Skip to main content

CLARREO Publications

Author, (Year), Title, Publication.
Abedin, M., M. Mlynczak, and T. F. Refaat (2010), Infrared detectors overview in the short-wave infrared to far-infrared for the CLARREO mission, SPIE Proceedings, 7808, doi:10.1117/12.863125.
Angal, A., et al. (2013), Impact of Terra MODIS Collection 6 on long-term trending comparisons with Landsat 7 ETM+ reflective solar bands, Remote Sensing Letters, 4, 873-881, doi:10.1080/2150704X.2013.809496.
Angal, A., et al. (2013), Multitemporal Cross-calibration of the Terra MODIS and Landsat 7 ETM+ Reflective Solar Bands, IEEE Trans. Geosci. Remote Sens., 51, doi:10.1109/TGRS.2012.2235448.
Angal, A., et al. (2016), Results from source-based and detector-based calibrations of a CLARREO Calibration Demonstration System , Earth Observing Systems XXI, 9972, doi:10.1117/12.2238634.
Angal, A., et al. (2016), Evaluation of GLAMR-based calibration for SI-traceable field reflectance retrievals, Earth Observing Systems XXI, 9972, doi:10.1117/12.2238630.
Angal, A., et al. (2018), Results From the Deep Convective Clouds-Based Response Versus Scan-Angle Characterization for the MODIS Reflective Solar Bands , IEEE Trans. Geosci. Remote Sens., 56, 1115-1128, doi:10.1109/TGRS.2017.2759660.
Angal, A., X. Xiong, and A. Wu (2017), Monitoring the On-Orbit Calibration of Terra MODIS Reflective Solar Bands Using Simultaneous Terra MISR Observations, IEEE Trans. Geosci. Remote Sens., 55, 1648-1659.
Antonelli, P., et al.;(2018), Regional Retrieval Processor for Direct Broadcast High-Resolution Infrared Data, J. Appl. Meteor. Climat., 56, 1681-1705, doi:10.1175/JAMC-D-16-0144.1.
Ao, C., A. J. Mannucci, and E. R. Kursinski (2012), Improving GPS Radio occultation stratospheric refractivity retrievals for climate benchmarking, Geophys. Res. Lett., 39, L12701, doi:10.1029/2012GL051720.
Ao, C., et al. (2013), Monitoring the width of the tropical belt with GPS radio occultation measurements, Geophys. Res. Lett., 40, 6236-6241, doi:10.1002/2013GL058203.
Ao, C., et al. (2015), Evaluation of CMIP5 upper troposphere and lower stratosphere geopotential height with GPS radio occultation observations, J. Geophys. Res., 120, 1678-1689, doi:10.1002/2014JD022239.
Asmar, S. W., et al. (2018), Small spacecraft for planetary atmospheric, surface, and interior structure using radio links, 2018 IEEE Aerospace Conference, 2018, 1-8, doi:10.1109/AERO.2018.8396551.
Aumann, H. H., et al. (2018), Evaluation of Radiative Transfer Models With Clouds, J. Geophys. Res., 123, 6142-6157, doi:10.1029/2017JD028063.
Bantges, R. J., et al. (2016), On the Detection of Robust Multidecadal Changes in Earth's Outgoing Longwave Radiation Spectrum , J. Climate, 29, 4939-4947, doi:10.1175/JCLI-D-15-0713.1.
Bauer, R. A., et al. (2010),  Technologies Supporting Radiative Science, Infrared Remote Sensing and Instrumentation, Xviii, 7808, doi:10.1117/12.862936.
Bellomo, K., et al. (2014),  Observational and Model Estimates of Cloud Amount Feedback over the Indian and Pacific Oceans, J. Climate, 27, 925-940, doi:10.1175/JCLI-D-13-00165.1.
Best, F. A., et al. (2012), Proceedings of SPIE, Conference on Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications IV, 8527, doi:10.1117/12.977559.
Best, F., et al. (2012), On-orbit Absolute Radiance Standard (OARS) for the next generation of IR remote sensing instruments, Proc. of SPIE, 8527, doi:10.1117/12.977559.
Bhatt, R., et al. (2013), Desert-Based Absolute Calibration of Successive Geostationary Visible Sensors Using a Daily Exoatmospheric Radiance Model, IEEE Trans. Geosci. Remote Sens., 52, 3670-3682, doi:10.1109/TGRS.2013.2274594.
Bhatt, R., et al. (2014), Initial Stability Assessment of S-NPP VIIRS Reflective Solar Band Calibration using Invariant Desert and Deep Convective Cloud Targets, Remote Sens., 6, 2809-2826, doi:10.3390/rs6042809.
Bhatt, R., et al. (2017), Development of Seasonal BRDF Models to Extend the Use of Deep Convective Clouds as Invariant Targets for Satellite SWIR-Band Calibration, Remote Sensing, 9, 1061, doi:10.3390/rs9101061.
Bhatt, R., et al. (2017), Characterizing response versus scan-angle for MODIS reflective solar bands using deep convective clouds, Journal of Applied Remote Sensing, 11, 16014, doi:10.1117/1.JRS.11.016014.
Bhatt, R., et al. (2018), Consideration of Radiometric Quantization Error in Satellite Sensor Cross-Calibration, Remote Sensing, 10, 1131, doi:10.3390/rs10071131.
Bhatt, R., et al. (2018), A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits. Part I: Methodology , J. Atmos. Oceanic Technol., 33, 2499-2515, doi:14 10.1175/JTECH-D-16-0044.1.
Bolcar, M., et al. (2012), Qualification of a null lens using image-based phase retrieval, Proc. SPIE: Space Telescopes and Instrumentation Optical, Infrared and Millimeter Wave, 844251, doi:10.1117/12.926231.
Brindley, H. E. &., and R. Bantges (2016), The Spectral Signature of Recent Climate Change, J. Curr Clim Change Rep, 2, 112, doi:10.1007/s40641-016-0039-5.
Brindley, H., et al. (2015), Spectral signatures of Earth’s climate variability over 5 years from IASI, J. Climate, 28, 1649-1660, doi:10.1175/JCLI-D-14-00431.1.
