Articles | Volume 6, issue 5
Atmos. Meas. Tech., 6, 1227–1243, 2013
https://doi.org/10.5194/amt-6-1227-2013
Atmos. Meas. Tech., 6, 1227–1243, 2013
https://doi.org/10.5194/amt-6-1227-2013

Research article 14 May 2013

Research article | 14 May 2013

Ground-based remote sensing of thin clouds in the Arctic

T. J. Garrett and C. Zhao

Related authors

Identification of a 50-year scaling relating current global energy demands to historically cumulative economic production
Timothy J. Garrett, Matheus R. Grasselli, and Stephen Keen
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-21,https://doi.org/10.5194/esd-2021-21, 2021
Preprint under review for ESD
Short summary
Measurement report: Mass and Density of Individual Frozen Hydrometeors
Karlie Rees, Dhiraj Singh, Eric Pardyjak, and Timothy Garrett
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-179,https://doi.org/10.5194/acp-2021-179, 2021
Preprint under review for ACP
Short summary
A differential emissivity imaging technique for measuring hydrometeor mass and type
Dhiraj K. Singh, Spencer Donovan, Eric R. Pardyjak, and Timothy J. Garrett
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-44,https://doi.org/10.5194/amt-2021-44, 2021
Preprint under review for AMT
Short summary
Arctic observations and numerical simulations of surface wind effects on Multi-Angle Snowflake Camera measurements
Kyle E. Fitch, Chaoxun Hang, Ahmad Talaei, and Timothy J. Garrett
Atmos. Meas. Tech., 14, 1127–1142, https://doi.org/10.5194/amt-14-1127-2021,https://doi.org/10.5194/amt-14-1127-2021, 2021
Short summary
Effect of disdrometer sampling area and time on the precision of precipitation rate measurement
Karlie Rees and Timothy J. Garrett
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-393,https://doi.org/10.5194/amt-2020-393, 2020
Preprint under review for AMT
Short summary

Related subject area

Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Applying machine learning methods to detect convection using Geostationary Operational Environmental Satellite-16 (GOES-16) advanced baseline imager (ABI) data
Yoonjin Lee, Christian D. Kummerow, and Imme Ebert-Uphoff
Atmos. Meas. Tech., 14, 2699–2716, https://doi.org/10.5194/amt-14-2699-2021,https://doi.org/10.5194/amt-14-2699-2021, 2021
Short summary
A new method to detect and classify polar stratospheric nitric acid trihydrate clouds derived from radiative transfer simulations and its first application to airborne infrared limb emission observations
Christoph Kalicinsky, Sabine Griessbach, and Reinhold Spang
Atmos. Meas. Tech., 14, 1893–1915, https://doi.org/10.5194/amt-14-1893-2021,https://doi.org/10.5194/amt-14-1893-2021, 2021
Short summary
A study of polarimetric error induced by satellite motion: application to the 3MI and similar sensors
Souichiro Hioki, Jérôme Riedi, and Mohamed S. Djellali
Atmos. Meas. Tech., 14, 1801–1816, https://doi.org/10.5194/amt-14-1801-2021,https://doi.org/10.5194/amt-14-1801-2021, 2021
Short summary
A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar
Xiaoyu Hu, Jinming Ge, Jiajing Du, Qinghao Li, Jianping Huang, and Qiang Fu
Atmos. Meas. Tech., 14, 1743–1759, https://doi.org/10.5194/amt-14-1743-2021,https://doi.org/10.5194/amt-14-1743-2021, 2021
Short summary
Two-dimensional and multi-channel feature detection algorithm for the CALIPSO lidar measurements
Thibault Vaillant de Guélis, Mark A. Vaughan, David M. Winker, and Zhaoyan Liu
Atmos. Meas. Tech., 14, 1593–1613, https://doi.org/10.5194/amt-14-1593-2021,https://doi.org/10.5194/amt-14-1593-2021, 2021
Short summary

Cited articles

Beesley, J. A.: Estimating the effect of clouds on the arctic surface energy budget, J. Geophys. Res., 105, 10103–10117, 2000.
Bourdages, L., Duck, T. J., Lesins, G., Drummond, J. R., and Eloranta, E. W.: Physical properties of High Arctic tropospheric particles during winter, Atmos. Chem. Phys., 9, 6881–6897, https://doi.org/10.5194/acp-9-6881-2009, 2009.
Campbell, J. R., Hlavka, D. L., Welton, E. J., Flynn, C. J., Turner, D. D., Spinhirne, J. D., and Scott, V. S.: Full-time eye-safe cloud and aerosol lidar observation at atmospheric radiation measurement program sites: Instruments and data processing, J. Atmos. Ocean. Tech., 19, 431–442, 2002.
Cesana, G., Kay, J. E., Chepfer, H., English, J. M., and de Boer, G.: Ubiquitous low-level liquid-containing Arctic clouds: New observations and climate model constraints from CALIPSO-GOCCP, Geophys. Res. Lett., 39, L20804, http://dx.doi.org/10.1029/2012GL053385, 2012.
Chylek, P., Robinson, S., Dubey, M. K., King, M. D., Fu, Q., and Clodius, W. B.: Comparison of near-infrared and thermal infrared cloud phase detections, J. Geophys. Res., 111, D20203, https://doi.org/10.1029/2006JD007140, 2006.
Download