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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, DOI:
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, DOI: 10.1109/AERO.2012.6187083.
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, DOI:
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.
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