Implementation issues in chemistry and transport models

International audienceOffline chemistry and transport models (CTMs) are versatile tools for studying composition and climate issues requiring multi-decadal simulations. They are computationally fast compared to coupled chemistry climate models, making them well-suited for integrating sensitivity experiments necessary for understanding model performance and interpreting results. The archived meteorological fields used by CTMs can be implemented with lower horizontal or vertical resolution than the original meteorological fields in order to shorten integration time, but the effects of these shortcuts on transport processes must be understood if the CTM is to have credibility. In this paper we present a series of CTM experiments, each differing from another by a single feature of the implementation. Transport effects arising from changes in resolution and model lid height are evaluated using process-oriented diagnostics that intercompare CH4, O3, and age tracer carried in the simulations. Some of the diagnostics used are derived from observations and are shown as a reality check for the model. Processes evaluated include the tropical ascent, tropical-midlatitude exchange, the poleward circulation in the upper stratosphere, and the development of the Antarctic vortex. We find that faithful representation of stratospheric transport in this CTM using Lin and Rood advection is possible with a full mesosphere, ~1 km resolution in the lower stratosphere, and relatively low vertical resolution (>4 km spacing) in the middle stratosphere and above, but lowering the lid from the upper to lower mesosphere leads to less realistic constituent distributions in the upper stratosphere. Ultimately, this affects the polar lower stratosphere, but the effects are greater for the Antarctic than the Arctic. The fidelity of lower stratospheric transport requires realistic tropical and high latitude mixing barriers which are produced at 2°×2.5°, but not lower resolution. At 2°×2.5° resolution, the CTM produces a vortex capable of isolating perturbed chemistry (e.g. high Cly and low NOy) required for simulating polar ozone loss

The Modulation of Apoptotic Pathways by Gammaherpesviruses

Apoptosis or programmed cell death is a tightly regulated process fundamental for cellular development and elimination of damaged or infected cells during the maintenance of cellular homeostasis. It is also an important cellular defense mechanism against viral invasion. In many instances, abnormal regulation of apoptosis has been associated with a number of diseases, including cancer development. Following infection of host cells, persistent and oncogenic viruses such as the members of the Gammaherpesvirus family employ a number of different mechanisms to avoid the host cell’s burglar alarm and to alter the extrinsic and intrinsic apoptotic pathways by either deregulating the expressions of cellular signaling genes or by encoding the viral homologues of cellular genes. In this review, we summarize the recent findings on how gammaherpesviruses inhibit cellular apoptosis via virus-encoded proteins by mediating modification of numerous signal transduction pathways. We also list the key viral anti-apoptotic proteins that could be exploited as effective targets for novel antiviral therapies in order to stimulate apoptosis in different types of cancer cells

Survival Rates Indicate that Correlations Between Community-Weighted Mean Traits and Environments can be Unreliable Estimates of the Adaptive Value of Traits

Correlations between community-weighted mean (CWM) traits and environmental gradients are often assumed to quantify the adaptive value of traits. We tested this assumption by comparing these correlations with models of survival probability using 46 perennial species from long-term permanent plots in pine forests of Arizona. Survival was modeled as a function of trait-by-environment interactions, plant size, climatic variation, and neighborhood competition. The effect of traits on survival depended on the environmental conditions, but the two statistical approaches were inconsistent. For example, CWM specific leaf area (SLA) and soil fertility were uncorrelated. However, survival was highest for species with low SLA in infertile soil, a result which agreed with expectations derived from the physiological tradeoff underpinning leaf economic theory. CWM trait-environment relationships were unreliable estimates of how traits affected survival, and should only be used in predictive models when there is empirical support for an evolutionary tradeoff that affects vital rates

