaluated here using different types of receivers: two mass market and two professional receivers. Moreover, three different approaches are considered for the inter-system bias determination: in the first one, the broadcast Galileo to GPS time offset is used to align GPS and Galileo time scales. In the second, the inter-system bias is included in the multi-constellation navigation solution and is estimated using the measurements available. Finally, an enhanced algorithm using constraints on the inter-system bias time evolution is proposed. The inter-system bias estimates obtained with the different approaches are analysed and their stability is experimentally evaluated using the Allan deviation. The impact of the inter-system bias on the position velocity time solution is also considered and the performance of the approaches analysed is evaluated in terms of standard deviation and mean errors for both horizontal and vertical components. From the experiments, it emerges that the inter-system bias is very stable and that the use of constraints, modelling the GPS/Galileo inter-system bias behaviour, significantly improves the performance of multi-constellation navigation.

Validation of a weather forecast model at radiance level against satellite observations allowing quantification of temperature, humidity, and cloud-related biases

NASA Astrophysics Data System (ADS)

Bani Shahabadi, Maziar; Huang, Yi; Garand, Louis; Heilliette, Sylvain; Yang, Ping

2016-09-01

An established radiative transfer model (RTM) is adapted for simulating all-sky infrared radiance spectra from the Canadian Global Environmental Multiscale (GEM) model in order to validate its forecasts at the radiance level against Atmospheric InfraRed Sounder (AIRS) observations. Synthetic spectra are generated for 2 months from short-term (3-9 h) GEM forecasts. The RTM uses a monthly climatological land surface emissivity/reflectivity atlas. An updated ice particle optical property library was introduced for cloudy radiance calculations. Forward model brightness temperature (BT) biases are assessed to be of the order of ˜1 K for both clear-sky and overcast conditions. To quantify GEM forecast meteorological variables biases, spectral sensitivity kernels are generated and used to attribute radiance biases to surface and atmospheric temperatures, atmospheric humidity, and clouds biases. The kernel method, supplemented with retrieved profiles based on AIRS observations in collocation with a microwave sounder, achieves good closure in explaining clear-sky radiance biases, which are attributed mostly to surface temperature and upper tropospheric water vapor biases. Cloudy-sky radiance biases are dominated by cloud-induced radiance biases. Prominent GEM biases are identified as: (1) too low surface temperature over land, causing about -5 K bias in the atmospheric window region; (2) too high upper tropospheric water vapor, inducing about -3 K bias in the water vapor absorption band; (3) too few high clouds in the convective regions, generating about +10 K bias in window band and about +6 K bias in the water vapor band.

Abnormal functional connectivity of EEG gamma band in patients with depression during emotional face processing.

PubMed

Li, Yingjie; Cao, Dan; Wei, Ling; Tang, Yingying; Wang, Jijun

2015-11-01

This paper evaluates the large-scale structure of functional brain networks using graph theoretical concepts and investigates the difference in brain functional networks between patients with depression and healthy controls while they were processing emotional stimuli. Electroencephalography (EEG) activities were recorded from 16 patients with depression and 14 healthy controls when they performed a spatial search task for facial expressions. Correlations between all possible pairs of 59 electrodes were determined by coherence, and the coherence matrices were calculated in delta, theta, alpha, beta, and gamma bands (low gamma: 30-50Hz and high gamma: 50-80Hz, respectively). Graph theoretical analysis was applied to these matrices by using two indexes: the clustering coefficient and the characteristic path length. The global EEG coherence of patients with depression was significantly higher than that of healthy controls in both gamma bands, especially in the high gamma band. The global coherence in both gamma bands from healthy controls appeared higher in negative conditions than in positive conditions. All the brain networks were found to hold a regular and ordered topology during emotion processing. However, the brain network of patients with depression appeared randomized compared with the normal one. The abnormal network topology of patients with depression was detected in both the prefrontal and occipital regions. The negative bias from healthy controls occurred in both gamma bands during emotion processing, while it disappeared in patients with depression. The proposed work studied abnormally increased connectivity of brain functional networks in patients with depression. By combing the clustering coefficient and the characteristic path length, we found that the brain networks of patients with depression and healthy controls had regular networks during emotion processing. Yet the brain networks of the depressed group presented randomization trends. Moreover, negative bias was detected in the healthy controls during emotion processing, while it was not detected in patients with depression, which might be related to the types of negative stimuli used in this study. The brain networks from both patients with depression and healthy controls were found to hold a regular and ordered topology. Yet the brain networks of patients with depression had randomization trends. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Seasonal evaluation of evapotranspiration fluxes from MODIS satellite and mesoscale model downscaled global reanalysis datasets

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Petropoulos, George P.; Gupta, Manika; Dai, Qiang

2016-04-01

Reference evapotranspiration (ETo) is an important variable in hydrological modeling, which is not always available, especially for ungauged catchments. Satellite data, such as those available from the MODerate Resolution Imaging Spectroradiometer (MODIS), and global datasets via the European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis (ERA) interim and National Centers for Environmental Prediction (NCEP) reanalysis are important sources of information for ETo. This study explored the seasonal performances of MODIS (MOD16) and Weather Research and Forecasting (WRF) model downscaled global reanalysis datasets, such as ERA interim and NCEP-derived ETo, against ground-based datasets. Overall, on the basis of the statistical metrics computed, ETo derived from ERA interim and MODIS were more accurate in comparison to the estimates from NCEP for all the seasons. The pooled datasets also revealed a similar performance to the seasonal assessment with higher agreement for the ERA interim (r = 0.96, RMSE = 2.76 mm/8 days; bias = 0.24 mm/8 days), followed by MODIS (r = 0.95, RMSE = 7.66 mm/8 days; bias = -7.17 mm/8 days) and NCEP (r = 0.76, RMSE = 11.81 mm/8 days; bias = -10.20 mm/8 days). The only limitation with downscaling ERA interim reanalysis datasets using WRF is that it is time-consuming in contrast to the readily available MODIS operational product for use in mesoscale studies and practical applications.

The Diversity-Weighted Living Planet Index: Controlling for Taxonomic Bias in a Global Biodiversity Indicator.