Brown, A. J., et al. (2014), The case for a modern multiwavelength, polarization-sensitive LIDAR in orbit around Mars, J. Quant. Spectrosc. Radiat. Transfer, doi:10.1016/j.jqsrt.2014.10.021.
Brown, S. W., et al. (2010), An Absolute Detector-based Spectral Radiance Source, Earth Observing Systems Xv, 7807, doi:10.1117/12.860544.
Butler, J. J., et al. (2008), Proceedings of SPIE, Earth Observing Systems Xiii, 7081, doi:10.1117/12.795983.
Cageao, R. P., et al. (2010), Far-IR Measurements at Cerro Toco, Chile: FIRST, REFIR, and AERI, Proc. of SPIE, 7808, doi:10.1117/12.862601.
Chander, G., et al. (2013), Overview of Inter-Calibration of Satellite Instruments, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 51, 1056-1080, doi:10.1109/TGRS.2012.2228654.
Chander, G., et al. (2013), Radiometric Cross-Calibration of EO-1 ALI With L7 ETM+ and Terra MODIS Sensors Using Near-Simultaneous Desert Observations, IEEE JSTARS, 6, 386-399, doi:10.1109/JSTARS.2013.2251999.
Chander, G., et al. (2013), Applications of Spectral Band Adjustment Factors (SBAF) for Cross-Calibration, IEEE Trans. Geosci. Remote Sens., 51, 1267-1281, doi:10.1109/TGRS.2012.2228007.
Chang, T. J. (2017), Aqua and Terra MODIS RSB Calibration Comparison Using BRDF Modeled Reflectance, IEEE Trans. Geosci. Remote Sens., 55, 2288-2298, doi:10.1109/TGRS.2016.2641258.
Chang, T. J., et al. (2016), VIIRS Reflective Solar Band Radiometric and Stability Evaluation Using Deep Convective Clouds, IEEE Trans. Geosci. Remote Sens., 54, 7009-7017, doi:10.1109/TGRS.2016.2594029.
Chen, H., et al. (2017), On-Orbit Characterization of the MODIS SDSM Screen for Solar Diffuser Degradation Estimation , IEEE Trans. Geosci. Remote Sens., 55, 6456-6467, doi:10.1109/TGRS.2017.2728520.
Chen, X. H., et al. (2013), Comparisons of Clear-Sky Outgoing Far-IR Flux Inferred from Satellite Observations and Computed from the Three Most Recent Reanalysis Products, J. Climate, 26, 478-494, doi:10.1175/JCLI-D-12-00212.1.
Chen, X. H., X. L. Huang, and  Xu Liu (2013), Non-negligible effects of cloud vertical overlapping assumptions on longwave spectral fingerprinting studies, J. Climate, 26, 478-494, doi:10.1002/jgrd.50562.
Chen, X., et al. (2014), Sensitivity of modeled far-IR radiation budgets in polar continents to treatments of snow surface and ice cloud radiative properties, Geophys. Res. Lett., 41, doi:10.1002/2014GL061216.
Chen, X., et al. (2016), Deriving clear-sky longwave spectral flux from spaceborne hyperspectral radiance measurements: a case study with AIRS observations, Atmos. Meas. Tech., 9, 6013-6023, doi:10.5194/amt-9-6013-2016.
Chung, E. S., et al. (2015), An Assessment of Direct Radiative Forcing, Radiative Adjustments, and Radiative Feedbacks in Coupled Ocean Atmosphere Models, J. Climate, 28, 4152-4170, doi:10.1175/JCLI-D-14-00436.1.
Chung, E.,B. Soden, and A. Clement (2012), Diagnosing climate feedbacks in coupled ocean-atmosphere models, Surv. Geophys., 733-744, doi:10.1007/s10712-012-9187-x.
Chung, E., B. Soden, and V. O. John (2013), Intercalibrating microwave satellite observations for monitoring long-term variations in upper and mid-tropospheric water vapor, J. Atmos. Oceanic Technol., 30, 2303-2319, doi:10.1175/JTECH-D-13-00001.1.
Coddington, O. M., et al. (2012), The Shannon information content of hyperspectral shortwave cloud albedo measurements: Quantification and practical applications, JOURNAL OF GEOPHYSICAL RESEARCH, 117, doi:10.1029/2011JD016771.
Coddington, O. M., et al. (2013), Characterizing a new surface-based shortwave cloud retrieval based on transmitted radiance for soil and vegetated surface types, Atmosphere, 4, 48-71, doi:10.3390/atmos4010048.
Coddington, O. M., et al. (2018), Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements , J. Geophys. Res., 122, 8079-8100, doi:10.1002/2017JD026493.
Coleman, D. M., and D. Feldman (2013), Porting Existing Radiation Code for GPU Acceleration, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, PP, 1-6, doi:10.1109/JSTARS.2013.2247379.
Cooke, R., et al. (2014), Value of Information for Climate Observing Systems, Environ Syst Decis, doi:10.1007/s10669-013-9451-8.
Cooke, R., et al. (2016), Using the social cost of carbon to value earth observing systems, Climate Policy, doi:10.1080/14693062.2015.1110109.
Divakarla, M., et al. (2014), The CrIMSS EDR Algorithm: Characterization, Optimization And Validation, J. Geophys. Res., 119, 4953-4977.
Doelling, D. R., et al. (2011), Spectral reflectance corrections for satellite intercalibrations using SCIAMACHY data., Geosci. Remote Sens. Lett, 8, doi:10.1109/LGRS.2011.2161751.
Doelling, D. R., et al. (2013), The Intercalibration of Geostationary Visible Imagers Using Operational Hyperspectral SCIAMACHY Radiances, IEEE Trans. Geosci. Remote Sens., 51, 1245-1254, doi:10.1109/TGRS.2012.2227760.
Doelling, D. R., et al. (2018), 1.17 - Vicarious Calibration and Validation, Comprehensive Remote Sensing, 475-518, doi:10.1016/B978-0-12-409548-9.10329-X.
Doelling, D. R., et al. (2018), Geostationary Visible Imager Calibration for the CERES SYN1deg Edition 4 Product , Remote Sensing, 10, doi:10.3390/rs10020288.
