Contribution of mixing to the upward transport across the TTL

During the second part of the TROCCINOX campaign that took place in Brazil in early 2005, chemical species were measured on-board of the high altitude research aircraft Geophysica (ozone, water vapor, NO, NOy, CH4 and CO) in the altitude range up to 20 km (or up to 450 K potential temperature), i.e. spanning the TTL region roughly extending between 350 and 420 K. Analysis of transport across TTL is performed using a new version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). In this new version, the stratospheric model has been extended to the earth surface. Above the tropopause, the isentropic and cross-isentropic advection in CLaMS is driven by ECMWF winds and heating/cooling rates derived from a radiation calculation. Below the tropopause the model smoothly transforms from the isentropic to hybrid-pressure coordinate and, in this way, takes into account the effect of large-scale convective transport as implemented in the ECMWF vertical wind. As with other CLaMS simulations, the irreversible transport, i.e. mixing, is controlled by the local horizontal strain and vertical shear rates. Stratospheric and tropospheric signatures in the TTL can be seen both in the observation and in the model. The composition of air above ≈350 K is mainly controlled by mixing on a time scale of weeks or even months. Based on CLaMS transport studies where mixing can be completely switched off, we deduce that vertical mixing, mainly driven by the vertical shear in the outflow regions of the large-scale convection and in the vicinity of the subtropical jets, is necessary to understand the upward transport of the tropospheric air from the main convective outflow around 350 K up to the tropical tropopause around 380 K. This mechanism is most effective if the outflow of the mesoscale convective systems interacts with the subtropical jets

Contribution of mixing to the upward transport across the TTL

During the second part of the TROCCINOX campaign that took place in Brazil in early 2005, chemical species were measured on-board of the high altitude research aircraft Geophysica (ozone, water vapor, NO, NOy, CH4 and CO) in the altitude range up to 20 km (or up to 450 K potential temperature), i.e. spanning the TTL region roughly extending between 350 and 420 K. Analysis of transport across TTL is performed using a new version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). In this new version, the stratospheric model has been extended to the earth surface. Above the tropopause, the isentropic and cross-isentropic advection in CLaMS is driven by ECMWF winds and heating/cooling rates derived from a radiation calculation. Below the tropopause the model smoothly transforms from the isentropic to hybrid-pressure coordinate and, in this way, takes into account the effect of large-scale convective transport as implemented in the ECMWF vertical wind. As with other CLaMS simulations, the irreversible transport, i.e. mixing, is controlled by the local horizontal strain and vertical shear rates. Stratospheric and tropospheric signatures in the TTL can be seen both in the observation and in the model. The composition of air above ≈350 K is mainly controlled by mixing on a time scale of weeks or even months. Based on CLaMS transport studies where mixing can be completely switched off, we deduce that vertical mixing, mainly driven by the vertical shear in the outflow regions of the large-scale convection and in the vicinity of the subtropical jets, is necessary to understand the upward transport of the tropospheric air from the main convective outflow around 350 K up to the tropical tropopause around 380 K. This mechanism is most effective if the outflow of the mesoscale convective systems interacts with the subtropical jets

Contribution of mixing to upward transport across the tropical tropopause layer (TTL)