PubMed

McRae, Louise; Deinet, Stefanie; Freeman, Robin

2017-01-01

As threats to species continue to increase, precise and unbiased measures of the impact these pressures are having on global biodiversity are urgently needed. Some existing indicators of the status and trends of biodiversity largely rely on publicly available data from the scientific and grey literature, and are therefore prone to biases introduced through over-representation of well-studied groups and regions in monitoring schemes. This can give misleading estimates of biodiversity trends. Here, we report on an approach to tackle taxonomic and geographic bias in one such indicator (Living Planet Index) by accounting for the estimated number of species within biogeographical realms, and the relative diversity of species within them. Based on a proportionally weighted index, we estimate a global population decline in vertebrate species between 1970 and 2012 of 58% rather than 20% from an index with no proportional weighting. From this data set, comprising 14,152 populations of 3,706 species from 3,095 data sources, we also find that freshwater populations have declined by 81%, marine populations by 36%, and terrestrial populations by 38% when using proportional weighting (compared to trends of -46%, +12% and +15% respectively). These results not only show starker declines than previously estimated, but suggests that those species for which there is poorer data coverage may be declining more rapidly.

The Diversity-Weighted Living Planet Index: Controlling for Taxonomic Bias in a Global Biodiversity Indicator

PubMed Central

Deinet, Stefanie; Freeman, Robin

2017-01-01

As threats to species continue to increase, precise and unbiased measures of the impact these pressures are having on global biodiversity are urgently needed. Some existing indicators of the status and trends of biodiversity largely rely on publicly available data from the scientific and grey literature, and are therefore prone to biases introduced through over-representation of well-studied groups and regions in monitoring schemes. This can give misleading estimates of biodiversity trends. Here, we report on an approach to tackle taxonomic and geographic bias in one such indicator (Living Planet Index) by accounting for the estimated number of species within biogeographical realms, and the relative diversity of species within them. Based on a proportionally weighted index, we estimate a global population decline in vertebrate species between 1970 and 2012 of 58% rather than 20% from an index with no proportional weighting. From this data set, comprising 14,152 populations of 3,706 species from 3,095 data sources, we also find that freshwater populations have declined by 81%, marine populations by 36%, and terrestrial populations by 38% when using proportional weighting (compared to trends of -46%, +12% and +15% respectively). These results not only show starker declines than previously estimated, but suggests that those species for which there is poorer data coverage may be declining more rapidly. PMID:28045977

Impact of DYNAMO observations on NASA GEOS-5 reanalyses and the representation of MJO initiation

NASA Astrophysics Data System (ADS)

Achuthavarier, D.; Wang, H.; Schubert, S. D.; Sienkiewicz, M.

2017-01-01

This study examines the impact of the Dynamics of the Madden-Julian Oscillation (DYNAMO) campaign in situ observations on NASA Goddard Earth Observing System version 5 (GEOS-5) reanalyses and the improvements gained thereby in the representation of the Madden-Julian Oscillation (MJO) initiation processes. To this end, we produced a global, high-resolution (1/4° spatially) reanalysis that assimilates the level-4, quality-controlled DYNAMO upper air soundings from about 87 stations in the equatorial Indian Ocean region along with a companion data-denied control reanalysis. The DYNAMO reanalysis produces a more realistic vertical structure of the temperature and moisture in the central tropical Indian Ocean by correcting the model biases, namely, the cold and dry biases in the lower troposphere and warm bias in the upper troposphere. The reanalysis horizontal winds are substantially improved, in that, the westerly acceleration and vertical shear of the zonal wind are enhanced. The DYNAMO reanalysis shows enhanced low-level diabatic heating, moisture anomalies and vertical velocity during the MJO initiation. Due to the warmer lower troposphere, the deep convection is invigorated, which is evident in convective cloud fraction. The GEOS-5 atmospheric general circulation model (AGCM) employed in the reanalysis is overall successful in assimilating the additional DYNAMO observations, except for an erroneous model response for medium rain rates, between 700 and 600 hPa, reminiscent of a bias in earlier versions of the AGCM. The moist heating profile shows a sharp decrease there due to the excessive convective rain re-evaporation, which is partly offset by the temperature increment produced by the analysis.

Status of Middle Atmosphere-Climate Models: Results SPARC-GRIPS

NASA Technical Reports Server (NTRS)

Pawson, Steven; Kodera, Kunihiko

2003-01-01

The middle atmosphere is an important component of the climate system, primarily because of the radiative forcing of ozone. Middle atmospheric ozone can change, over long times, because of changes in the abundance of anthropogenic pollutants which catalytically destroy it, and because of the temperature sensitivity of kinetic reaction rates. There is thus a complex interaction between ozone, involving chemical and climatic mechanisms. One question of interest is how ozone will change over the next decades , as the "greenhouse-gas cooling" of the middle atmosphere increases but the concentrations of chlorine species decreases (because of policy changes). concerns the climate biases in current middle atmosphere-climate models, especially their ability to simulate the correct seasonal cycle at high latitudes, and the existence of temperature biases in the global mean. A major obstacle when addressing this question This paper will present a summary of recent results from the "GCM-Reality Intercomparison Project for SPARC" (GRIPS) initiative. A set of middle atmosphere-climate models has been compared, identifying common biases. Mechanisms for these biases are being studied in some detail, including off-line assessments of the radiation transfer codes and coordinated studies of the impacts of gravity wave drag due to sub-grid-scale processes. ensemble of models will be presented, along with numerical experiments undertaken with one or more models, designed to investigate the mechanisms at work in the atmosphere. The discussion will focus on dynamical and radiative mechanisms in the current climate, but implications for coupled ozone chemistry and the future climate will be assessed.

Social exclusion in academia through biases in methodological quality evaluation: On the situation of women in science and philosophy.

PubMed

Leuschner, Anna

2015-12-01

Empirical studies show that academia is socially exclusive. I argue that this social exclusion works, at least partly, through the systematic methodological disqualification of contributions from members of underrepresented social groups. As methodological quality criteria are underdetermined their interpretation and weighting can be biased with relation to gender, race, social background, etc. Such biased quality evaluation can take place on a local or global level. The current situation of women in academic philosophy illuminates this. I conclude that only mechanical solutions can effectively change the situation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Looking on the bright side: biased attention and the human serotonin transporter gene.