Doelling, D. R., et al. (2018), Improvements to the Geostationary Visible Imager Ray-Matching Calibration Algorithm for CERES Edition 4, J. Atmos. Oceanic Technol., 33, 2679-2698, doi:6 10.1175/JTECH-D-16-0113.1.
Doelling, D., et al. (2014), MTSAT-1R Visible Imager Point Spread Function Correction, Part I: The Need for, Validation of, and Calibration With, IEEE Trans. Geosci. Remote Sens., 53, 1513-1526, doi:10.1109/TGRS.2014.2344678.
Doelling, D., et al. (2015), The Radiometric Stability and Scaling of Collection 6 Terra and Aqua-MODIS VIS, NIR, and SWIR Spectral Bands, IEEE Trans. Geosci. Remote Sens., 53, doi:10.1109/TGRS.2015.2400928.
Efremova, B., et al. (2014), CLARREO calibration uncertainty assessment tool: status and path forward, Proc. SPIE 9218, Earth Observing Systems XIX, doi:10.1117/12.2061962.
Eon, R. S., et al. (2017), Development of a simulation environment to support intercalibration studies over the Algodones Dunes system , Journal of Applied Remote Sensing, 12, doi:10.1117/1.jrs.12.012008.
Espejo, J., et al. (2011), A hyperspectral imager for high radiometric accuracy Earth climate studies, Imaging Spectrometry Xvi, 8158, doi:10.1117/12.893803.
Fain, R., et al. (2018), CMOS-compatible Mid-Infrared Silicon Detector , Conference on Lasers and Electro-Optics, doi:10.1364/CLEO_SI.2017.STu1N.4.
Fan, X., et al. (2018), Using a MODIS Index to Quantify MODIS-AVHRRs Spectral Differences in the Visible Band , Remote Sensing, 10, doi:10.3390/rs10010061.
Feldman, D., D. M. Coleman, and W. D. Collins (2013), On the Usage of Spectral and Broadband Satellite Instrument Measurements to Differentiate Climate Models with Different Cloud Feedback Strengths, J. Climate, doi:10.1175/JCLI-D-12-00378.1.
Feldman, D., et al. (2011), Simulation studies for the detection of changes in broadband albedo and shortwave nadir reflectance spectra under a climate change scenario, J. Geophys. Res., 116, D24103, doi:10.1029/2011JD016407.
Feldman, D., et al. (2011), CLARREO shortwave observing system simulation experiments of the twenty‐first century: Simulator design and implementation, J. Geophys. Res., 116, D10107, doi:10.1029/2010JD015350.
Feldman, D., et al. (2014), Far-Infrared Surface Emissivity in Climate, Proc. Natl. Acad. Sci., 111, 16297-16302, doi:10.1073/pnas.1413640111.
Feldman, D., et al. (2015),  Pan-spectral observing system simulation experiments of shortwave reflectance and long-wave radiance for climate model evaluation, Geosci. Model Dev, 8, 1943-1954, doi:10.5194/gmd-8-1943-2015.
Feltz, M. L. (2018), Assessment of COSMIC radio occultation and AIRS hyperspectral IR sounder temperature products in the stratosphere using observed radiances, J. Geophys. Res., 122, 8593-8616, doi:10.1002/2017JD026704.
Feltz, M., et al. (2014), Application of GPS radio occultation to the assessment of temperature profile retrievals from microwave and infrared sounders, Atmos. Meas. Tech., 7, 3751-3762, doi:10.5194/amt-7-3751-2014.
Feltz, M., et al. (2014), A methodology for the validation of temperature profiles from hyperspectral infrared sounders using GPS radio occultation: Experience with AIRS and COSMIC, J. Geophys. Res., 119, 1680-1691, doi:10.1002/ 2013JD020853.
Feng, J., et al. (2018), Cloud-Assisted Retrieval of Lower-Stratospheric Water Vapor from Nadir-View Satellite Measurements, J. Atmos. Oceanic Technol., 35, 541-553, doi:10.1175/JTECH-D-17-0132.1.
Gastineau, G., et al. (2014), Satellite-Based Reconstruction of the Tropical Oceanic Clear-Sky Outgoing Longwave Radiation and Comparison with Climate Models, J. Climate, 27, 941-957, doi:10.1175/JCLI-D-13-00047.1.
Gerace, A. D., et al. (2015), The development of a DIRSIG simulation environment to support instrument trade studies for the SOLARIS sensor, and Ultraspectral Imagery Xxi, 9472, doi:10.1117/12.2177507.
Gero, P. J., et al. (2012), On-orbit Absolute Blackbody Emissivity Determination Using the Heated Halo Method, Metrologia, 49, doi:10.1088/0026-1394/49/2/S1.
Godoy, W. F., et al. (2012), Parallel Jacobian-­‐Free Newton Krylov Solution of the Discrete Ordinates Method With Flux Limiters for 3D Radiative Transfer, Journal of Computational Physics, 11, 4257-4278, doi:10.1016/
Goldberg, M., et al. (2011), The Global Space-based Inter-Calibration System (GSICS), Bull. Am. Meteorol. Soc., 92, 467-475, doi:10.1175/2010bam2967.1.
Goldin, D., et al. (2015), Empirical Polarization Distribution Models for CLARREO-Imager Intercalibration, J. Atmos. Oceanic Technol., 33, doi:10.1175/JTECH-D-15-0165.1.
Gong, X., et al. (2018), ntercomparison Between VIIRS and CrIS by Taking Into Account the CrIS Subpixel Cloudiness and Viewing Geometry , J. Geophys. Res., 123, 5335-5345, doi:10.1029/2017JD027849.
Gorrono, J., et al. (2018), Providing uncertainty estimates of the Sentinel-2 top-of-atmosphere measurements for radiometric validation activities , European Journal of Remote Sensing, 51, 650-666, doi:10.1080/22797254.2018.1471739.
Gorrono, J., et al. (2018), Radiometric inter-sensor cross-calibration uncertainty using a traceable high accuracy reference hyperspectral imager , ISPRS Journal of Photogrammetry and Remote Sensing, 130, 393-417, doi:10.1016/j.isprsjprs.2017.07.002.