Accurate estimates of dynamical statistics using memory

Many chemical reactions and molecular processes occur on timescales that are significantly longer than those accessible by direct simulation. One successful approach to estimating dynamical statistics for such processes is to use many short time series observations of the system to construct a Markov state model (MSM), which approximates the dynamics of the system as memoryless transitions between a set of discrete states. The dynamical Galerkin approximation (DGA) generalizes MSMs for the problem of calculating dynamical statistics, such as committors and mean first passage times, by replacing the set of discrete states with a projection onto a basis. Because the projected dynamics are generally not memoryless, the Markov approximation can result in significant systematic error. Inspired by quasi-Markov state models, which employ the generalized master equation to encode memory resulting from the projection, we reformulate DGA to account for memory and analyze its performance on two systems: a two-dimensional triple well and helix-to-helix transitions of the AIB$_9$ peptide. We demonstrate that our method is robust to the choice of basis and can decrease the time series length required to obtain accurate kinetics by an order of magnitude.Comment: 17 pages, 14 figure

Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction

Understanding dynamics in complex systems is challenging because there are many degrees of freedom, and those that are most important for describing events of interest are often not obvious. The leading eigenfunctions of the transition operator are useful for visualization, and they can provide an efficient basis for computing statistics such as the likelihood and average time of events (predictions). Here we develop inexact iterative linear algebra methods for computing these eigenfunctions (spectral estimation) and making predictions from a data set of short trajectories sampled at finite intervals. We demonstrate the methods on a low-dimensional model that facilitates visualization and a high-dimensional model of a biomolecular system. Implications for the prediction problem in reinforcement learning are discussed.Comment: 27 pages, 16 figure

The Sensitivity of Arctic Ozone Loss to Polar Stratospheric Cloud Volume and Chlorine and Bromine Loading in a Chemistry and Transport Model

The sensitivity of Arctic ozone loss to polar stratospheric cloud volume (V(sub PSC)) and chlorine and bromine loading is explored using chemistry and transport models (CTMs). A simulation using multi-decadal output from a general circulation model (GCM) in the Goddard Space Flight Center (GSFC) CTM complements one recycling a single year s GCM output in the Global Modeling Initiative (GMI) CTM. Winter polar ozone loss in the GSFC CTM depends on equivalent effective stratospheric chlorine (EESC) and polar vortex characteristics (temperatures, descent, isolation, polar stratospheric cloud amount). Polar ozone loss in the GMI CTM depends only on changes in EESC as the dynamics repeat annually. The GSFC CTM simulation reproduces a linear relationship between ozone loss and Vpsc derived from observations for 1992 - 2003 which holds for EESC within approx.85% of its maximum (approx.1990 - 2020). The GMI simulation shows that ozone loss varies linearly with EESC for constant, high V(sub PSC)

Modeling the Frozen-In Anticyclone in the 2005 Arctic Summer Stratosphere

Immediately following the breakup of the 2005 Arctic spring stratospheric vortex, a tropical air mass, characterized by low potential vorticity (PV) and high nitrous oxide (N2O), was advected poleward and became trapped in the easterly summer polar vortex. This feature, known as a "Frozen-In Anticyclone (FrIAC)", was observed in Earth Observing System (EOS) Aura Microwave Limb Sounder (MLS) data to span the potential temperature range from approximately 580 to 1100 K (approximately 25 to 40 km altitude) and to persist from late March to late August 2005. This study compares MLS N2O observations with simulations from the Global Modeling Initiative (GMI) chemistry and transport model, the GEOS-5/MERRA Replay model, and the VanLeer Icosahedral Triangular Advection isentropic transport model to elucidate the processes involved in the lifecycle of the FrIAC which is here divided into three distinct phases. During the "spin-up phase" (March to early April), strong poleward flow resulted in a tight isolated anticyclonic vortex at approximately 70-90 deg N, marked with elevated N2O. GMI, Replay, and VITA all reliably simulted the spin-up of the FrIAC, although the GMI and Replay peak N2O values were too low. The FrIAC became trapped in the developing summer easterly flow and circulated around the polar region during the "anticyclonic phase" (early April to the end of May). During this phase, the FrIAC crossed directly over the pole between the 7th and 14th of April. The VITA and Replay simulations transported the N2O anomaly intact during this crossing, in agreement with MLS, but unrealistic dispersion of the anomaly occurred in the GMI simulation due to excessive numerical mixing of the polar cap. The vortex associated with the FrIAC was apparently resistant to the weak vertical hear during the anticyclonic phase, and it thereby protected the embedded N20 anomaly from stretching. The vortex decayed in late May due to diabatic processes, leaving the N2O anomaly exposed to horizontal and vertical wind shears during the "shearing phase" (June to August). The observed lifetime of the FrIAC during this phase is consistent with time-scales calculated from the ambient horizontal and vertical wind shear. Replay maintained the horizontal structure of the N2O anomaly similar to NILS well into August. The VITA simulation also captured the horizontal structure of the FrIAC during this phase, but VITA eventually developed fine-scale N2O structure not observed in MLS data

