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Publication Citation
Kang, J.
,
et al.
(2011),
“Variable localization” in an ensemble Kalman filter: Application to the carbon cycle data assimilation
,
J. Geophys. Res., 116
, D09110, doi:10.1029/2010JD014673.
Kang, J.
,
et al.
(2012),
Estimation of surface carbon fluxes with an advanced data assimilation methodology
,
J. Geophys. Res., 117
, D24101, doi:10.1029/2012JD018259.
Kopacz, M.
,
et al.
(2009),
Comparison of adjoint and analytical Bayesian inversion methods for constraining Asian sources of carbon monoxide using satellite (MOPITT) measurements of CO columns
,
J. Geophys. Res., 114
, D04305, doi:10.1029/2007JD009264.
Kopacz, M.
,
et al.
(2010),
Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES)
,
Atmos. Chem. Phys., 10
, 855-876, doi:10.5194/acp-10-855-2010.
Liu, J.
,
et al.
(2009),
Univariate and Multivariate Assimilation of AIRS Humidity Retrievals with the Local Ensemble Transform Kalman Filter
,
Mon. Wea. Rev., 137
, 3918-3932, doi:10.1175/2009MWR2791.1.
Liu, J.
,
et al.
(2011),
CO2 transport uncertainties from the uncertainties in meteorological fields
,
Geophys. Res. Lett., 38
, L12808, doi:10.1029/2011GL047213.
Liu, J.
,
et al.
(2012),
Simultaneous assimilation of AIRS Xco2 and meteorological observations in a carbon climate model with an ensemble Kalman filter
,
J. Geophys. Res., 117
, D05309, doi:10.1029/2011JD016642.
Marquis, J. W.,
et al.
(2017),
Estimating Infrared Radiometric Satellite Sea Surface Temperature Retrieval Cold Biases in the Tropics due to Unscreened Optically Thin Cirrus Clouds
,
J. Atmos. Oceanic Technol., 34
, 355-373, doi:10.1175/JTECH-D-15-0226.1.
McCoy, D. T.,
et al.
(2017),
The global aerosol-cloud first indirect effect estimated using MODIS, MERRA, and AeroCom
,
J. Geophys. Res., 122
, doi:10.1002/2016JD026141.
Mccoy, D. T.
,
et al.
(2017),
The Change in Low Cloud Cover in a Warmed Climate Inferred from AIRS, MODIS, and ERA-Interim
,
J. Climate, 30
, 3609-3620, doi:10.1175/JCLI-D-15-0734.1.
McHardy, T. M.,
et al.
(2015),
An improved method for retrieving nighttime aerosol optical thickness from the VIIRS Day/Night Band
,
Atmos. Meas. Tech., 8
, 4773-4783, doi:10.5194/amt-8-4773-2015.
Menon, S.,
et al.
(2008),
Analyzing signatures of aerosol-cloud interactions from satellite retrievals and the GISS GCM to constrain the aerosol indirect effect
,
J. Geophys. Res., 113
, D14S22, doi:10.1029/2007JD009442.
Naud, C. M.
,
A. Del Genio
, and
M. Bauer
(2006),
Observational Constraints on the Cloud Thermodynamic Phase in Midlatitude Storms
,
J. Climate, 19
, 5273-5288.
Naud, C. M.
,
J. Booth
, and
A. Del Genio
(2016),
The Relationship between Boundary Layer Stability and Cloud Cover in the Post-Cold-Frontal Region
,
J. Climate, 29
, 8129-8149, doi:10.1175/JCLI-D-15-0700.1.
Oreopoulos, L.
,
et al.
(2014),
An examination of the nature of global MODIS cloud regimes
,
J. Geophys. Res., 119
, 8362-8383, doi:10.1002/2013JD021409.
Pan, F.
, and
X. Huang
(2018),
The Spectral Dimension of Modeled Relative Humidity Feedbacks in the CMIP5 Experiments
,
J. Climate, 31
, 10021-10038, doi:10.1175/JCLI-D-17-0491.1.
Polivka, T. N.
,
et al.
(2016),
Improving Nocturnal Fire Detection with the VIIRS Day-Night Band, IEEE Transactions on Geoscience &
,
Remote Sensing, 9
, 5503-5519.
Sharma, A.,
J. Wang
, and
E. Lennartson
(2017),
atmosphere Article Intercomparison of MODIS and VIIRS Fire Products in Khanty-Mansiysk Russia: Implications for Characterizing Gas Flaring from Space
,
www.mdpi.com/journal/atmosphere, 8
, 95, doi:10.3390/atmos8060095.
Shiflett, S. A.,
et al.
(2017),
Variation in the urban vegetation, surface temperature, air temperature nexus
,
Science of the Total Environment, 579
, 495-505, doi:10.1016/j.scitotenv.2016.11.069.
Tang, W.
,
et al.
(2019),
Satellite data reveal a common combustion emission pathway for major cities in China
,
Atmos. Chem. Phys., 19
, 4269-4288, doi:10.5194/acp-19-4269-2019.
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