Hanea, A. M., et al. (2018), Bayesian networks for identifying incorrect probabilistic intuitions in a climate trend uncertainty quantification context , Journal of Risk Research, 1-16, doi:10.1080/13669877.2018.1437059.
Hao, X. P., et al. (2018), Vacuum Radiance-Temperature Standard Facility for Infrared Remote Sensing at NIM , International Journal of Thermophysics, 39, doi:10.1007/s10765-018-2396-x.
Helder, D., et al. (2013), Absolute Radiometric Calibration of Landsat Using a Pseudo Invariant Calibration Site, IEEE Trans. Geosci. Remote Sens., 51, 1360-1369, doi:10.1109/TGRS.2013.2243738.
Henry, P., et al. (2013), Assessment of Spectral Band Impact on Intercalibration Over Desert Sites Using Simulation Based on EO-1 Hyperion Data, IEEE Trans. Geosci. Remote Sens., 51, 1297-1307, doi:10.1109/TGRS.2012.2228210.
Hogue, H. H., et al. (2007), Far-Infrared Blocked Impurity Band Detector Development, Proc. of SPIE, 6678, doi:10.1117/12.735123.
Hogue, H. H., et al. (2008), Far-infrared detector development for space-based Earth observation, Proc. of SPIE, 7082, doi:10.1117/12.797078.
Huang, X. L., et al. (2016), An Observationally Based Global Band-by-Band Surface Emissivity Dataset for Climate and Weather Simulations, J. Atmos. Sci., 73, 3541-3555, doi:10.1175/JAS-D-15-0355.1.
Huang, X., et al. (2014), The spectral dimension of longwave feedback in the CMIP3 and CMIP5 experiments, Geophys. Res. Lett., 41, doi:10.1002/2014GL061938.
Huang, X.,  N. Loeb, and H. Chuang (2012), Assessing Stability of CERES-FM3 Daytime Longwave Unfiltered Radiance with AIRS Radiances, J. Atmos. Oceanic Technol., 29, 375-381, doi:10.1175/JTECH-D-11-00066.1.
Huang, Y. (2012), A simulated climatology of spectrally decomposed atmospheric infrared radiation, J. Climate, doi:10.1175/JCLI-D-12-00438.1.
Huang, Y. (2013), On the longwave climate feedback, J. Climate, 26, 7603-7610, doi:10.1175/JCLI-D-13-00025.1.
Huang, Y., et al. (2011), Discriminating between climate observations in terms of their ability to improve an ensemble of climate predictions, Proc. Natl. Acad. Sci., 108, 10405-10409, doi:10.1073/pnas.1107403108.
Huang, Y., et al. (2014), The implication of radiative forcing and feedback for poleward energy transport, Geophy. Res. Lett., 41, 1665-1672, doi:10.1002/2013GL059079.
Huang, Y., et al. (2016), Is there a stratospheric radiative feedback in global warming simulations?, Clim. Dyn., 46, 177-186, doi:10.1007/s00382-015-2577-2.
Huang, Y., et al. (2016), Inhomogeneous radiative forcing of homogeneous greenhouse gases, J. Geophys. Res., 121, 2780-2789, doi:10.1002/2015JD024569.
Jamnejad, V., et al. (2012), Synthesis Study of a 6-Element Non-Uniform Array with Tilted Elements for CLARREO Project, 2012 Ieee Aerospace Conference.
Jin, Z., et al. (2011), Spectral kernel approach to study radiative response of climate variables and interannual variability of reflected solar spectrum, J. Geophys. Res., 116, D10113, doi:10.1029/2010JD015228.
Jin, Z., et al. (2012), Correlation between SCIAMACHY, MODIS, and CERES reflectance measurements: Implications for CLARREO, J. Geophys. Res., 117, D05114, doi:10.1029/2011JD017051.
Jin, Z., et al. (2013), An Efficient And Effective Method to Simulate The Earth Spectral Reflectance Over Large Time and Space Scales, GEOPHYSICAL RESEARCH LETTERS, 40, 374-379, doi:10.1002/GRL.50116.
Jin, Z., et al. (2014), Interannual variability of the Earth's spectral solar reflectance from measurements and simulations, J. Geophys. Res., 119, 4458-4470, doi:10.1002/2013JD021056.
Jin, Z., et al. (2016), An Initial Study on Climate Change Fingerprinting Using the Reflected Solar Spectra, J. Climate, 28, doi:10.1175/JCLI-D-15-0297.1.
Jin, Z., et al. (2017), Errors in spectral fingerprints and their effects on climate fingerprinting accuracy in the solar spectrum, J. Quant. Spectrosc. Radiat. Transfer, 188, doi:10.1016/j.jqsrt.2016.06.029.
Johnson, D. G., and M. Mlynczak (2011), Science, Measurement, and Technology Requirements for Infrared Climate Benchmark Missions, OSA Technical Digest.
Kahn, B., et al. (2016), ENSO regulation of far- and mid-infrared contributions to clear-sky OLR, Geophys. Res. Lett., 43, 8751-8759, doi:10.1002/2016gl070263.
Kato, S., et al. (2011), Detection of Atmospheric Changes in Spatially and Temporally Averaged Infrared Spectra Observed from Space, J. Climate, 24, 6392-6407, doi:10.1175/JCLI-D-10-05005.1.
Kato, S., et al. (2014), Retrieval of Atmospheric and Cloud Property Anomalies and Their Trend from Temporally and Spatially Averaged Infrared Spectra Observed from Space, J. of Climate, 27, 4403-4420, doi:10.1175/JCLI-D-13-00566.1.
Khlopenkov, K., et al. (2014), MTSAT-1R Visible Imager Point Spread Function Correction, Part II, IEEE Trans. Geosci. Remote Sens., 53, 1504-1512, doi:10.1109/TGRS.2014.2344627.
Kindel, B. C., et al. (2016), Upper-troposphere and lower-stratosphere water vapor retrievals from the 1400 and 1900 nm water vapor bands, Atmos. Meas. Tech., 8, 1147-1156, doi:10.5194/amt-8-1147-2015.
Kopp, G., et al. (2017), Radiometric flight results from the HyperSpectral Imager for Climate Science (HySICS), Geosci. Instrum. Method. Data Syst., 6, 169-191, doi:10.5194/gi-6-169-2017.
