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.

Pages