During the second part of the TROCCINOX campaign that took place in Brazil in early 2005, chemical species were measured on-board the high-altitude research aircraft Geophysica (ozone, water vapor, NO, NOy, CH4 and CO) in the altitude range up to 20 km (or up to 450 K potential temperature), i.e. spanning the entire TTL region roughly extending between 350 and 420 K. Here, analysis of transport across the TTL is performed using a new version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). In this new version, the stratospheric model has been extended to the earth surface. Above the tropopause, the isentropic and cross-isentropic advection in CLaMS is driven by meteorological analysis winds and heating/cooling rates derived from a radiation calculation. Below the tropopause, the model smoothly transforms from the isentropic to the hybrid-pressure coordinate and, in this way, takes into account the effect of large-scale convective transport as implemented in the vertical wind of the meteorological analysis. As in previous CLaMS simulations, the irreversible transport, i.e. mixing, is controlled by the local horizontal strain and vertical shear rates. Stratospheric and tropospheric signatures in the TTL can be seen both in the observations and in the model. The composition of air above ≈350 K is mainly controlled by mixing on a time scale of weeks or even months. Based on CLaMS transport studies where mixing can be completely switched off, we deduce that vertical mixing, mainly driven by the vertical shear in the tropical flanks of the subtropical jets and, to some extent, in the the outflow regions of the large-scale convection, offers an explanation for the upward transport of trace species from the main convective outflow at around 350 K up to the tropical tropopause around 380 K

Contribution of mixing to the upward transport across the TTL

International audienceDuring the second part of the TROCCINOX campaign that took place in Brazil in early 2005, chemical species were measured on-board of the high altitude research aircraft Geophysica (ozone, water vapor, NO, NOy, CH4 and CO) in the altitude range up to 20 km (or up to 450 K potential temperature), i.e. spanning the TTL region roughly extending between 350 and 420 K. Analysis of transport across TTL is performed using a new version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). In this new version, the stratospheric model has been extended to the earth surface. Above the tropopause, the isentropic and cross-isentropic advection in CLaMS is driven by ECMWF winds and heating/cooling rates derived from a radiation calculation. Below the tropopause the model smoothly transforms from the isentropic to hybrid-pressure coordinate and, in this way, takes into account the effect of large-scale convective transport as implemented in the ECMWF vertical wind. As with other CLaMS simulations, the irreversible transport, i.e. mixing, is controlled by the local horizontal strain and vertical shear rates. Stratospheric and tropospheric signatures in the TTL can be seen both in the observation and in the model. The composition of air above ?350 K is mainly controlled by mixing on a time scale of weeks or even months. Based on CLaMS transport studies where mixing can be completely switched off, we deduce that vertical mixing, mainly driven by the vertical shear in the outflow regions of the large-scale convection and in the vicinity of the subtropical jets, is necessary to understand the upward transport of the tropospheric air from the main convective outflow around 350 K up to the tropical tropopause around 380 K. This mechanism is most effective if the outflow of the mesoscale convective systems interacts with the subtropical jets

Active Control of Acoustic Field-of-View in a Biosonar System

Echolocating bats can actively change the area scanned by their biosonar sensory system (“field of view”), and they do so according to the complexity of the environment and depending on the distance to the target

A Neurocomputational Model of Stimulus-Specific Adaptation to Oddball and Markov Sequences

Stimulus-specific adaptation (SSA) occurs when the spike rate of a neuron decreases with repetitions of the same stimulus, but recovers when a different stimulus is presented. It has been suggested that SSA in single auditory neurons may provide information to change detection mechanisms evident at other scales (e.g., mismatch negativity in the event related potential), and participate in the control of attention and the formation of auditory streams. This article presents a spiking-neuron model that accounts for SSA in terms of the convergence of depressing synapses that convey feature-specific inputs. The model is anatomically plausible, comprising just a few homogeneously connected populations, and does not require organised feature maps. The model is calibrated to match the SSA measured in the cortex of the awake rat, as reported in one study. The effect of frequency separation, deviant probability, repetition rate and duration upon SSA are investigated. With the same parameter set, the model generates responses consistent with a wide range of published data obtained in other auditory regions using other stimulus configurations, such as block, sequential and random stimuli. A new stimulus paradigm is introduced, which generalises the oddball concept to Markov chains, allowing the experimenter to vary the tone probabilities and the rate of switching independently. The model predicts greater SSA for higher rates of switching. Finally, the issue of whether rarity or novelty elicits SSA is addressed by comparing the responses of the model to deviants in the context of a sequence of a single standard or many standards. The results support the view that synaptic adaptation alone can explain almost all aspects of SSA reported to date, including its purported novelty component, and that non-trivial networks of depressing synapses can intensify this novelty response