PubMed

Fox, Elaine; Ridgewell, Anna; Ashwin, Chris

2009-05-22

Humans differ in terms of biased attention for emotional stimuli and these biases can confer differential resilience and vulnerability to emotional disorders. Selective processing of positive emotional information, for example, is associated with enhanced sociability and well-being while a bias for negative material is associated with neuroticism and anxiety. A tendency to selectively avoid negative material might also be associated with mental health and well-being. The neurobiological mechanisms underlying these cognitive phenotypes are currently unknown. Here we show for the first time that allelic variation in the promotor region of the serotonin transporter gene (5-HTTLPR) is associated with differential biases for positive and negative affective pictures. Individuals homozygous for the long allele (LL) showed a marked bias to selectively process positive affective material alongside selective avoidance of negative affective material. This potentially protective pattern was absent among individuals carrying the short allele (S or SL). Thus, allelic variation on a common genetic polymorphism was associated with the tendency to selectively process positive or negative information. The current study is important in demonstrating a genotype-related alteration in a well-established processing bias, which is a known risk factor in determining both resilience and vulnerability to emotional disorders.

Associations of hallucination proneness with free-recall intrusions and response bias in a nonclinical sample.

PubMed

Brébion, Gildas; Larøi, Frank; Van der Linden, Martial

2010-10-01

Hallucinations in patients with schizophrenia have been associated with a liberal response bias in signal detection and recognition tasks and with various types of source-memory error. We investigated the associations of hallucination proneness with free-recall intrusions and false recognitions of words in a nonclinical sample. A total of 81 healthy individuals were administered a verbal memory task involving free recall and recognition of one nonorganizable and one semantically organizable list of words. Hallucination proneness was assessed by means of a self-rating scale. Global hallucination proneness was associated with free-recall intrusions in the nonorganizable list and with a response bias reflecting tendency to make false recognitions of nontarget words in both types of list. The verbal hallucination score was associated with more intrusions and with a reduced tendency to make false recognitions of words. The associations between global hallucination proneness and two types of verbal memory error in a nonclinical sample corroborate those observed in patients with schizophrenia and suggest that common cognitive mechanisms underlie hallucinations in psychiatric and nonclinical individuals.

The Double ITCZ Syndrome in GCMs: A Coupled Problem among Convection, Atmospheric and Ocean Circulations

NASA Astrophysics Data System (ADS)

Zhang, G. J.; Song, X.

2017-12-01

The double ITCZ bias has been a long-standing problem in coupled atmosphere-ocean models. A previous study indicates that uncertainty in the projection of global warming due to doubling of CO2 is closely related to the double ITCZ biases in global climate models. Thus, reducing the double ITCZ biases is not only important to getting the current climate features right, but also important to narrowing the uncertainty in future climate projection. In this work, we will first review the possible factors contributing to the ITCZ problem. Then, we will focus on atmospheric convection, presenting recent progress in alleviating the double ITCZ problem and its sensitivity to details of convective parameterization, including trigger conditions for convection onset, convective memory, entrainment rate, updraft model and closure in the NCAR CESM1. These changes together can result in dramatic improvements in the simulation of ITCZ. Results based on both atmospheric only and coupled simulations with incremental changes of convection scheme will be shown to demonstrate the roles of convection parameterization and coupled interaction between convection, atmospheric circulation and ocean circulation in the simulation of ITCZ.

Manually controlled human balancing using visual, vestibular and proprioceptive senses involves a common, low frequency neural process

PubMed Central

Lakie, Martin; Loram, Ian D

2006-01-01

Ten subjects balanced their own body or a mechanically equivalent unstable inverted pendulum by hand, through a compliant spring linkage. Their balancing process was always characterized by repeated small reciprocating hand movements. These bias adjustments were an observable sign of intermittent alterations in neural output. On average, the adjustments occurred at intervals of ∼400 ms. To generate appropriate stabilizing bias adjustments, sensory information about body or load movement is needed. Subjects used visual, vestibular or proprioceptive sensation alone and in combination to perform the tasks. We first ask, is the time between adjustments (bias duration) sensory specific? Vision is associated with slow responses. Other senses involved with balance are known to be faster. Our second question is; does bias duration depend on sensory abundance? An appropriate bias adjustment cannot occur until unplanned motion is unambiguously perceived (a sensory threshold). The addition of more sensory data should therefore expedite action, decreasing the mean bias adjustment duration. Statistical analysis showed that (1) the mean bias adjustment duration was remarkably independent of the sensory modality and (2) the addition of one or two sensory modalities made a small, but significant, decrease in the mean bias adjustment duration. Thus, a threshold effect can alter only a very minor part of the bias duration. The bias adjustment duration in manual balancing must reflect something more than visual sensation and perceptual thresholds; our suggestion is that it is a common central motor planning process. We predict that similar processes may be identified in the control of standing. PMID:16959857

Single- and Dual-Process Models of Biased Contingency Detection

PubMed Central

2016-01-01

Abstract. Decades of research in causal and contingency learning show that people’s estimations of the degree of contingency between two events are easily biased by the relative probabilities of those two events. If two events co-occur frequently, then people tend to overestimate the strength of the contingency between them. Traditionally, these biases have been explained in terms of relatively simple single-process models of learning and reasoning. However, more recently some authors have found that these biases do not appear in all dependent variables and have proposed dual-process models to explain these dissociations between variables. In the present paper we review the evidence for dissociations supporting dual-process models and we point out important shortcomings of this literature. Some dissociations seem to be difficult to replicate or poorly generalizable and others can be attributed to methodological artifacts. Overall, we conclude that support for dual-process models of biased contingency detection is scarce and inconclusive. PMID:27025532

The Impact of Experiential Avoidance on the Inference of Characters' Emotions: Evidence for an Emotional Processing Bias.

PubMed

Pickett, Scott M; Kurby, Christopher A

2010-12-01

Experiential avoidance is a functional class of maladaptive strategies that contribute to the development and maintenance of psychopathology. Although previous research has demonstrated group differences in the interpretation of aversive stimuli, there is limited work on the influence of experiential avoidance during the online processing of emotion. An experimental design investigated the influence of self-reported experiential avoidance during emotion processing by assessing emotion inferences during the comprehension of narratives that imply different emotions. Results suggest that experiential avoidance is partially characterized by an emotional information processing bias. Specifically, individuals reporting higher experiential avoidance scores exhibited a bias towards activating negative emotion inferences, whereas individuals reporting lower experiential avoidance scores exhibited a bias towards activating positive emotion inferences. Minimal emotional inference was observed for the non-bias affective valence. Findings are discussed in terms of the implications of experiential avoidance as a cognitive vulnerability for psychopathology.

Can CFMIP2 models reproduce the leading modes of cloud vertical structure in the CALIPSO-GOCCP observations?

