Chris Yost
Organization:
NASA Langley Research Center
Science Systems and Applications, Inc.
First Author Publications:
- Yost, C., et al. (2021), CERES MODIS Cloud Product Retrievals for Edition 4—Part II: Comparisons to CloudSat and CALIPSO, IEEE Trans. Geosci. Remote Sens., 59, 3695-3724, doi:10.1109/TGRS.2020.3015155.
- Yost, C., et al. (2018), A prototype method for diagnosing high ice water content probability using satellite imager data, Atmos. Meas. Tech., 11, 1615-1637, doi:10.5194/amt-11-1615-2018.
- Yost, C., et al. (2010), Comparison of GOES‐retrieved and in situ measurements of deep convective anvil cloud microphysical properties during the Tropical Composition, Cloud and Climate Coupling Experiment (TC4), J. Geophys. Res., 115, D00J06, doi:10.1029/2009JD013313.
- Yost, C., et al. (2009), Parameterization of cirrus microphysical property profiles using GOES, CloudSat, and CALIPSO data. Eos Trans., AGU, 90, 14-17.
Co-Authored Publications:
- Minnis, P., et al. (2023), VIIRS Edition 1 Cloud Properties for CERES, Part 1: Algorithm Adjustments and Results, Algorithm Adjustments and Results. Remote Sens., 15, 578, doi:10.3390/rs15030578.
- 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.
- Bedka, K., et al. (2019), Analysis and Automated Detection of Ice Crystal Icing Conditions Using Geostationary Satellite Datasets and In Situ Ice Water Content Measurements, SAE Technical Paper, 2019-01-1953, 2019, doi:10.4271/2019-01-1953.
- Bedka, K., et al. (2019), Analysis and Automated Detection of Ice Crystal Icing Conditions Using Geostationary Satellite Datasets and In Situ Ice Water Content Measurements, SAE Technical Paper, 2019-01-1953, 2019, doi:10.4271/2019-01-1953.
- Trepte, Q. Z., et al. (2019), Global Cloud Detection for CERES Edition 4 Using Terra and Aqua MODIS Data, IEEE Trans. Geosci. Remote Sens., 57, 9410-9449, doi:10.1109/TGRS.2019.2926620.
- Painemal, D., et al. (2017), Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship-based and satellite remote sensing observations, J. Geophys. Res., 122, 2403-2418, doi:10.1002/2016JD025771.
- 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. (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.
- Minnis, P., et al. (2012), Simulations of Infrared Radiances over a Deep Convective Cloud System Observed during TC4: Potential for Enhancing Nocturnal Ice Cloud Retrievals, Remote Sens., 4, 3022-3054, doi:10.3390/rs4103022.
- Chang, F., et al. (2010), Evaluation of satellite‐based upper troposphere cloud top height retrievals in multilayer cloud conditions during TC4, J. Geophys. Res., 115, D00J05, doi:10.1029/2009JD013305.
- Garrett, K. J., et al. (2009), Influence of Cloud-Top Height and Geometric Thickness on a MODIS Infrared-Based Ice Cloud Retrieval, J. Appl. Meteor. Climat., 48, 818-832, doi:10.1175/2008JAMC1915.1.
- Minnis, P., et al. (2008), Estimating the top altitude of optically thick ice clouds from thermal infrared satellite observations using CALIPSO data, Geophys. Res. Lett., 35, L12801, doi:10.1029/2008GL033947.