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> Publications for CLARREO
Publication Citation
Roberts, Y. L.
,
P. Pilewskie
, and
B. C. Kindel
(2011),
Evaluating the observed variability in hyperspectral Earth‐reflected solar radiance
,
J. Geophys. Res., 116
, D24119, doi:10.1029/2011JD016448.
Roithmayr, C.
, and
P. Speth
(2012),
Analysis Of Opportunities For Intercalibration Between Two Spacecraft
,
Spacecraft: Engineering, Technology and Research Missions
, 406-436.
Roithmayr, C.
,
et al.
(2014),
Opportunities to Intercalibrate Radiometric Sensors from International Space Station
,
J. Atmos. Oceanic Technol., 31
, 890-902, doi:10.1175/JTECH-D-13-00163.1.
Roithmayr, C.
,
et al.
(2014),
CLARREO Approach for Reference Intercalibration of Reflected Solar Sensors: On-Orbit Data Matching and Sampling
,
IEEE Trans. Geosci. Remote Sens., 52
, 6762-6774, doi:10.1109/TGRS.2014.2302397.
Roman, J. A.
,
et al.
(2012),
Assessment of Regional Global Climate Model Water Vapor Bias and Trends Using Precipitable Water Vapor (PWV) Observations from a Network of Global Positioning Satellite (GPS) Receivers in the U.S. Great Plains and Midwest
,
J. Climate, 25
, 5471-5493, doi:10.1175/JCLI-D-11-00570.1.
Roman, J. A.
,
et al.
(2016),
Estimating Minimum Detection Times for Satellite Remote Sensing of Trends in Mean and Extreme Precipitable Water Vapor
,
J. Climate
, doi:10.1175/JCLI-D-16-0303.1.
Roman, J.,
B. Knuteson
, and S. Ackerman (2014),
Time-to-Detect Trends in Precipitable Water Vapor with Varying Measurement Error
,
J. Climate, 27
, 8259-8275, doi:.org/10.1175/JCLI-D-13-00736.1.
Roman, J.,
et al.
(2015),
Predicted Changes in the Frequency of Extreme Precipitable Water Vapor Events
,
J. Climate, 28
, 7057-7070, doi:.org/10.1175/JCLI-D-14-00679.1.
Roman, J.,
et al.
(2015),
Predicted Changes in the Frequency of Extreme Precipitable Water Vapor Events
,
J. Climate, 28
, 7057-7070, doi:10.1175/JCLI-D-14-00679.1.
Roman, J.,
et al.
(2016),
A global assessment of NASA AIRS v6 and EUMETSAT IASI v6 precipitable water vapor using ground-based GPS SuomiNet stations
,
J. Geophys. Res., 121
, doi:10.1002/2016JD024806.
Sandford, S. P.
,
et al.
(2010),
CLARREO: cornerstone of the climate observing system measuring decadal change through accurate emitted infrared and reflected solar spectra and radio occultation
,
Proc. SPIE, 7826
, doi:10.1117/12.866353.
Scarino, B. R.,
et al.
(2016),
A Web-Based Tool for Calculating Spectral Band Difference Adjustment Factors Derived From SCIAMACHY Hyperspectral Data
,
IEEE Trans. Geosci. Remote Sens., 54
, 2529-2542, doi:18 10.1109/tgrs.2015.2502904.
Selva, D.,
et al.
(2014),
Rule-Based System Architecting of Earth Observing Systems: Earth Science Decadal Survey
,
Journal of Spacecraft and Rockets, 51
, 1505-1521, doi:10.2514/1.A32656.
Shahabadi, M. B., and Y. Huang (2014),
Logarithmic radiative effect of water vapor and spectral kernels
,
J. Geophys. Res., 119
, 6000-6008, doi:10.1002/2014JD021623.
Shahabadi, M.,
et al.
(2014),
Measuring stratospheric H2O with an airborne spectrometer, J. Atmos. and Oceanic Tech., 31, 1502-1515, doi:http
,
//dx., 31
, 1502-1515, doi:.org/10.1175/JTECH-D-13-00191.1.
Shea, Y. L.,
et al.
(2017),
Quantifying the Dependence of Satellite Cloud Retrievals on Instrument Uncertainty
,
J. Climate
, doi:10.1175/JCLI-D-16-0429.1.
Smith, N.
(2015),
AIRS, IASI and CrIS Retrieval Records At Climate Scales - An Investigation into the Propagation of Systematic Uncertainty
,
J. Appl. Meteor. Climat.
, doi:10.1175/JAMC-D-14-0299.1.
Smith., W. L.,
et al.
(2012),
Dual-Regression Retrieval Algorithm for Real-Time Processing of Satellite Ultraspectral Radiances
,
J. Appl. Meteor. Climat., 51
, 1455-1476, doi:10.1175/JAMC-D-11-0173.1.
Soden, B.
, and G. A. Vecchi (2011),
The vertical distribution of cloud feedback in coupled ocean‐atmosphere models
,
Geophys. Res. Lett., 38
, L12704, doi:10.1029/2011GL047632.
Solomon, S.,
et al.
(2010),
Contributions of Stratospheric Water Vapor to Decadal Changes in the Rate of Global Warming
,
Science, 327
, 1219-1223.
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