Laszlo, I. (2018), 7.06 - Remote Sensing of Tropospheric Aerosol Optical Depth From Multispectral Monodirectional Space-Based Observations, Comprehensive Remote Sensing, 137, 137-196, doi:10.1016/B978-0-12-409548-9.10389-6.
Latvakiski, H. M., et al. (2013), Far-Infrared Spectroscopy of the Troposphere (FIRST) - Instrument description and calibration performance, Appl. Opt., 52, 264-273, doi:175801.
Latvakoski, H. M., et al. (2010), Accurate blackbodies, Proc. of SPIE, 7739, doi:10.1117/12.857171.
Latvakoski, H., et al. (2010), A high-accuracy blackbody for CLARREO, Proc. of SPIE, 7808, doi:10.1117/12.859477.
Latvakoski, H., et al. (2011), Testing of Highly Accurate Blackbodies, Infrared Remote Sensing and Instrumentation Xix, 8154, doi:10.1117/12.895985.
Latvakoski, H., et al. (2014), Far-infrared spectroscopy of the troposphere: Calibration with a cold background, Appl. Opt., 53, 5425-5433, doi:10.1364/AO.53.005425.
LeBlanc, S. E., et al. (2015), A spectral method for discriminating thermodynamic phase and retrieving cloud optical thickness and effective radius using transmitted solar radiance spectra, Atmos. Meas. Tech., 8, 1361-1383, doi:10.5194/amt-8-1361-2015.
Leckey, J. (2016), ABSOLUTE STANDARDS FOR CLIMATE MEASUREMENTS, Xxiii Isprs Congress, Commission Viii, 41, 1407-1408, doi:10.5194/isprs-archives-XLI-B8-1407-2016.
Leckey, J. (2017), CLIMATE ABSOLUTE RADIANCE AND REFRACTIVITY OBSERVATORY (CLARREO), Remote Sensing of Environment, 47, 213-217, doi:10.5194/isprsarchives-XL-7-W3-213-2015.
Leroy, S., and M. J. Rodwell (2014), Leveraging highly accurate data in diagnosing errors in atmospheric models, Bull. Am. Meteorol. Soc., 95, doi:10.1175/BAMS-D-12-00143.1.
Leroy, S., C. Ao, and O. Verkhoglyadova (2012), Mapping GPS Radio Occultation Data by Bayesian Interpolation, J. Atmos. Oceanic Technol., 29, 1062-1074, doi:10.1175/JTECH-D-11-00179.1.
Leroy, S., et al. (2008), Testing Climate Models Using Thermal Infrared Spectra, J. Climate, 21, 1863-1875, doi:10.1175/2007JCLI2061.1.
Leroy, S., et al. (2017), LEVERAGING HIGHLY ACCURATE DATA IN DIAGNOSING ERRORS IN ATMOSPHERIC MODELS, Bull. Am. Meteorol. Soc., 95, 1227-1233, doi:10.1175/BAMS-D-12-00143.1.
Leroy, S., J. Anderson, and G. Ohring (2008), Climate Signal Detection Times and Constraints on Climate Benchmark Accuracy Requirements, J. Climate, 21, 841-846, doi:10.1175/2007JCLI1946.1.
Liang, S. (2018), 5.01 - Volume 5 Overview: Recent progress in Remote Sensing of Earth’s Energy Budget, Comprehensive Remote Sensing, 1-31,
Libois, Q., et al. (2018), Added value of far-infrared radiometry for remote sensing of ice clouds, J. Geophys. Res., 122, 6541-6564, doi:10.1002/2016JD026423.
Lin, Z., et al. (2015), Improved discrete ordinate solutions in the presence of an anisotropically reflecting lower boundary: Upgrades of the DISORT computational tool, J. Quant. Spectrosc. Radiat. Transfer, 157, 119-134.
Liu, X. (2012), Retrieving atmospheric temperature and moisture profiles from SUOMI NPP CrIS/ATMS sensors using CrIMSS EDR algorithm, Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International, 2012, 1956-1959, doi:10.1109/IGARSS.2012.6350816.
Liu, X., et al. (2016), Development of a fast and accurate PCRTM radiative transfer model in the solar spectral region, Appl. Opt., 55, 8236-8247, doi:10.1364/AO.55.008236.
Liu, X., et al. (2018), Spectrally Dependent CLARREO Infrared Spectrometer Calibration Requirement for Climate Change Detection, J. Climate, 30, 3979-3998, doi:1 10.1175/JCLI-D-16-0704.1.
Loeb, N., et al. (2007), Multi-Instrument Comparison of Top-of-Atmosphere Reflected Solar Radiation, J. Climate, 20, 575, doi:10.1175/JCLI4018.1.
Loeb, N., et al. (2007), Variability in global top-of-atmosphere shortwave radiation between 2000 and 2005, Geophys. Res. Lett., 34, L03704, doi:10.1029/2006GL028196.
Loeb, N., et al. (2009), Toward Optimal Closure of the Earth's Top-of-Atmosphere Radiation Budget, J. Climate, 22, 748-766, doi:10.1175/2008JCLI2637.1.
Lukashin, C. (2015), CLARREO Reflected Solar Spectrometer: Restrictions for Instrument Sensitivity to Polarization, IEEE Trans. Geosci. Remote Sens., doi:1109/TGRS.2015.2446197.
Lukashin, C., et al. (2013), Uncertainty Estimates for Imager Reference Inter-calibration with CLARREO Reflected Solar Spectrometer, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 51, doi:10.1109/TGRS.2012.2233480
Lukashin, C., et al. (2015), CLARREO Reflected Solar Spectrometer: Restrictions for Instrument Sensitivity to Polarization, IEEE Trans. Geosci. Remote Sens., doi:1109/TGRS.2015.2446197.
Lukashin, C., et al. (2017), On-orbit data matching and sensor inter-calibration, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 297-300, doi:10.1109/IGARSS.2017.8126954.
Lukashin, C., et al. (2017), On-orbit Data Matching and Sensor Inter-calibration , IEEE International Geoscience and Remote Sensing Symposium, 170, 297-300.
