Journal of Advances in Modeling Earth Systems

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Regular Articles
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  Combined evaluation of MPI-ESM land surface water and energy fluxes
  Stefan Hagemann, Alexander Loew and A. Andersson
  Article first published online: 17 MAY 2013 | DOI: 10.1029/2012MS000173
  Key Points
  MPI-ESM has considerably improved surface SW radiation fluxes compared to ECHAM5
  Coupling to ocean model leads to improved precipitation over Ganges/B.catchment
  MPI-ESM is suited for climate change studies on land surface water/energy fluxes
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  Marine low cloud sensitivity to an idealized climate change: The CGILS LES intercomparison
  Peter N. Blossey, Christopher S. Bretherton, Minghua Zhang, Anning Cheng, Satoshi Endo, Thijs Heus, Yangang Liu, Adrian P. Lock, Stephan R. de Roode and Kuan-Man Xu
  Article first published online: 14 MAY 2013 | DOI: 10.1002/jame.20025
  Key Points
  Marine low cloud sensitivity to an idealized climate change is studied
  The models do not show consistent cloud changes in the perturbed climate
  Low cloud feedbacks involve cancellation between different effects of warming
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  Paths to accuracy for radiation parameterizations in atmospheric models
  Robert Pincus and Bjorn Stevens
  Article first published online: 6 MAY 2013 | DOI: 10.1002/jame.20027
  Key Points
  Radiation is usually computed infrequently in models, which limits accuracy
  An alternative is spectrally-sparse, temporally dense calculations
  Teams of spectral points are needed to limit errors in surface radiation fluxes
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  A China data set of soil properties for land surface modeling
  Wei Shangguan, Yongjiu Dai, Baoyuan Liu, Axing Zhu, Qingyun Duan, Lizong Wu, Duoying Ji, Aizhong Ye, Hua Yuan, Qian Zhang, Dongdong Chen, Ming Chen, Jianting Chu, Youjun Dou, Jianxia Guo, Haiqin Li, Junjia Li, Lu Liang, Xiao Liang, Heping Liu, Shuyan Liu, Chiyuan Miao and Yizhou Zhang
  Article first published online: 6 MAY 2013 | DOI: 10.1002/jame.20026
  Key Points
  A soil characteristics dataset of China was developed for land modeling
  A soil attribute database of China, comprising 8979 soil profiles, was developed
  The polygon linkage method was used to derive the spatial distribution of soils
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  Atmospheric component of the MPI-M Earth System Model: ECHAM6
  Bjorn Stevens, Marco Giorgetta, Monika Esch, Thorsten Mauritsen, Traute Crueger, Sebastian Rast, Marc Salzmann, Hauke Schmidt, Jürgen Bader, Karoline Block, Renate Brokopf, Irina Fast, Stefan Kinne, Luis Kornblueh, Ulrike Lohmann, Robert Pincus, Thomas Reichler and Erich Roeckner
  Article first published online: 18 APR 2013 | DOI: 10.1002/jame.20015
  Key Points
  To describe ECHAM6, as it was configured for participation in CMIP5
  To describe the climate of ECHAM6
  To describe the climate sensitivity of ECHAM6
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  A simplified PDF parameterization of subgrid-scale clouds and turbulence for cloud-resolving models
  Peter A. Bogenschutz and Steven K. Krueger
  Article first published online: 18 APR 2013 | DOI: 10.1002/jame.20018
  Key Points
  Simplified PDF parameter just as good as predictive
  New turbulence length scale functions well for boundary layer clouds
  Better representation of boundary layer clouds
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  Arctic sea-ice evolution as modeled by Max Planck Institute for Meteorology's Earth system model
  Dirk Notz, F. Alexander Haumann, Helmuth Haak, Johann H. Jungclaus and Jochem Marotzke
  Article first published online: 18 APR 2013 | DOI: 10.1002/jame.20016
  Key Points
  Simulations of Arctic sea ice with MPI-ESM agree well with observations
  Estimates of sea-ice volume trends depend on choice of atmospheric reanalysis
  Modeled sea-ice evolution significantly lags behind CO2 concentration changes
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  Hurricanes in an aquaplanet world: Implications of the impacts of external forcing and model horizontal resolution
  Fuyu Li, William D. Collins, Michael F. Wehner and L. Ruby Leung
  Article first published online: 2 APR 2013 | DOI: 10.1002/jame.20020
  Key Points
  Horizontal resolution impacts the simulation of hurricanes
  Analyzing scale is more important than the model horizontal resolution
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  Why is it so difficult to represent stably stratified conditions in numerical weather prediction (NWP) models?
  Irina Sandu, Anton Beljaars, Peter Bechtold, Thorsten Mauritsen and Gianpaolo Balsamo
  Article first published online: 2 APR 2013 | DOI: 10.1002/jame.20013
  Key Points
  some NWP models use excessive diffusion in stable conditions
  reducing turbulent diffusion improves stable boundary layers
  enhanced diffusion helps offsetting errors due to other processes