NASA Astrophysics Data System (ADS)

Wang, Fang; Yang, Song

2018-02-01

Using principal component (PC) analysis, three leading modes of cloud vertical structure (CVS) are revealed by the GCM-Oriented CALIPSO Cloud Product (GOCCP), i.e. tropical high, subtropical anticyclonic and extratropical cyclonic cloud modes (THCM, SACM and ECCM, respectively). THCM mainly reflect the contrast between tropical high clouds and clouds in middle/high latitudes. SACM is closely associated with middle-high clouds in tropical convective cores, few-cloud regimes in subtropical anticyclonic clouds and stratocumulus over subtropical eastern oceans. ECCM mainly corresponds to clouds along extratropical cyclonic regions. Models of phase 2 of Cloud Feedback Model Intercomparison Project (CFMIP2) well reproduce the THCM, but SACM and ECCM are generally poorly simulated compared to GOCCP. Standardized PCs corresponding to CVS modes are generally captured, whereas original PCs (OPCs) are consistently underestimated (overestimated) for THCM (SACM and ECCM) by CFMIP2 models. The effects of CVS modes on relative cloud radiative forcing (RSCRF/RLCRF) (RSCRF being calculated at the surface while RLCRF at the top of atmosphere) are studied in terms of principal component regression method. Results show that CFMIP2 models tend to overestimate (underestimated or simulate the opposite sign) RSCRF/RLCRF radiative effects (REs) of ECCM (THCM and SACM) in unit global mean OPC compared to observations. These RE biases may be attributed to two factors, one of which is underestimation (overestimation) of low/middle clouds (high clouds) (also known as stronger (weaker) REs in unit low/middle (high) clouds) in simulated global mean cloud profiles, the other is eigenvector biases in CVS modes (especially for SACM and ECCM). It is suggested that much more attention should be paid on improvement of CVS, especially cloud parameterization associated with particular physical processes (e.g. downwelling regimes with the Hadley circulation, extratropical storm tracks and others), which may be crucial to reduce the CRF biases in current climate models.

A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mitra, Ashis K.; AghaKouchak, Amir; Liu, Zhong; Norouzi, Hamidreza; Pai, D. S.

2018-01-01

Following the launch of the Global Precipitation Measurement (GPM) Core Observatory, two advanced high resolution multi-satellite precipitation products namely, Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) version 6 are released. A critical evaluation of these newly released precipitation data sets is very important for both the end users and data developers. This study provides a comprehensive assessment of IMERG research product and GSMaP estimates over India at a daily scale for the southwest monsoon season (June to September 2014). The GPM-based precipitation products are inter-compared with widely used TRMM Multi-satellite Precipitation Analysis (TMPA), and gauge-based observations over India. Results show that the IMERG estimates represent the mean monsoon rainfall and its variability more realistically than the gauge-adjusted TMPA and GSMaP data. However, GSMaP has relatively smaller root-mean-square error than IMERG and TMPA, especially over the low mean rainfall regimes and along the west coast of India. An entropy-based approach is employed to evaluate the distributions of the selected precipitation products. The results indicate that the distribution of precipitation in IMERG and GSMaP has been improved markedly, especially for low precipitation rates. IMERG shows a clear improvement in missed and false precipitation bias over India. However, all the three satellite-based rainfall estimates show exceptionally smaller correlation coefficient, larger RMSE, larger negative total bias and hit bias over the northeast India where precipitation is dominated by orographic effects. Similarly, the three satellite-based estimates show larger false precipitation over the southeast peninsular India which is a rain-shadow region. The categorical verification confirms that these satellite-based rainfall estimates have difficulties in detection of rain over the southeast peninsula and northeast India. These preliminary results need to be confirmed in other monsoon seasons in future studies when the fully GPM-based IMERG retrospectively processed data prior to 2014 are available.

Global image registration using a symmetric block-matching approach

PubMed Central

Modat, Marc; Cash, David M.; Daga, Pankaj; Winston, Gavin P.; Duncan, John S.; Ourselin, Sébastien

2014-01-01

Abstract. Most medical image registration algorithms suffer from a directionality bias that has been shown to largely impact subsequent analyses. Several approaches have been proposed in the literature to address this bias in the context of nonlinear registration, but little work has been done for global registration. We propose a symmetric approach based on a block-matching technique and least-trimmed square regression. The proposed method is suitable for multimodal registration and is robust to outliers in the input images. The symmetric framework is compared with the original asymmetric block-matching technique and is shown to outperform it in terms of accuracy and robustness. The methodology presented in this article has been made available to the community as part of the NiftyReg open-source package. PMID:26158035

Bias and design in software specifications

NASA Technical Reports Server (NTRS)

Straub, Pablo A.; Zelkowitz, Marvin V.

1990-01-01

Implementation bias in a specification is an arbitrary constraint in the solution space. Presented here is a model of bias in software specifications. Bias is defined in terms of the specification process and a classification of the attributes of the software product. Our definition of bias provides insight into both the origin and the consequences of bias. It also shows that bias is relative and essentially unavoidable. Finally, we describe current work on defining a measure of bias, formalizing our model, and relating bias to software defects.

Bias modification training can alter approach bias and chocolate consumption.

PubMed

Schumacher, Sophie E; Kemps, Eva; Tiggemann, Marika

2016-01-01

Recent evidence has demonstrated that bias modification training has potential to reduce cognitive biases for attractive targets and affect health behaviours. The present study investigated whether cognitive bias modification training could be applied to reduce approach bias for chocolate and affect subsequent chocolate consumption. A sample of 120 women (18-27 years) were randomly assigned to an approach-chocolate condition or avoid-chocolate condition, in which they were trained to approach or avoid pictorial chocolate stimuli, respectively. Training had the predicted effect on approach bias, such that participants trained to approach chocolate demonstrated an increased approach bias to chocolate stimuli whereas participants trained to avoid such stimuli showed a reduced bias. Further, participants trained to avoid chocolate ate significantly less of a chocolate muffin in a subsequent taste test than participants trained to approach chocolate. Theoretically, results provide support for the dual process model's conceptualisation of consumption as being driven by implicit processes such as approach bias. In practice, approach bias modification may be a useful component of interventions designed to curb the consumption of unhealthy foods. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Causes of Errors in Clinical Reasoning: Cognitive Biases, Knowledge Deficits, and Dual Process Thinking.