Multi-model simulations of the impact of international shipping on Atmospheric Chemistry and Climate in 2000 and 2030

The global impact of shipping on atmospheric chemistry and radiative forcing, as well as the associated uncertainties, have been quantified using an ensemble of ten state-of-the-art atmospheric chemistry models and a predefined set of emission data. The analysis is performed for present-day conditions ( year 2000) and for two future ship emission scenarios. In one scenario ship emissions stabilize at 2000 levels; in the other ship emissions increase with a constant annual growth rate of 2.2% up to 2030 ( termed the "Constant Growth Scenario" (CGS)). Most other anthropogenic emissions follow the IPCC ( Intergovernmental Panel on Climate Change) SRES ( Special Report on Emission Scenarios) A2 scenario, while biomass burning and natural emissions remain at year 2000 levels. An intercomparison of the model results with observations over the Northern Hemisphere (25 degrees - 60 degrees N) oceanic regions in the lower troposphere showed that the models are capable to reproduce ozone (O-3) and nitrogen oxides (NOx= NO+ NO2) reasonably well, whereas sulphur dioxide (SO2) in the marine boundary layer is significantly underestimated. The most pronounced changes in annual mean tropospheric NO2 and sulphate columns are simulated over the Baltic and North Seas. Other significant changes occur over the North Atlantic, the Gulf of Mexico and along the main shipping lane from Europe to Asia, across the Red and Arabian Seas. Maximum contributions from shipping to annual mean near-surface O-3 are found over the North Atlantic ( 5 - 6 ppbv in 2000; up to 8 ppbv in 2030). Ship contributions to tropospheric O3 columns over the North Atlantic and Indian Oceans reach 1 DU in 2000 and up to 1.8 DU in 2030. Tropospheric O-3 forcings due to shipping are 9.8 +/- 2.0 mW/m(2) in 2000 and 13.6 +/- 2.3 mW/m(2) in 2030. Whilst increasing O-3, ship NOx simultaneously enhances hydroxyl radicals over the remote ocean, reducing the global methane lifetime by 0.13 yr in 2000, and by up to 0.17 yr in 2030, introducing a negative radiative forcing. The models show future increases in NOx and O-3 burden which scale almost linearly with increases in NOx emission totals. Increasing emissions from shipping would significantly counteract the benefits derived from reducing SO2 emissions from all other anthropogenic sources under the A2 scenario over the continents, for example in Europe. Globally, shipping contributes 3% to increases in O-3 burden between 2000 and 2030, and 4.5% to increases in sulphate under A2/CGS. However, if future ground based emissions follow a more stringent scenario, the relative importance of ship emissions will increase. Inter-model differences in the simulated O-3 contributions from ships are significantly smaller than estimated uncertainties stemming from the ship emission inventory, mainly the ship emission totals, the distribution of the emissions over the globe, and the neglect of ship plume dispersion