Lyapustin, A., et al. (2014), Scientific impact of MODIS C5 calibration degradation and C6+ improvements, Atmos. Meas. Tech., 7, doi:10.5194/amt-7-4353-2014.
Mast, J., et al. (2018), Measurements of downwelling far-infrared radiance during the RHUBC-II campaign at Cerro Toco, Chile and comparisons with line-by-line radiative transfer calculations, J. Quant. Spectrosc. Radiat. Transfer, 198, 25-39, doi:10.1016/j.jqsrt.2017.04.028.
Matthews, G. (2018), First decadal lunar results from the Moon and Earth Radiation Budget Experiment, Appl. Opt., 57, 1594-1610, doi:10.1364/AO.57.001594.
McCorkel, J. (2012), Instrumentation and first results of the reflected solar demonstration system for the Climate Absolute Radiance and Refractivity Observatory, Earth Observing Systems Xvii, 8510, doi:10.1117/12.930950.
Mlynczak, M., et al. (2013), The Far-Infrared Spectroscopy of the Troposphere (FIRST) Instrument: New Technology for Measuring Earth’s Energy Balance and Climate Change, Earthzine.
Mlynczak, M., et al. (2016), Observations of downwelling far-infrared emission at Table Mountain California made by the FIRST instrument, J. Quant. Spectrosc. Radiat. Transfer, 170, 90-105, doi:10.1016/j.jqsrt.2015.10.017.
Mlynczak, M., et al. (2016), The spectroscopic foundation of radiative forcing of climate by carbon dioxide, Geophys. Res. Lett., 43, doi:10.1002/2016GL068837.
Moyer, D., et al. (2017), JPSS-1VIIRS Prelaunch Polarization Testing and Performance, IEEE Trans. Geosci. Remote Sens., 55, 2463-2476, doi:10.1109/TGRS.2016.2645403.
Mu, Q. Z., et al. (2017), Optimization of a Deep Convective Cloud Technique in Evaluating the Long-Term Radiometric Stability of MODIS Reflective Solar Bands , Remote Sensing, 6, doi:10.3390/rs9060535.
Mulargia, F., et al. (2018), Scientific principles and public policy, Earth-Science Reviews, 176, 214-221, doi:10.1016/j.earscirev.2017.09.007.
Nalli, N. R., et al. (2013), Validation of Hyperspectral Infrared Sounder Environmental Data Records: Application to the Cross-track Infrared Microwave Sounder Suite (CrIMSS), 1-16, doi:10.1002/2013JD020436.
Oudrari, H., et al. (2016),JPSS-1 VIIRS Radiometric Characterization and Calibration Based on Pre-Launch Testing, Remote Sensing, 8, doi:10.3390/rs8010041.
Pan, F., et al. (2015), Linear trends and closures of 10- year observations of AIRS stratospheric channels, J. Climate, doi:10.1175/JCLID-15-0418.1.
Pan, F., et al. (2015), Linear trends and closures of 10- year observations of AIRS stratospheric channels, J. Climate, in press, doi:10.1175/JCLID-15-0418.1.
Pan, F., et al. (2018), The Stratospheric Changes Inferred from 10 Years of AIRS and AMSU-A Radiances , J. Climate, 30, 6005-6016, doi:10.1175/JCLI-D-17-0037.1.
Pavlov, A., et al. (2018), Vertical profile of polarization over Vladivostok using horizon shadowing: Clues to understanding the altitude variation of reflectance of aerosol particles , J. Quant. Spectrosc. Radiat. Transfer, 204, 94-102, doi: 10.1016/j.jqsrt.2017.08.024.
Phojanamongkolkij, N., et al. (2014), A Comparison of Climate Signal Trend Detection Uncertainty Analysis Methods, J. Climate, 27, 3363-3376, doi:10.1175/JCLI-D-13-00400.1.
Refaat, T. F., and D. G. Johnson (2012), Absolute linearity measurement of photodetectors using sinusoidal modulated radiation, Applied Optics, 51, 4420-4429, doi:165676.
Revercomb, H., et al. (2016), Monitoring climate from space: a metrology perspective, Earth Observing Missions and Sensors: Development, Implementation, and Characterization Iv, 9881, doi:10.1117/12.2223978.
Roberts, Y. L., et al. (2012), Quantitative Comparison of the Variability in Observed and Simulated Shortwave Reflectance, Atmos. Chem. Phys., 13, 3133-3147, doi:10.5194/acp-13-3133-2013.
Roberts, Y. L., et al. (2014), Temporal variability of observed and simulated hyperspectral reflectance, J. Geophys. Res., 119, 262-280, doi:10.1002/2014JD021566.
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,
Roman, J., et al. (2015), Predicted Changes in the Frequency of Extreme Precipitable Water Vapor Events, J. Climate, 28, 7057-7070,
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,
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.
Stephens, G. L., et al. (2015), The albedo of Earth C8 - 2014RG000449, Rev. Geophys., 53, 141-163, doi:10.1002/2014RG000449.
Strojnik, M., et al. (2008), Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie), Infrared Spaceborne Remote Sensing and Instrumentation Xvi, 7082, doi:10.1117/12.797078.
Sun, J., et al. (2016), Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite polarization sensitivity analysis, Appl. Opt., 55, 7645-7658, doi:10.1364/AO.55.007645.
Sun, W., and C. Lukashin (2013), Modeling polarized solar radiation from the ocean–atmosphere system for CLARREO inter-calibration applications, Atmos. Chem. Phys., 13, 10303-10324, doi:10.5194/acp-13-10303-2013.
Sun, W., et al. (2011), A study of subvisual clouds and their radiation effect with a synergy of CERES, MODIS, CALIPSO, and AIRS data, J. Geophys. Res., 116, D22207, doi:10.1029/2011JD016422.
Sun, W., et al. (2011), On the consistency of CERES longwave flux and AIRS temperature and humidity profiles, J. Geophys. Res., 116, D17101, doi:10.1029/2011JD016153.
Sun, W., et al. (2012), For the depolarization of linearly polarized light by smoke particles, J. Quant. Spectrosc. Radiat. Transfer, doi:10.1016/j.jqsrt.2012.03.031.
