Studies of the spin, parity and tensor couplings of the Higgs boson in the , and decay processes at the LHC are presented. The investigations are based on of pp collision data collected by the ATLAS experiment at  TeV and  TeV. The Standard Model (SM) Higgs boson hypothesis, corresponding to the quantum numbers , is tested against several alternative spin scenarios, including non-SM spin-0 and spin-2 models with universal and non-universal couplings to fermions and vector bosons. All tested alternative models are excluded in favour of the SM Higgs boson hypothesis at more than 99.9 % confidence level. Using the and decays, the tensor structure of the interaction between the spin-0 boson and the SM vector bosons is also investigated. The observed distributions of variables sensitive to the non-SM tensor couplings are compatible with the SM predictions and constraints on the non-SM couplings are derived.

This paper reviews and extends searches for the direct pair production of the scalar supersymmetric partners of the top and bottom quarks in proton–proton collisions collected by the ATLAS collaboration during the LHC Run 1. Most of the analyses use 20 of collisions at a centre-of-mass energy of TeV, although in some case an additional of collision data at TeV are used. New analyses are introduced to improve the sensitivity to specific regions of the model parameter space. Since no evidence of third-generation squarks is found, exclusion limits are derived by combining several analyses and are presented in both a simplified model framework, assuming simple decay chains, as well as within the context of more elaborate phenomenological supersymmetric models.

A search is presented for a high-mass Higgs boson in the , , , and decay modes using the ATLAS detector at the CERN Large Hadron Collider. The search uses proton–proton collision data at a centre-of-mass energy of 8 TeV corresponding to an integrated luminosity of 20.3 fb. The results of the search are interpreted in the scenario of a heavy Higgs boson with a width that is small compared with the experimental mass resolution. The Higgs boson mass range considered extends up to for all four decay modes and down to as low as 140 , depending on the decay mode. No significant excess of events over the Standard Model prediction is found. A simultaneous fit to the four decay modes yields upper limits on the production cross-section of a heavy Higgs boson times the branching ratio to  boson pairs. 95 % confidence level upper limits range from 0.53 pb at  GeV to 0.008 pb at  GeV for the gluon-fusion production mode and from 0.31 pb at  GeV to 0.009 pb at  GeV for the vector-boson-fusion production mode. The results are also interpreted in the context of Type-I and Type-II two-Higgs-doublet models.

Abstract. A three-dimensional variational data assimilation (3-DVAR) algorithm for aerosols in a WRF/Chem model is presented. The WRF/Chem model uses the MOSAIC (Model for Simulating Aerosol Interactions and Chemistry) scheme, which explicitly treats eight major species (elemental/black carbon, organic carbon, nitrate, sulfate, chloride, ammonium, sodium and the sum of other inorganic, inert mineral and metal species) and represents size distributions using a sectional method with four size bins. The 3-DVAR scheme is formulated to take advantage of the MOSAIC scheme in providing comprehensive analyses of species concentrations and size distributions. To treat the large number of state variables associated with the MOSAIC scheme, this 3-DVAR algorithm first determines the analysis increments of the total mass concentrations of the eight species, defined as the sum of the mass concentrations across all size bins, and then distributes the analysis increments over four size bins according to the background error variances. The number concentrations for each size bin are adjusted based on the ratios between the mass and number concentrations of the background state. Additional flexibility is incorporated to further lump the eight mass concentrations, and five lumped species are used in the application presented. The system is evaluated using the analysis and prediction of PM2.5 in the Los Angeles basin during the CalNex 2010 field experiment, with assimilation of surface PM2.5 and speciated concentration observations. The results demonstrate that the data assimilation significantly reduces the errors in comparison with a simulation without data assimilation and improved forecasts of the concentrations of PM2.5 as well as individual species for up to 24 h. Some implementation difficulties and limitations of the system are discussed.

Abstract. This paper focuses on three interconnected topics: (1) quantitative relationship between surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo; (2) surface-based approach for measuring cloud albedo; (3) multiscale (diurnal, annual and inter-annual) variations and covariations of surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo. An analytical expression is first derived to quantify the relationship between cloud radiative forcing, cloud fraction, and cloud albedo. The analytical expression is then used to deduce a new approach for inferring cloud albedo from concurrent surfacebased measurements of downwelling surface shortwave radiation and cloud fraction. High-resolution decade-long data on cloud albedos are obtained by use of this surface-based approach over the US Department of Energy's Atmospheric Radiaton Measurement (ARM) Program at the Great Southern Plains (SGP) site. The surface-based cloud albedos are further compared against those derived from the coincident GOES satellite measurements. The three long-term (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)) sets of hourly data on shortwave cloud radiative forcing, cloud fraction and cloud albedo collected over the SGP site are analyzed to explore the multiscale (diurnal, annual and inter-annual) variations and covariations. The analytical formulation is useful for diagnosing deficiencies of cloudradiation parameterizations in climate models.