Fast Detection of Unexpected Sound Intensity Decrements as Revealed by Human Evoked Potentials

The detection of deviant sounds is a crucial function of the auditory system and is reflected by the automatically elicited mismatch negativity (MMN), an auditory evoked potential at 100 to 250 ms from stimulus onset. It has recently been shown that rarely occurring frequency and location deviants in an oddball paradigm trigger a more negative response than standard sounds at very early latencies in the middle latency response of the human auditory evoked potential. This fast and early ability of the auditory system is corroborated by the finding of neurons in the animal auditory cortex and subcortical structures, which restore their adapted responsiveness to standard sounds, when a rare change in a sound feature occurs. In this study, we investigated whether the detection of intensity deviants is also reflected at shorter latencies than those of the MMN. Auditory evoked potentials in response to click sounds were analyzed regarding the auditory brain stem response, the middle latency response (MLR) and the MMN. Rare stimuli with a lower intensity level than standard stimuli elicited (in addition to an MMN) a more negative potential in the MLR at the transition from the Na to the Pa component at circa 24 ms from stimulus onset. This finding, together with the studies about frequency and location changes, suggests that the early automatic detection of deviant sounds in an oddball paradigm is a general property of the auditory system

Neural Processing of Short-Term Recurrence in Songbird Vocal Communication

BACKGROUND: Many situations involving animal communication are dominated by recurring, stereotyped signals. How do receivers optimally distinguish between frequently recurring signals and novel ones? Cortical auditory systems are known to be pre-attentively sensitive to short-term delivery statistics of artificial stimuli, but it is unknown if this phenomenon extends to the level of behaviorally relevant delivery patterns, such as those used during communication. METHODOLOGY/PRINCIPAL FINDINGS: We recorded and analyzed complete auditory scenes of spontaneously communicating zebra finch (Taeniopygia guttata) pairs over a week-long period, and show that they can produce tens of thousands of short-range contact calls per day. Individual calls recur at time scales (median interval 1.5 s) matching those at which mammalian sensory systems are sensitive to recent stimulus history. Next, we presented to anesthetized birds sequences of frequently recurring calls interspersed with rare ones, and recorded, in parallel, action and local field potential responses in the medio-caudal auditory forebrain at 32 unique sites. Variation in call recurrence rate over natural ranges leads to widespread and significant modulation in strength of neural responses. Such modulation is highly call-specific in secondary auditory areas, but not in the main thalamo-recipient, primary auditory area. CONCLUSIONS/SIGNIFICANCE: Our results support the hypothesis that pre-attentive neural sensitivity to short-term stimulus recurrence is involved in the analysis of auditory scenes at the level of delivery patterns of meaningful sounds. This may enable birds to efficiently and automatically distinguish frequently recurring vocalizations from other events in their auditory scene

Computational Models of Auditory Scene Analysis: A Review

Auditory scene analysis (ASA) refers to the process(es) of parsing the complex acoustic input into auditory perceptual objects representing either physical sources or temporal sound patterns, such as melodies, which contributed to the sound waves reaching the ears. A number of new computational models accounting for some of the perceptual phenomena of ASA have been published recently. Here we provide a theoretically motivated review of these computational models, aiming to relate their guiding principles to the central issues of the theoretical framework of ASA. Specifically, we ask how they achieve the grouping and separation of sound elements and whether they implement some form of competition between alternative interpretations of the sound input. We consider the extent to which they include predictive processes, as important current theories suggest that perception is inherently predictive, and also how they have been evaluated. We conclude that current computational models of ASA are fragmentary in the sense that rather than providing general competing interpretations of ASA, they focus on assessing the utility of specific processes (or algorithms) for finding the causes of the complex acoustic signal. This leaves open the possibility for integrating complementary aspects of the models into a more comprehensive theory of ASA