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> Publications for CloudSat
Publication Citation
Deng, M.
,
J. Mace
, and
Z. Wang
(2016),
Anvil Productivities of Tropical Deep Convective Clusters and Their Regional Differences
,
J. Atmos. Sci., 73
, 3467-3487, doi:10.1175/JAS-D-15-0239.1.
Desmons, M.,
et al.
(2013),
Improved information about the vertical location and extent of monolayer clouds from POLDER3 measurements in the oxygen A-band
,
Atmos. Meas. Tech., 6
, 2221-2238, doi:10.5194/amt-6-2221-2013.
Devasthale, A.
, and M. A. Thomas (2012),
Sensitivity of Cloud Liquid Water Content Estimates to the Temperature-Dependent Thermodynamic Phase: A Global Study Using CloudSat Data
,
J. Climate, 25
, 7297-7307, doi:10.1175/JCLI-D-11-00521.1.
Di Giuseppe, F., and A. M. Tompkins (2015),
Generalizing Cloud Overlap Treatment to Include the Effect of Wind Shear
,
J. Atmos. Sci., 72
, 2865-2876, doi:10.1175/JAS-D-14-0277.1.
Di Michele, S.
,
et al.
(2012),
Interpreting an evaluation of the ECMWF global model with CloudSat observations: ambiguities due to radar reflectivity forward operator uncertainties
,
Q. J. R. Meteorol. Soc., 138
, 2047-2065.
Díaz, J. P.,
et al.
(2015),
WRF multi-physics simulation of clouds in the African region
,
Q. J. R. Meteorol. Soc., 141
, 2737-2749, doi:10.1002/qj.2560.
Doan, K.,
et al.
(2014),
Performance Comparison of Big-Data Technologies in Locating Intersections in Satellite Ground Tracks
,
Conference, Harvard University, December, 2014
, 14-16.
Dodson, J. B., D. A. Randall, and
K. Suzuki
(2013),
Comparison of observed and simulated tropical cumuliform clouds by CloudSat and NICAM
,
J. Geophys. Res., 118
, 1852-1867, doi:10.1002/jgrd.50121.
Dolinar, E. K.,
et al.
(2015),
Evaluation of CMIP5 simulated clouds and TOA radiation budgets using NASA satellite observations
,
Clim. Dyn., 44
, 2229-2247, doi:10.1007/s00382-014-2158-9.
Dongmei, X., T. Auligné, and X. Huang (2015),
A Validation of the Multivariate and Minimum Residual Method for Cloud Retrieval Using Radiance from Multiple Satellites
,
Advances In Atmospheric Sciences, 32
, 349-362.
Draft--, -.,
et al.
(2016),
Dependence of the Ice Water Content and Snowfall Rate on Temperature, Globally: Comparison of In-Situ Observations, Satellite Active Remote Sensing Retrievals and Global Climate Model Simulations
,
J. Appl. Meteor. Climat.
.
Eastman, R., and R. Wood (2016),
Factors Controlling Low-Cloud Evolution over the Eastern Subtropical Oceans: A Lagrangian Perspective Using the A-Train Satellites
,
J. Atmos. Sci., 73
, 331-351, doi:10.1175/JAS-D-15-0193.1.
Eberhard, G., S. D’Amico, and O. Montenbruck (2007),
Autonomous Formation Flying for the PRISMA mission
,
Journal of Spacecraft and Rockets, 44
, 671-681, doi:10.2514/1.23015.
Efon, E.,
et al.
(2016),
Cloud properties during active and break spells of the West African summer monsoon from CloudSat–CALIPSO measurements
,
Journal of Atmospheric and Solar-Terrestrial Physics, 145
, 1-11.
Ekström, M., and P. Eriksson (2008),
Altitude resolved ice-fraction in the uppermost tropical troposphere
,
Geophys. Res. Lett., 35
, L13822, doi:10.1029/2008GL034305.
Eliasson, S.,
et al.
(2013),
Systematic and random errors between collocated satellite ice water path observations
,
J. Geophys. Res., 118
, 2629-2642, doi:10.1029/2012JD018381.
Ellis, T. D.,
et al.
(2009),
How often does it rain over the global oceans? The perspective from CloudSat
,
Geophys. Res. Lett., 36
, L03815, doi:10.1029/2008GL036728.
Elsaesser, G.,
et al.
(2017),
An improved convective ice parameterization for the NASA GISS Global Climate Model and impacts on cloud ice simulation
,
J. Clim., 30
, 317-336, doi:10.1175/JCLI-D-16-0346.1.
English, J. M.,
et al.
(2014),
Contributions of Clouds, Surface Albedos, and Mixed-Phase Ice Nucleation Schemes to Arctic Radiation Biases in CAM5
,
J. Climate, 27
, 5174-5197, doi:10.1175/JCLI-D-13-00608.1.
Eriksson, P.,
et al.
(2008),
Comparison between early Odin-SMR, Aura MLS and CloudSat retrievals of cloud ice mass in the upper tropical troposphere
,
Atmos. Chem. Phys., 8
, 1937-1948, doi:10.5194/acp-8-1937-2008.
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