PubMed

Norman, Geoffrey R; Monteiro, Sandra D; Sherbino, Jonathan; Ilgen, Jonathan S; Schmidt, Henk G; Mamede, Silvia

2017-01-01

Contemporary theories of clinical reasoning espouse a dual processing model, which consists of a rapid, intuitive component (Type 1) and a slower, logical and analytical component (Type 2). Although the general consensus is that this dual processing model is a valid representation of clinical reasoning, the causes of diagnostic errors remain unclear. Cognitive theories about human memory propose that such errors may arise from both Type 1 and Type 2 reasoning. Errors in Type 1 reasoning may be a consequence of the associative nature of memory, which can lead to cognitive biases. However, the literature indicates that, with increasing expertise (and knowledge), the likelihood of errors decreases. Errors in Type 2 reasoning may result from the limited capacity of working memory, which constrains computational processes. In this article, the authors review the medical literature to answer two substantial questions that arise from this work: (1) To what extent do diagnostic errors originate in Type 1 (intuitive) processes versus in Type 2 (analytical) processes? (2) To what extent are errors a consequence of cognitive biases versus a consequence of knowledge deficits?The literature suggests that both Type 1 and Type 2 processes contribute to errors. Although it is possible to experimentally induce cognitive biases, particularly availability bias, the extent to which these biases actually contribute to diagnostic errors is not well established. Educational strategies directed at the recognition of biases are ineffective in reducing errors; conversely, strategies focused on the reorganization of knowledge to reduce errors have small but consistent benefits.

Contextual cueing in naturalistic scenes: Global and local contexts.

PubMed

Brockmole, James R; Castelhano, Monica S; Henderson, John M

2006-07-01

In contextual cueing, the position of a target within a group of distractors is learned over repeated exposure to a display with reference to a few nearby items rather than to the global pattern created by the elements. The authors contrasted the role of global and local contexts for contextual cueing in naturalistic scenes. Experiment 1 showed that learned target positions transfer when local information is altered but not when global information is changed. Experiment 2 showed that scene-target covariation is learned more slowly when local, but not global, information is repeated across trials than when global but not local information is repeated. Thus, in naturalistic scenes, observers are biased to associate target locations with global contexts. Copyright 2006 APA, all rights reserved.

Effect of driving voltages in dual capacitively coupled radio frequency plasma: A study by nonlinear global model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bora, B., E-mail: bbora@cchen.cl

2015-10-15

On the basis of nonlinear global model, a dual frequency capacitively coupled radio frequency plasma driven by 13.56 MHz and 27.12 MHz has been studied to investigate the influences of driving voltages on the generation of dc self-bias and plasma heating. Fluid equations for the ions inside the plasma sheath have been considered to determine the voltage-charge relations of the plasma sheath. Geometrically symmetric as well as asymmetric cases with finite geometrical asymmetry of 1.2 (ratio of electrodes area) have been considered to make the study more reasonable to experiment. The electrical asymmetry effect (EAE) and finite geometrical asymmetry is found tomore » work differently in controlling the dc self-bias. The amount of EAE has been primarily controlled by the phase angle between the two consecutive harmonics waveforms. The incorporation of the finite geometrical asymmetry in the calculations shift the dc self-bias towards negative polarity direction while increasing the amount of EAE is found to increase the dc self-bias in either direction. For phase angle between the two waveforms ϕ = 0 and ϕ = π/2, the amount of EAE increases significantly with increasing the low frequency voltage, whereas no such increase in the amount of EAE is found with increasing high frequency voltage. In contrast to the geometrically symmetric case, where the variation of the dc self-bias with driving voltages for phase angle ϕ = 0 and π/2 are just opposite in polarity, the variation for the geometrically asymmetric case is different for ϕ = 0 and π/2. In asymmetric case, for ϕ = 0, the dc self-bias increases towards the negative direction with increasing both the low and high frequency voltages, but for the ϕ = π/2, the dc-self bias is increased towards positive direction with increasing low frequency voltage while dc self-bias increases towards negative direction with increasing high frequency voltage.« less

How Pedagogical Blogging Helps Prepare Students for Intercultural Communication in the Global Workplace

ERIC Educational Resources Information Center

Jaidev, Radhika

2014-01-01

Employees in the global workplace must be able to communicate effectively with interlocutors from different cultural backgrounds. To do this, they must be aware of the similarities and differences between their own and other cultures and of cultural biases that they and other people may have. This paper reports on the use of pedagogical blogging…

Susceptibility to Optical Illusions Varies as a Function of the Autism-Spectrum Quotient but Not in Ways Predicted by Local-Global Biases

ERIC Educational Resources Information Center

Chouinard, Philippe A.; Unwin, Katy L.; Landry, Oriane; Sperandio, Irene

2016-01-01

Individuals with autism spectrum disorder and those with autistic tendencies in non-clinical groups are thought to have a perceptual style privileging local details over global integration. We used 13 illusions to investigate this perceptual style in typically developing adults with various levels of autistic traits. Illusory susceptibility was…

Large-Scale Variation in Forest Carbon Turnover Rate and its Relation to Climate - Remote Sensing vs. Global Vegetation Models

NASA Astrophysics Data System (ADS)

Carvalhais, N.; Thurner, M.; Beer, C.; Forkel, M.; Rademacher, T. T.; Santoro, M.; Tum, M.; Schmullius, C.

2015-12-01

While vegetation productivity is known to be strongly correlated to climate, there is a need for an improved understanding of the underlying processes of vegetation carbon turnover and their importance at a global scale. This shortcoming has been due to the lack of spatially extensive information on vegetation carbon stocks, which we recently have been able to overcome by a biomass dataset covering northern boreal and temperate forests originating from radar remote sensing. Based on state-of-the-art products on biomass and NPP, we are for the first time able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests. The implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current global vegetation models. In contrast to our observation-based findings, investigated models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well to observation-based NPP, simulated vegetation carbon stocks are severely biased compared to our biomass dataset. Current limitations lead to considerable uncertainties in the estimated vegetation carbon turnover, contributing substantially to the forest feedback to climate change. Our results are the basis for improving mortality concepts in global vegetation models and estimating their impact on the land carbon balance.

New method for estimating daily global solar radiation over sloped topography in China

NASA Astrophysics Data System (ADS)

Shi, Guoping; Qiu, Xinfa; Zeng, Yan

2018-03-01

A new scheme for the estimation of daily global solar radiation over sloped topography in China is developed based on the Iqbal model C and MODIS cloud fraction. The effects of topography are determined using a digital elevation model. The scheme is tested using observations of solar radiation at 98 stations in China, and the results show that the mean absolute bias error is 1.51 MJ m-2 d-1 and the mean relative absolute bias error is 10.57%. Based on calculations using this scheme, the distribution of daily global solar radiation over slopes in China on four days in the middle of each season (15 January, 15 April, 15 July and 15 October 2003) at a spatial resolution of 1 km × 1 km are analyzed. To investigate the effects of topography on global solar radiation, the results determined in four mountains areas (Tianshan, Kunlun Mountains, Qinling, and Nanling) are discussed, and the typical characteristics of solar radiation over sloped surfaces revealed. In general, the new scheme can produce reasonable characteristics of solar radiation distribution at a high spatial resolution in mountain areas, which will be useful in analyses of mountain climate and planning for agricultural production.

