Chemical transport model ozone simulations for spring 2001 over the western Pacific: Regional ozone production and its global impacts

The spatial and temporal variation in ozone production over major source regions in East Asia during the NASA Transport and Chemical Evolution over the Pacific (TRACE-P) measurement campaign in spring 2001 is assessed using a global chemical transport model. There is a strong latitudinal gradient in ozone production in springtime, driven by regional photochemistry, which rapidly diminishes as the season progresses. The great variability in meteorological conditions characteristic of East Asia in springtime leads to large daily variability in regional ozone formation, but we find that it has relatively little impact on the total global production. We note that transport processes effectively modulate and thus stabilize total ozone production through their influence over its location. However, the impact on the global ozone burden, important for assessing the effects of precursor emissions on tropospheric oxidizing capacity and climate, is sensitive to local meteorology through the effects of location on chemical lifetime. Stagnant, anticyclonic conditions conducive to substantial boundary layer ozone production typically allow little lifting of precursors into the free troposphere where greater ozone production could occur, and the consequent shorter chemical lifetime for ozone leads to relatively small impacts on global ozone. Conversely, cyclonic conditions with heavy cloud cover suppressing regional ozone production are often associated with substantial cloud convection, enhancing subsequent production in the free troposphere where chemical lifetimes are longer, and the impacts on global ozone are correspondingly greater. We find that ozone formation in the boundary layer and free troposphere outside the region of precursor emissions dominates total gross production from these sources in springtime, and that it makes a big contribution to the long range transport of ozone, which is greatest in this season

Global tropospheric ozone modelling:quantifying errors due to grid resolution.

Ozone production in global chemical models is dependent on model resolution because ozone chemistry is inherently nonlinear, the timescales for chemical production are short, and precursors are artificially distributed over the spatial scale of the model grid. In this study we examine the sensitivity of ozone, its precursors, and its production to resolution by running a global chemical transport model at four different resolutions between T21 (5.6° × 5.6°) and T106 (1.1° × 1.1°) and by quantifying the errors in regional and global budgets. The sensitivity to vertical mixing through the parameterization of boundary layer turbulence is also examined. We find less ozone production in the boundary layer at higher resolution, consistent with slower chemical production in polluted emission regions and greater export of precursors. Agreement with ozonesonde and aircraft measurements made during the NASA TRACE-P campaign over the western Pacific in spring 2001 is consistently better at higher resolution. We demonstrate that the numerical errors in transport processes on a given resolution converge geometrically for a tracer at successively higher resolutions. The convergence in ozone production on progressing from T21 to T42, T63, and T106 resolution is likewise monotonic but indicates that there are still large errors at 120 km scales, suggesting that T106 resolution is too coarse to resolve regional ozone production. Diagnosing the ozone production and precursor transport that follow a short pulse of emissions over east Asia in springtime allows us to quantify the impacts of resolution on both regional and global ozone. Production close to continental emission regions is overestimated by 27% at T21 resolution, by 13% at T42 resolution, and by 5% at T106 resolution. However, subsequent ozone production in the free troposphere is not greatly affected. We find that the export of short-lived precursors such as NO x by convection is overestimated at coarse resolution

Chemical nonlinearities in relating intercontinental ozone pollution to anthropogenic emissions

Model studies typically estimate intercontinental influence on surface ozone by perturbing emissions from a source continent and diagnosing the ozone response in the receptor continent. Since the response to perturbations is non-linear due to chemistry, conclusions drawn from different studies may depend on the magnitude of the applied perturbation. We investigate this issue for intercontinental transport between North America, Europe, and Asia with sensitivity simulations in three global chemical transport models. In each region, we decrease anthropogenic emissions of NOx and nonmethane volatile organic compounds (NMVOCs) by 20% and 100%. We find strong nonlinearity in the response to NOx perturbations outside summer, reflecting transitions in the chemical regime for ozone production. In contrast, we find no significant nonlinearity to NOx perturbations in summer or to NMVOC perturbations year-round. The relative benefit of decreasing NOx vs. NMVOC from current levels to abate intercontinental pollution increases with the magnitude of emission reductions

Chemical nonlinearities in relating intercontinental ozone pollution to anthropogenic emissions

Model studies typically estimate intercontinental influence on surface ozone by perturbing emissions from a source continent and diagnosing the ozone response in the receptor continent. Since the response to perturbations is non-linear due to chemistry, conclusions drawn from different studies may depend on the magnitude of the applied perturbation. We investigate this issue for intercontinental transport between North America, Europe, and Asia with sensitivity simulations in three global chemical transport models. In each region, we decrease anthropogenic emissions of NOx and nonmethane volatile organic compounds (NMVOCs) by 20% and 100%. We find strong nonlinearity in the response to NOx perturbations outside summer, reflecting transitions in the chemical regime for ozone production. In contrast, we find no significant nonlinearity to NOx perturbations in summer or to NMVOC perturbations year-round. The relative benefit of decreasing NOx vs. NMVOC from current levels to abate intercontinental pollution increases with the magnitude of emission reductions