Sun, W., et al. (2013), Scattered-field FDTD and PSTD algorithms with CPML absorbing boundary conditions for light scattering by aerosols, J. Quant. Spectrosc. Radiat. Transfer, 131, 166-174, doi:10.1016/j.jqsrt.2013.07.015.
Sun, W., et al. (2014), Detecting super-thin clouds with polarized sunlight, Geophy. Res. Lett., 41, 688-693, doi:10.1002/2013GL058840.
Sun, W., et al. (2014), Notes Sensing Hadley cell with space-borne lidar, J. Quant. Spectrosc. Radiat. Transfer, 148, 38-41, doi:10.1016/j.jqsrt.2014.06.017.
Sun, W., et al. (2014), Modeling polarized solar radiation for CLARREO inter-calibration applications, J. Quant. Spectrosc. Radiat. Transfer, doi:10.1016/j.jqsrt.2014.05.013.
Sun, W., et al. (2015), A method to retrieve super-thin cloud optical depth over ocean background with polarized sunlight, Atmos. Chem. Phys., 15, 11909-11918, doi:10.5194/acp-15-11909-2015.
Sun, W., et al. (2015), A method to retrieve super-thin cloud optical depth over ocean background with polarized sunlight, Atmos. Chem. Phys., doi:10.5194/acpd-15-21959-2015.
Sun, W., et al. (2015), Modeling polarized solar radiation of the ocean-atmosphere system for satellite remote sensing applications, in Light Scattering Reviews. (edited by Alexander A. Kokhanovsky) Praxis Publishing, United Kingdom, 10.
Sun, W., et al. (2015), Deriving polarization properties of desert-reflected solar spectra with PARASOL data, Atmos. Chem. Phys., 15, 7725-7734, doi:10.5194/acp-15-7725-2015.
Sun, W., et al. (2018), Chapter 7 - Polarimetric Technique for Satellite Remote Sensing of Superthin Clouds , Remote Sensing of Aerosols, Clouds, and Precipitation, 153-174, doi:10.1016/B978-0-12-810437-8.00007-4.
Sun, W., et al. (2019), Modeling polarized solar radiation from a snow surface for correction of polarization-induced error in satellite data, J. Quant. Spectrosc. Radiat. Transfer, 222–223, 154-169, doi:10.1016/j.jqsrt.2018.10.011.
Sun, W., G. Videen, and M. Mishchenko (2014), Detecting super-thin clouds with polarized sunlight, Geophy. Res. Lett., 41, doi:10.1002/2013GL058840.
Taylor, J., et al. (2010), The University of Wisconsin Space Science and Engineering Center Absolute Radiance Interferometer (ARI), Proc. SPIE 7857, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications III,, 7857, doi:10.1117/12.869581.
Taylor, J., et al. (2012), The University of Wisconsin Space Science and Engineering Center Absolute Radiance Interferometer (ARI): instrument overview and radiometric performance, Proc. SPIE 8527, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications IV, 8527, doi:10.1117/12.977533.
Thome, K. J. (2012), Characterization approaches to place invariant sites on si-traceable scales, 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARRS). Pps, 7019-7022, doi:10.1109/IGARSS.2012.6351955.
Thome, K. J., et al. (2011), Preliminary Error Budget for the Reflected Solar Instrument For The Climate Absolute Radiance And Refractivity Observatory, Earth Observing Systems Xvi, 8153, doi:10.1117/12.894177.
Thome, K. J., et al. (2012), Test plan for a calibration demonstration system for the reflected solar instrument for the climate absolute radiance and refractivity observatory, Proc. SPIE 8516 Remote Sensing System Engineering, doi:10.1117/12.930337.
Thome, K. J., et al. (2017), Importance of calibration/validation traceability for multi-sensor imaging spectrometry applications , 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 3055-3058, doi:10.1109/IGARSS.2017.8127643.
Thome, K. J., J. McCorkel, and B. McAndrew (2012), Error budget for a calibration demonstration system for the reflected solar instrument for the climate absolute radiance and refractivity observatory. Proc. SPIE 8870, Imaging Spectrometry XVIII, 887008 (September 23, 2013); doi:10.1117/12.2024562; http, //dx.,
Thome, K. J., T. Gubbels, and R. Barnes (2011), 2011, Preliminary error budget for the reflected solar instrument for the Climate Absolute Radiance and Refractivity Observatory, Proc. SPIE 8153, Earth Observing Systems, XVI, 81530R, doi:10.1117/12.894177.
Thome, K., et al. (2010), Calibration of the reflected solar instrument for the climate absolute radiance and refractivity observatory, IEEE International Geoscience and Remote Sensing Symposium. ISBN, 2275-2278, doi:10.1109/IGARSS.2010.5651486.
Thome, K., et al. (2010), CALIBRATION OF THE REFLECTED SOLAR INSTRUMENT FOR THE CLIMATE ABSOLUTE RADIANCE AND REFRACTIVITY OBSERVATORY, 2010 Ieee International Geoscience and Remote Sensing Symposium, 15, 2275-2278, doi:10.1109/IGARSS.2010.5651486.
Thome, K., et al. (2012), CHARACTERIZATION APPROACHES TO PLACE INVARIANT SITES ON SITRACEABLE SCALES, 2012 Ieee International Geoscience and Remote Sensing Symposium (Igarss), 7019-7022, doi:10.1109/IGARSS.2012.6351955 (submitted).
Thome, K., et al. (2015), Demonstrating the error budget for the Climate Absolute Radiance and Refractivity Observatory through solar irradiance measurements, Conference on Earth Observing Systems XX, 9607, doi:10.1117/12.2188849.
Thompson, P., and P. C. Hill (2012), Conceptual optical design and system engineering of the CLARREO/RS (reflected solar) instrument suite, Conceptual optical design and system engineering of the CLARREO/RS (reflected solar) instrument suite, Proc. SPIE 8515 Imaging Spectrometry, XVII, 85150N, doi:10.1117/12.929849.
Tobin, D., et al. (2015), Reference Infrared Satellite Intercalibration, J. Geophys. Res. (submitted).
Tobin, D., et al. (2016), Characterization of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) ability to serve as an infrared satellite intercalibration reference, J. Geophys. Res., 121, 4258-4271, doi:10.1002/2016JD024770.
