Benjamin Scarino
Organization:
NASA Langley Research Center
Science Systems and Applications, Inc.
First Author Publications:
- Scarino, B., et al. (2017), Global clear-sky surface skin temperature from multiple satellites using a single-channel algorithm with angular anisotropy corrections, Atmos. Meas. Tech., 10, 351-371, doi:10.5194/amt-10-351-2017.
- Scarino, B., 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:10.1109/TGRS.2015.2502904.
- Scarino, B., et al. (2013), Retrieving Clear-Sky Surface Skin Temperature for Numerical Weather Prediction Applications from Geostationary Satellite Data, Remote Sens., 5, 342-366, doi:10.3390/rs5010342.
Co-Authored Publications:
- Doelling, D. R., et al. (2023), Daily monitoring algorithms to detect geostationary imager visible radiance anomalies, Terms of Use, doi:10.1117/1.JRS.16.014502.
- Minnis, P., et al. (2021), CERES MODIS Cloud Product Retrievals for Edition 4—Part I: Algorithm Changes, IEEE Trans. Geosci. Remote Sens., 59, 2744-2780, doi:10.1109/TGRS.2020.3008866.
- Bhatt, R., et al. (2020), Response Versus Scan-Angle Assessment of MODIS Reflective Solar Bands in Collection 6.1 Calibration, IEEE Trans. Geosci. Remote Sens., 1-14, doi:10.1109/TGRS.2019.2946963.
- Doelling, D. R., et al. (2019), The Inter-Calibration of the DSCOVR EPIC Imager with Aqua-MODIS and NPP-VIIRS, doi:10.3390/rs11131609.
- Sun-Mack, S., et al. (2019), Calibration Changes to Terra MODIS Collection-5 Radiances for CERES Edition 4 Cloud Retrievals, IEEE Trans. Geosci. Remote Sens., 1-17, doi:10.1109/TGRS.2018.2829902.
- Bedka, K., et al. (2018), The Above-Anvil Cirrus Plume: An Important Severe Weather Indicator in Visible and Infrared Satellite Imagery, Wea. Forecasting, 33, 1159-1181, doi:10.1175/WAF-D-18-0040.1.
- Bhatt, R., et al. (2018), Consideration of Radiometric Quantization Error in Satellite Sensor Cross-Calibration, Remote Sensing, 10, 1131, doi:10.3390/rs10071131.
- Doelling, D. R., et al. (2018), Geostationary Visible Imager Calibration for the CERES SYN1deg Edition 4 Product, Remote Sensing, 10, 288, doi:10.3390/rs10020288.
- 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. (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. (2016), 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:10.1175/JTECH-D-16-0044.1.
- Doelling, D. R., et al. (2016), Improvements to the Geostationary Visible Imager Ray-Matching Calibration Algorithm for CERES Edition 4, J. Atmos. Oceanic Technol., 33, 2679-2698, doi:10.1175/JTECH-D-16-0113.1.
- Doelling, D. R., et al. (2016), A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits. Part II: Validation, J. Atmos. Oceanic Technol., 33, 2517-2534, doi:10.1175/JTECH-D-16-0042.1.
- Bhatt, R., et al. (2014), 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.
- 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. (2013), The Characterization of Deep Convective Clouds as an Invariant Calibration Target and as a Visible Calibration Technique, IEEE Trans. Geosci. Remote Sens., 51, 1147-1159, doi:10.1109/TGRS.2012.2225066.
- Doelling, D. R., et al. (2012), Spectral Reflectance Corrections for Satellite Intercalibrations Using SCIAMACHY Data, IEEE Geosci. Remote Sens. Lett., 9, 119-123, doi:10.1109/LGRS.2011.2161751.