Ocean heat content and ocean energy budget: make better use of historical global subsurface temperature dataset

NASA Astrophysics Data System (ADS)

Cheng, L.; Zhu, J.

2016-02-01

Ocean heat content (OHC) change contributes substantially to global sea level rise, also is a key metric of the ocean/global energy budget, so it is a vital task for the climate research community to estimate historical OHC. While there are large uncertainties regarding its value, here we review the OHC calculation by using the historical global subsurface temperature dataset, and discuss the sources of its uncertainty. The presentation briefly introduces how to correct to the systematic biases in expendable bathythermograph (XBT) data, a alternative way of filling data gaps (which is main focus of this talk), and how to choose a proper climatology. A new reconstruction of historical upper (0-700 m) OHC change will be presented, which is the Institute of Atmospheric Physics (IAP) version of historical upper OHC assessment. The authors also want to highlight the impact of observation system change on OHC calculation, which could lead to bias in OHC estimates. Furthermore, we will compare the updated observational-based estimates on ocean heat content change since 1970s with CMIP5 results. This comparison shows good agreement, increasing the confidence of the climate models in representing the climate history.

Decreasing self-reported cognitive biases and increasing clinical insight through meta-cognitive training in patients with chronic schizophrenia.

PubMed

Gawęda, Łukasz; Krężołek, Martyna; Olbryś, Joanna; Turska, Agnieszka; Kokoszka, Andrzej

2015-09-01

The aim of this study was to assess the impact of meta-cognitive training (MCT) on cognitive biases, symptoms, clinical insight, and general functioning among low-level functioning persons diagnosed with chronic schizophrenia who were attending a daily Community Social Support Group Program; we compared the treatment-as-usual (TAU) condition with the MCT + TAU condition. Forty-four patients diagnosed with chronic schizophrenia were allocated to either the MCT + treatment-as-usual condition or the treatment-as-usual (TAU) condition. Delusion and hallucination severity, cognitive biases, clinical insight, and global functioning were assessed pre- and post-treatment (clinical trial NCT02187692). No significant changes were found in symptom severity as measured with the PSYRATS. Conversely, a medium to large effect size was observed for delusional ideation changes when assessed by the self-report measure (Paranoia Checklist). MCT was found to ameliorate cognitive biases as measured by the self-report scale at large effect size, however, no changes in jumping to conclusions (the Fish Task) and theory of mind deficits ("Reading the Mind in the Eyes" Test) were found in the behavioral tasks. MCT increased insight at large effect size. No changes in global functioning were found between the two conditions. Low intensity intervention. No follow-up assessment was provided. Only PSYRATS was assessed blind to patient allocation. MCT has a beneficial effect on low-functioning chronic schizophrenic patients in ameliorating cognitive biases and increasing clinical insight. Copyright © 2015 Elsevier Ltd. All rights reserved.

Near-Surface PM2.5 Concentrations Derived from Satellites, Simulation and Ground Monitors

NASA Astrophysics Data System (ADS)

van Donkelaar, A.; Martin, R.; Hsu, N. Y. C.; Kahn, R. A.; Levy, R. C.; Lyapustin, A.; Sayer, A. M.; Brauer, M.

2015-12-01

Exposure to fine particulate matter (PM2.5) is globally associated with 3.2 million premature deaths annually. Satellite retrievals of total column aerosol optical depth (AOD) from instruments such as MODIS, MISR and SeaWiFS are related to PM2.5 through local aerosol vertical profiles and optical properties. A globally applicable and geophysically-based AOD to PM2.5 relationship can be calculated from chemical transport model (CTM) simulations. This approach, while effective, ignores the wealth of ground monitoring data that exist in some regions of the world. We therefore use ground monitors to develop a geographically weighted regression (GWR) that predicts the residual bias in geophysically-based satellite-derived PM2.5. Predictors such as the AOD to PM2.5 relationship resolution, land cover type, and chemical composition are used to predict this bias, which can then be used to improve the initial PM2.5 estimates. This approach not only allows for direct bias correction, but also provides insight into factors biasing the initial CTM-derived AOD to PM2.5 relationship. Over North America, we find significant improvement in bias-corrected PM2.5 (r2=0.82 versus r2=0.62), with evidence that fine-scale variability in surface elevation and urban factors are major sources of error in the CTM-derived relationships. Agreement remains high (r2=0.78) even when a large fraction of ground monitors (70%) are withheld from the GWR, suggesting this technique may add value in regions with even sparse ground monitoring networks, and potentially worldwide.

Cognitive debiasing 1: origins of bias and theory of debiasing

PubMed Central

Croskerry, Pat; Singhal, Geeta; Mamede, Sílvia

2013-01-01

Numerous studies have shown that diagnostic failure depends upon a variety of factors. Psychological factors are fundamental in influencing the cognitive performance of the decision maker. In this first of two papers, we discuss the basics of reasoning and the Dual Process Theory (DPT) of decision making. The general properties of the DPT model, as it applies to diagnostic reasoning, are reviewed. A variety of cognitive and affective biases are known to compromise the decision-making process. They mostly appear to originate in the fast intuitive processes of Type 1 that dominate (or drive) decision making. Type 1 processes work well most of the time but they may open the door for biases. Removing or at least mitigating these biases would appear to be an important goal. We will also review the origins of biases. The consensus is that there are two major sources: innate, hard-wired biases that developed in our evolutionary past, and acquired biases established in the course of development and within our working environments. Both are associated with abbreviated decision making in the form of heuristics. Other work suggests that ambient and contextual factors may create high risk situations that dispose decision makers to particular biases. Fatigue, sleep deprivation and cognitive overload appear to be important determinants. The theoretical basis of several approaches towards debiasing is then discussed. All share a common feature that involves a deliberate decoupling from Type 1 intuitive processing and moving to Type 2 analytical processing so that eventually unexamined intuitive judgments can be submitted to verification. This decoupling step appears to be the critical feature of cognitive and affective debiasing. PMID:23882089