Topham, T. S., et al. (2015), Observational study: microgravity testing of a phase-change reference on the International Space Station, npj Microgravity, 2015, 15009, doi:10.1038/npjmgrav.2015.9.
Videen, G., et al. (2014), Mixing rules and morphology dependence, J. Quant. Spectrosc. Radiat. Transfer, doi:10.1016/j.jqsrt.2014.07.022.
Wang, C., P. Yang, and X. Liu (2015), A High-Spectral-Resolution Radiative Transfer Model for Simulating Multilayered Clouds and Aerosols in the Infrared Spectral Region, J. Atmos. Sci., 72, 926-942.
Wang, L., et al. (2018), Improved scheme for Cross-track Infrared Sounder geolocation assessment and optimization, J. Geophys. Res., 122, 519-536, doi:10.1002/2016JD025812.
Wang, Z., et al. (2016), Improved Band-to-Band Registration Characterization for VIIRS Reflective Solar Bands Based on Lunar Observations, Remote Sensing, 8, doi:10.3390/rs8010027.
Weatherhead, E. C., et al. (2018), Designing the Climate Observing System of the Future , Earths Future, 6, 80-102, doi:10.1002/2017ef000627.
Weisz, E., et al. (2013), Advances in simultaneous atmospheric profile and cloud parameter regression based retrieval from high-spectral resolution radiance measurements, J. Geophys. Res., 118, 6433-6443, doi:10.1002/jgrd.50521.
Wielicki, B., et al. (2013), Achieving Climate Change Absolute Accuracy in Orbit, Bull. Am. Meteorol. Soc., 94, 1519-1539, doi:10.1175/BAMS-D-12-00149.1.
Wong, T., et al. (2018), On the Lessons Learned From the Operations of the ERBE Nonscanner Instrument in Space and the Production of the Nonscanner TOA Radiation Budget Data Set , IEEE Trans. Geosci. Remote Sens., 1-12, doi:10.1109/TGRS.2018.2828783.
Wu, A., et al. (2013), Impacts of hyperspectral sensor spectral coverage, sampling and resolution on cross-comparison with broadband sensor for reflective solar bands, Earth Observing Systems Xviii, 8866, doi:10.1117/12.2023393.
Wu, A., et al. (2013), Characterization of Terra and Aqua MODIS VIS, NIR and SWIR Spectral Bands Calibration Stability, IEEE Trans. Geosci. Remote Sens., 51, 4330-4338, doi:10.1109/TGRS.2012.2226588.
Wu, A., et al. (2016), Assessment of SNPP VIIRS VIS/NIR Radiometric Calibration Stability Using Aqua MODIS and Invariant Surface Targets, IEEE Trans. Geosci. Remote Sens., 54, 2918-2924, doi:10.1109/TGRS.2015.2508379.
Wu, A., et al. (2017), Assessment of Terra MODIS On-Orbit Polarization Sensitivity Using Pseudoinvariant Desert Sites , IEEE Trans. Geosci. Remote Sens., 55, 4168-4176, doi:10.1109/TGRS.2017.2689719.
Wu, W., et al. (2017), The Application of PCRTM Physical Retrieval Methodology for IASI Cloudy Scene Analysis , IEEE Trans. Geosci. Remote Sens., 55, 5042-5056, doi:10.1109/TGRS.2017.2702006.
Xiong, X., et al. (2014), VIIRS on-orbit calibration methodology and performance, J. Geophys. Res., 119, 5065-5078, doi:10.1002/2013JD020423.
Xiong, X., et al. (2016), Global Space-based Inter-Calibration System Reflective Solar Calibration Reference: From Aqua MODIS to S-NPP VIIRS, Earth Observing Missions and Sensors: Development, Implementation, and Characterization Iv, 9881, doi:10.1117/12.2224320.
Xiong, X., et al. (2016), Assessment of S-NPP VIIRS On-Orbit Radiometric Calibration and Performance, Remote Sensing, 8, doi:10.3390/rs8020084.
Xiong, X., et al. (2016), S-NPP VIIRS CALIBRATION AND PERFORMANCE UPDATE, 2016 Ieee International Geoscience and Remote Sensing Symposium (Igarss), 1976-1979.
Xiong, X., et al. (2016), Lunar Calibration and Performance for S-NPP VIIRS Reflective Solar Bands, 10.1109/tgrs.2015.2473665, 54, 1052-1061, doi:10.1109/TGRS.2015.2473665.
Xu, X., et al. (2018), Sense size-dependent dust loading and emission from space using reflected solar and infrared spectral measurements: An observation system simulation experiment , J. Geophys. Res., 122, 8233-8254, doi:3 10.1002/2017JD026677.
Yang, Q., et al. (2015), Effective multi-scattering-stream model for fast radiative transfer simulation, OSA Technical Digest (online), doi:10.1364/HISE.2015.HT4B.5.
Zhai, P., et al. (2018), Water-leaving contribution to polarized radiation field over ocean , Optics Express, 25, A689-A708, doi:10.1364/OE.25.00A689.
Zhang, L., et al. (2018), A novel hyperspectral lunar irradiance model based on ROLO and mean equigonal albedo , Optik - International Journal for Light and Electron Optics, 142, 657-664, doi:10.1016/j.ijleo.2017.06.007.
Zhang, M., et al. (2014), Radiative forcing of quadrupling CO2, J. Climate, 27, 2496-2508, doi:10.1175/JCLI-D-13-00535.1.
Zhang, X., et al. (2014), Black carbon aerosols in urban central China, J. Quant. Spectrosc. Radiat. Transfer, doi:10.1016/j.jqsrt.2014.03.006 (submitted).
Zhou, D. K., A. Larar, and X. Liu (2013), MetOp-A/IASI Observed Continental Thermal IR Emissivity Variations, IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing.,
Zhou, D. K., et al. (2007), Physically Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements, J. Atmos. Sci., 64, 969-982, doi:10.1175/JAS3877.1.
Zubko, V., et al. (2013), Light scattering by feldspar particles: Comparison of model agglomerate debris particles with laboratory samples, J. Quant. Spectrosc. Radiat. Transfer, 131, 175-187, doi:10.1016/j.jqsrt.2013.01.017.