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Michele M. Rienecker, Max J. Suarez, Ronald Gelaro, Ricardo Todling, Julio Bacmeister, Emily Liu, Michael G. Bosilovich, Siegfried D. Schubert, Lawrence Takacs, Gi-Kong Kim, Stephen Bloom, Junye Chen, Douglas Collins, Austin Conaty, Arlindo da Silva, Wei Gu, Joanna Joiner, Randal D. Koster, Robert Lucchesi, Andrea Molod, Tommy Owens, Steven Pawson, Philip Pegion, Christopher R. Redder, Rolf Reichle, Franklin R. Robertson, Albert G. Ruddick, Meta Sienkiewicz, and Jack Woollen

meteorological forcing fields and surface fluxes over land from MERRA and other reanalyses with satellite estimates and in situ observations from flux towers. Roberts et al. (2011, manuscript submitted to J. Climate ) and Brunke et al. (2011) analyze surface turbulent fluxes over the ocean from MERRA and other data products. Harnik et al. (2011) use MERRA to analyze decadal changes in downward wave coupling between the stratosphere and troposphere. By identifying both the strengths and weaknesses of the

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Hidde Leijnse, Remko Uijlenhoet, and Alexis Berne

, orientation, temperature, and on the wavelength and polarization of the signal. Computations of scattering of electromagnetic waves by particles of arbitrary shapes are carried out here by using Waterman’s T-matrix method (e.g., Waterman 1965 ; Mishchenko et al. 1996 ). This method has been numerically implemented by Mishchenko (2000) , whose code is freely available online (at http://www.giss.nasa.gov/~crmim/t_matrix.html ). From the amplitude scattering matrix produced by this code, the extinction

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Behnjamin J. Zib, Xiquan Dong, Baike Xi, and Aaron Kennedy

ocean–wave model. Several differences were made in data assimilation and observations between the ERA-I and ERA-40 reanalysis. Some of these advances in ERA-I include the use of 12-h 4DVAR, a T255 horizontal resolution, improved model physics, and an improved fast radiative transfer model. ERA-I also utilizes the RRTM for the longwave radiation transfer scheme ( Mlawer et al. 1997 ). A prognostic cloud scheme is implemented in ERA-I in which clouds are assumed to be maximum–random overlapped

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Benjamin A. Schenkel and Robert E. Hart

temperatures (SSTs) were driving changes in power dissipation. In a separate study, data from the ERA-40 were used to estimate the average global oceanic heat transport attributable to TCs ( Sriver and Huber 2007 ). Reanalyses have also been used to correlate TC activity with the strength of the meridional temperature flux during the following winter to indirectly determine whether TCs are significant contributors to atmospheric poleward heat transport ( Hart 2010 ). Truchelut and Hart (2011) utilized

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Aaron D. Kennedy, Xiquan Dong, Baike Xi, Shaocheng Xie, Yunyan Zhang, and Junye Chen

(EOS)—to improve the representation of the earth’s energy and water cycles. GEOS-5 includes the GEOS-5 AGCM and the gridpoint statistical interpolation (GSI) atmospheric analysis developed jointly with the National Oceanic and Atmospheric Administration (NOAA)’s NCEP Environmental Modeling Center (EMC). Incremental analysis update (IAU) technique ( Bloom et al. 1996 ) is incorporated into the GEOS-5 to minimize the 6-hourly shock from the observation input. The model has a native spatial resolution

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