A CloudSat Perspective of the Atmospheric Water Cycle and Precipitation: Recent Progress and Grand Challenges

NASA Technical Reports Server (NTRS)

Stephens, Graeme L.; Im, Eastwood; Vane, Deborah

2012-01-01

Summary Global - mean precipitation - is controlled by Earth's energy balance and is a quantifiable consequence of the water vapor feedback. Predictability rests on the degree to which the water vapor feedback is predictable. Regional scale - to a significant extent, changes are shaped by atmospheric circulation changes but we do not know the extent to which regional scale changes are predictable. The impacts of changes to atmospheric circulation on regional scale water cycle changes can be dramatic. Process - scale - significant biases to the CHARACTER of precipitation (frequency and intensity) is related to how the precipitation process is parameterized in models. Aerosol - We still do not know the extent to which the water cycle is influenced by aerosol but anecdotal evidence is building. The character of precipitation is affected by the way aerosol influence clouds and thus affects the forcing of the climate system through the albedo effect. Observations - we still have a way to go and need to approach the problem in a more integrated way (tie clouds, aerosol and precipitation together and then link to soil moisture, etc). Globally our capabilities seriously lag behind the science and model development.

Bias correction of daily satellite precipitation data using genetic algorithm

NASA Astrophysics Data System (ADS)

Pratama, A. W.; Buono, A.; Hidayat, R.; Harsa, H.

2018-05-01

Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) was producted by blending Satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) with Stasion observations data. The blending process was aimed to reduce bias of CHIRP. However, Biases of CHIRPS on statistical moment and quantil values were high during wet season over Java Island. This paper presented a bias correction scheme to adjust statistical moment of CHIRP using observation precipitation data. The scheme combined Genetic Algorithm and Nonlinear Power Transformation, the results was evaluated based on different season and different elevation level. The experiment results revealed that the scheme robustly reduced bias on variance around 100% reduction and leaded to reduction of first, and second quantile biases. However, bias on third quantile only reduced during dry months. Based on different level of elevation, the performance of bias correction process is only significantly different on skewness indicators.

Atypical category processing and hemispheric asymmetries in high-functioning children with autism: revealed through high-density EEG mapping.

PubMed

Fiebelkorn, Ian C; Foxe, John J; McCourt, Mark E; Dumas, Kristina N; Molholm, Sophie

2013-05-01

Behavioral evidence for an impaired ability to group objects based on similar physical or semantic properties in autism spectrum disorders (ASD) has been mixed. Here, we recorded brain activity from high-functioning children with ASD as they completed a visual-target detection task. We then assessed the extent to which object-based selective attention automatically generalized from targets to non-target exemplars from the same well-known object class (e.g., dogs). Our results provide clear electrophysiological evidence that children with ASD (N=17, aged 8-13 years) process the similarity between targets (e.g., a specific dog) and same-category non-targets (SCNT) (e.g., another dog) to a lesser extent than do their typically developing (TD) peers (N=21). A closer examination of the data revealed striking hemispheric asymmetries that were specific to the ASD group. These findings align with mounting evidence in the autism literature of anatomic underconnectivity between the cerebral hemispheres. Years of research in individuals with TD have demonstrated that the left hemisphere (LH) is specialized toward processing local (or featural) stimulus properties and the right hemisphere (RH) toward processing global (or configural) stimulus properties. We therefore propose a model where a lack of communication between the hemispheres in ASD, combined with typical hemispheric specialization, is a root cause for impaired categorization and the oft-observed bias to process local over global stimulus properties. Copyright © 2012 Elsevier Ltd. All rights reserved.

Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes

NASA Technical Reports Server (NTRS)

Chern, Jiun-Dar; Tao, Wei-Kuo; Lang, Stephen E.; Matsui, Toshihisa; Li, J.-L.; Mohr, Karen I.; Skofronick-Jackson, Gail M.; Peters-Lidard, Christa D.

2016-01-01

The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

Adolescents growing up amidst intractable conflict attenuate brain response to pain of outgroup

PubMed Central

Levy, Jonathan; Influs, Moran; Masalha, Shafiq; Zagoory-Sharon, Orna; Feldman, Ruth

2016-01-01

Adolescents’ participation in intergroup conflicts comprises an imminent global risk, and understanding its neural underpinnings may open new perspectives. We assessed Jewish-Israeli and Arab-Palestinian adolescents for brain response to the pain of ingroup/outgroup protagonists using magnetoencephalography (MEG), one-on-one positive and conflictual interactions with an outgroup member, attitudes toward the regional conflict, and oxytocin levels. A neural marker of ingroup bias emerged, expressed via alpha modulations in the somatosensory cortex (S1) that characterized an automatic response to the pain of all protagonists followed by rebound/enhancement to ingroup pain only. Adolescents’ hostile social interactions with outgroup members and uncompromising attitudes toward the conflict influenced this neural marker. Furthermore, higher oxytocin levels in the Jewish-Israeli majority and tighter brain-to-brain synchrony among group members in the Arab-Palestinian minority enhanced the neural ingroup bias. Findings suggest that in cases of intractable intergroup conflict, top-down control mechanisms may block the brain’s evolutionary-ancient resonance to outgroup pain, pinpointing adolescents’ interpersonal and sociocognitive processes as potential targets for intervention. PMID:27849588

Southern Ocean Carbon Dioxide and Oxygen Fluxes Detected by SOCCOM Biogeochemical Profiling Floats

NASA Astrophysics Data System (ADS)

Sarmiento, J. L.; Bushinksy, S.; Gray, A. R.

2016-12-01

The Southern Ocean is known to play an important role in the global carbon cycle, yet historically our measurements of this remote region have been sparse and heavily biased towards summer. Here we present new estimates of air-sea fluxes of carbon dioxide and oxygen calculated with measurements from autonomous biogeochemical profiling floats. At high latitudes in and southward of the Antarctic Circumpolar Current, we find a significant flux of CO2 from the ocean to the atmosphere during 2014-2016, which is particularly enhanced during winter months. These results suggest that previous estimates may be biased towards stronger Southern Ocean CO2 uptake due to undersampling in winter. We examine various implications of having a source of CO2 that is higher than previous estimates. We also find that CO2:O2 flux ratios north of the Subtropical Front are positive, consistent with the fluxes being driven by changes in solubility, while south of the Polar Front biological processes and upwelling of deep water combine to produce a negative CO2:O2 flux ratio.

