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Register a new userIonization in the atmosphere, comparison between measurements and simulations
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A survey of the data on measured particle fluxes and the rate of ionization in the atmosphere is presented. Measurements as a function of altitude, time and cut-off rigidity are compared with simulations of particle production from cosmic rays. The simulations generally give a reasonable representation of the data. However, some discrepancies are found. The solar modulation of the particle fluxes is measured and found to be a factor 2.7$pm$0.8 greater than that observed for muons alone near sea level.
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We present the results of full new calculation of radiocarbon 14C production in the Earth atmosphere, using a numerical Monte-Carlo model. We provide, for the first time, a tabulated 14C yield function for the energy of primary cosmic ray particles ranging from 0.1 to 1000 GeV/nucleon. We have calculated the global production rate of 14C, which is 1.64 and 1.88 atoms/cm2/s for the modern time and for the pre-industrial epoch, respectively. This is close to the values obtained from the carbon cycle reservoir inventory. We argue that earlier models overestimated the global 14C production rate because of outdated spectra of cosmic ray heavier nuclei. The mean contribution of solar energetic particles to the global 14C is calculated as about 0.25% for the modern epoch. Our model provides a new tool to calculate the 14C production in the Earths atmosphere, which can be applied, e.g., to reconstructions of solar activity in the past.
A new framework is proposed for the evaluation of stochastic subgrid-scale parameterizations in the context of MAOOAM, a coupled ocean-atmosphere model of intermediate complexity. Two physically-based parameterizations are investigated, the first one based on the singular perturbation of Markov operator, also known as homogenization. The second one is a recently proposed parameterization based on the Ruelles response theory. The two parameterization are implemented in a rigorous way, assuming however that the unresolved scale relevant statistics are Gaussian. They are extensively tested for a low-order version known to exhibit low-frequency variability, and some preliminary results are obtained for an intermediate-order version. Several different configurations of the resolved-unresolved scale separations are then considered. Both parameterizations show remarkable performances in correcting the impact of model errors, being even able to change the modality of the probability distributions. Their respective limitations are also discussed.
In 2017, AWAKE demonstrated the seeded self-modulation (SSM) of a 400 GeV proton beam from the Super Proton Synchrotron (SPS) at CERN. The angular distribution of the protons deflected due to SSM is a quantitative measure of the process, which agrees with simulations by the two-dimensional (axisymmetric) particle-in-cell code LCODE. Agreement is achieved for beam populations between $10^{11}$ and $3 times 10^{11}$ particles, various plasma density gradients ($-20 div 20%$) and two plasma densities ($2times 10^{14} text{cm}^{-3}$ and $7 times 10^{14} text{cm}^{-3}$). The agreement is reached only in the case of a wide enough simulation box (at least five plasma wavelengths).
This paper explores the potential of Local Ensemble Transform Kalman Filter (LETKF) by comparing the performance of LETKF with an operational 3D-Var assimilation system, Physical-Space Statistical Analysis System (PSAS), under a perfect model scenario. The comparison is carried out on the finite volume Global Circulation Model (fvGCM) with 72 grid points zonally, 46 grid points meridionally and 55 vertical levels. With only forty ensemble members, LETKF obtains an analysis and forecasts with lower RMS errors than those from PSAS. The performance of LETKF is further improved, especially over the oceans, by assimilating simulated temperature observations from rawinsondes and conventional surface pressure observations instead of geopotential heights. An initial decrease of the forecast errors in the NH observed in PSAS but not in LETKF suggests that the PSAS analysis is less balanced. The observed advantage of LETKF over PSAS is due to the ability of the forty-member ensemble from LETKF to capture flow-dependent errors and thus create a good estimate of the true background uncertainty. Furthermore, localization makes LETKF highly parallel and efficient, requiring only 5 minutes per analysis in a cluster of 20 PCs with forty ensemble members.
Simulation results are presented from a new general circulation model (GCM) of Titan, the Titan Atmospheric Model (TAM), which couples the Flexible Modeling System (FMS) spectral dynamical core to a suite of external/sub-grid-scale physics. These include a new non-gray radiative transfer module that takes advantage of recent data from Cassini-Huygens, large-scale condensation and quasi-equilibrium moist convection schemes, a surface model with bucket hydrology, and boundary layer turbulent diffusion. The model produces a realistic temperature structure from the surface to the lower mesosphere, including a stratopause, as well as satisfactory superrotation. The latter is shown to depend on the dynamical cores ability to build up angular momentum from surface torques. Simulated latitudinal temperature contrasts are adequate, compared to observations, and polar temperature anomalies agree with observations. In the lower atmosphere, the insolation distribution is shown to strongly impact turbulent fluxes, and surface heating is maximum at mid-latitudes. Surface liquids are unstable at mid- and low-latitudes, and quickly migrate poleward. The simulated humidity profile and distribution of surface temperatures, compared to observations, corroborate the prevalence of dry conditions at low latitudes. Polar cloud activity is well represented, though the observed mid-latitude clouds remain somewhat puzzling, and some formation alternatives are suggested.
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