Finding the saddlepoint faster than sorting

A saddlepoint of an $n \times n$ matrix $A$ is an entry of $A$ that is a maximum in its row and a minimum in its column. Knuth (1968) gave several different algorithms for finding a saddlepoint. The worst-case running time of these algorithms is $\Theta(n^2)$, and Llewellyn, Tovey, and Trick (1988) showed that this cannot be improved, as in the worst case all entries of A may need to be queried. A strict saddlepoint of $A$ is an entry that is the strict maximum in its row and the strict minimum in its column. The strict saddlepoint (if it exists) is unique, and Bienstock, Chung, Fredman, Sch\"affer, Shor, and Suri (1991) showed that it can be found in time $O(n \log{n})$, where a dominant runtime contribution is sorting the diagonal of the matrix. This upper bound has not been improved since 1991. In this paper we show that the strict saddlepoint can be found in $O(n \log^{*}{n})$ time, where $\log^{*}$ denotes the very slowly growing iterated logarithm function, coming close to the lower bound of $\Omega(n)$. In fact, we can also compute, within the same runtime, the value of a non-strict saddlepoint, assuming one exists. Our algorithm is based on a simple recursive approach, a feasibility test inspired by searching in sorted matrices, and a relaxed notion of saddlepoint.Comment: To be presented at SOSA 202

Behavioral variation across the days and lives of honey bees

In honey bee colonies, workers generally change tasks with age (from brood care, to nest work, to foraging). While these trends are well established, our understanding of how individuals distribute tasks during a day, and how individuals differ in their lifetime behavioral trajectories, is limited. Here, we use automated tracking to obtain long-term data on 4,100+ bees tracked continuously at 3 Hz, across an entire summer, and use behavioral metrics to compare behavior at different timescales. Considering single days, we describe how bees differ in space use, detection, and movement. Analyzing the behavior exhibited across their entire lives, we find consistent inter-individual differences in the movement characteristics of individuals. Bees also differ in how quickly they transition through behavioral space to ultimately become foragers, with fast-transitioning bees living the shortest lives. Our analysis framework provides a quantitative approach to describe individual behavioral variation within a colony from single days to entire lifetimes

Finding the saddlepoint faster than sorting

A saddlepoint of an $n \times n$ matrix $A$ is an entry of $A$ that is a maximum in its row and a minimum in its column. Knuth (1968) gave several different algorithms for finding a saddlepoint. The worst-case running time of these algorithms is $\Theta(n^2)$, and Llewellyn, Tovey, and Trick (1988) showed that this cannot be improved, as in the worst case all entries of A may need to be queried. A strict saddlepoint of $A$ is an entry that is the strict maximum in its row and the strict minimum in its column. The strict saddlepoint (if it exists) is unique, and Bienstock, Chung, Fredman, Sch\"affer, Shor, and Suri (1991) showed that it can be found in time $O(n \log{n})$, where a dominant runtime contribution is sorting the diagonal of the matrix. This upper bound has not been improved since 1991. In this paper we show that the strict saddlepoint can be found in $O(n \log^{*}{n})$ time, where $\log^{*}$ denotes the very slowly growing iterated logarithm function, coming close to the lower bound of $\Omega(n)$. In fact, we can also compute, within the same runtime, the value of a non-strict saddlepoint, assuming one exists. Our algorithm is based on a simple recursive approach, a feasibility test inspired by searching in sorted matrices, and a relaxed notion of saddlepoint

How honeybees respond to heat stress from the individual to colony level

A honey bee colony functions as an integrated collective, with individuals coordinating their behaviour to adapt and respond to unexpected disturbances. Nest homeostasis is critical for colony function; when ambient temperatures increase, individuals switch to thermoregulatory roles to cool the nest, such as fanning and water collection. While prior work has focused on bees engaged in specific behaviours, less is known about how responses are coordinated at the colony level, and how previous tasks predict behavioural changes during a heat stress. Using BeesBook automated tracking, we follow thousands of individuals during an experimentally induced heat stress, and analyse their behavioural changes from the individual to colony level. We show that heat stress causes an overall increase in activity levels and a spatial reorganization of bees away from the brood area. Using a generalized framework to analyse individual behaviour, we find that individuals differ in their response to heat stress, which depends on their prior behaviour and correlates with age. Examining the correlation of behavioural metrics over time suggests that heat stress perturbation does not have a long-lasting effect on an individual’s future behaviour. These results demonstrate how thousands of individuals within a colony change their behaviour to achieve a coordinated response to an environmental disturbance