Adolescents growing up amidst intractable conflict attenuate brain response to pain of outgroup.

PubMed

Levy, Jonathan; Goldstein, Abraham; Influs, Moran; Masalha, Shafiq; Zagoory-Sharon, Orna; Feldman, Ruth

2016-11-29

Adolescents' participation in intergroup conflicts comprises an imminent global risk, and understanding its neural underpinnings may open new perspectives. We assessed Jewish-Israeli and Arab-Palestinian adolescents for brain response to the pain of ingroup/outgroup protagonists using magnetoencephalography (MEG), one-on-one positive and conflictual interactions with an outgroup member, attitudes toward the regional conflict, and oxytocin levels. A neural marker of ingroup bias emerged, expressed via alpha modulations in the somatosensory cortex (S1) that characterized an automatic response to the pain of all protagonists followed by rebound/enhancement to ingroup pain only. Adolescents' hostile social interactions with outgroup members and uncompromising attitudes toward the conflict influenced this neural marker. Furthermore, higher oxytocin levels in the Jewish-Israeli majority and tighter brain-to-brain synchrony among group members in the Arab-Palestinian minority enhanced the neural ingroup bias. Findings suggest that in cases of intractable intergroup conflict, top-down control mechanisms may block the brain's evolutionary-ancient resonance to outgroup pain, pinpointing adolescents' interpersonal and sociocognitive processes as potential targets for intervention.

Beyond assembly bias: exploring secondary halo biases for cluster-size haloes

NASA Astrophysics Data System (ADS)

Mao, Yao-Yuan; Zentner, Andrew R.; Wechsler, Risa H.

2018-03-01

Secondary halo bias, commonly known as `assembly bias', is the dependence of halo clustering on a halo property other than mass. This prediction of the Λ Cold Dark Matter cosmology is essential to modelling the galaxy distribution to high precision and interpreting clustering measurements. As the name suggests, different manifestations of secondary halo bias have been thought to originate from halo assembly histories. We show conclusively that this is incorrect for cluster-size haloes. We present an up-to-date summary of secondary halo biases of high-mass haloes due to various halo properties including concentration, spin, several proxies of assembly history, and subhalo properties. While concentration, spin, and the abundance and radial distribution of subhaloes exhibit significant secondary biases, properties that directly quantify halo assembly history do not. In fact, the entire assembly histories of haloes in pairs are nearly identical to those of isolated haloes. In general, a global correlation between two halo properties does not predict whether or not these two properties exhibit similar secondary biases. For example, assembly history and concentration (or subhalo abundance) are correlated for both paired and isolated haloes, but follow slightly different conditional distributions in these two cases. This results in a secondary halo bias due to concentration (or subhalo abundance), despite the lack of assembly bias in the strict sense for cluster-size haloes. Due to this complexity, caution must be exercised in using any one halo property as a proxy to study the secondary bias due to another property.

Toward a synthesis of cognitive biases: how noisy information processing can bias human decision making.

PubMed

Hilbert, Martin

2012-03-01

A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelated cognitive decision-making biases. During the past 6 decades, hundreds of empirical studies have resulted in a variety of rules of thumb that specify how humans systematically deviate from what is normatively expected from their decisions. Several complementary generative mechanisms have been proposed to explain those cognitive biases. Here it is suggested that (at least) 8 of these empirically detected decision-making biases can be produced by simply assuming noisy deviations in the memory-based information processes that convert objective evidence (observations) into subjective estimates (decisions). An integrative framework is presented to show how similar noise-based mechanisms can lead to conservatism, the Bayesian likelihood bias, illusory correlations, biased self-other placement, subadditivity, exaggerated expectation, the confidence bias, and the hard-easy effect. Analytical tools from information theory are used to explore the nature and limitations that characterize such information processes for binary and multiary decision-making exercises. The ensuing synthesis offers formal mathematical definitions of the biases and their underlying generative mechanism, which permits a consolidated analysis of how they are related. This synthesis contributes to the larger goal of creating a coherent picture that explains the relations among the myriad of seemingly unrelated biases and their potential psychological generative mechanisms. Limitations and research questions are discussed.

Does parental anxiety cause biases in the processing of child-relevant threat material?

PubMed

Cartwright-Hatton, Sam; Abeles, Paul; Dixon, Clare; Holliday, Christine; Hills, Becky

2014-06-01

Anxiety leads to biases in processing personally relevant information. This study set out to examine whether anxious parents also experience biases in processing child-relevant material. Ninety parents acted as a control condition, or received a social anxiety or child-related anxiety induction. They completed a task examining attentional biases in relation to child-threat words and social-threat words, and a task examining ability to categorize emotion in children's faces and voices. There was a trend indicating group differences in attentional bias towards social-threat words, and this appears to have been only in the social anxiety condition, but not the child anxiety or control conditions. For child-threat words, attentional bias was present in the child anxiety condition, but not the social anxiety or control conditions. In the emotion recognition task, there was no difference between the control and child anxiety conditions, but the social anxiety condition were more likely to erroneously label children's faces and voices as sad. Parents' anxious biases may spill over into their child's world. Parents' anxious biases may spill over into their child's world. Anxious parents may have attentional biases towards threats in their children's environment. Anxious parents may over-attribute negative emotion to children. © 2013 The British Psychological Society.

Natural, but not artificial, facial movements elicit the left visual field bias in infant face scanning

PubMed Central

Xiao, Naiqi G.; Quinn, Paul C.; Wheeler, Andrea; Pascalis, Olivier; Lee, Kang

2014-01-01

A left visual field (LVF) bias has been consistently reported in eye movement patterns when adults look at face stimuli, which reflects hemispheric lateralization of face processing and eye movements. However, the emergence of the LVF attentional bias in infancy is less clear. The present study investigated the emergence and development of the LVF attentional bias in infants from 3 to 9 months of age with moving face stimuli. We specifically examined the naturalness of facial movements in infants’ LVF attentional bias by comparing eye movement patterns in naturally and artificially moving faces. Results showed that 3- to 5-month-olds exhibited the LVF attentional bias only in the lower half of naturally moving faces, but not in artificially moving faces. Six- to 9-month-olds showed the LVF attentional bias in both the lower and upper face halves only in naturally moving, but not in artificially moving faces. These results suggest that the LVF attentional bias for face processing may emerge around 3 months of age and is driven by natural facial movements. The LVF attentional bias reflects the role of natural face experience in real life situations that may drive the development of hemispheric lateralization of face processing in infancy. PMID:25064049