Organization
NASA Langley Research Center
Science Systems and Applications, Inc.
First Author Publications
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Palikonda, R., et al. (2005), Contrail coverage derived from 2001 AVHRR data over the continental United States of America and surrounding areas, Meteorologische Zeitschrift, 14, 525-536, doi:10.1127/0941-2948/2005/0051.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.
Co-Authored Publications
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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.
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Albrecht, B., et al. (2019), Cloud System Evolution In The Trades (Cset): Following Evolution of Boundary Layer Cloud Systems with the NSF-NCAR GV, Bull. Am. Meteorol. Soc., 100, 93-121, doi:10.1175/BAMS-D-17-0180.1.
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Kurzrock, F., et al. (2019), Evaluation of WRF-DART (ARW v3.9.1.1 and DART Manhattan release) multiphase cloud water path assimilation for short-term solar irradiance forecasting in a tropical environment, Geosci. Model. Dev., 12, 3939-3954, doi:10.5194/gmd-12-3939-2019.
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Jones, T., et al. (2018), Comparison of Cloud Microphysics Schemes in a Warn-on-Forecast System Using Synthetic Satellite Objects, Jones Et Al., doi:10.1175/WAF-D-18-0112.1.
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McHardy, T.M., et al. (2018), Comparison of Daytime Low-Level Cloud Properties Derived From GOES and ARM SGP Measurements, J. Geophys. Res., 123, 8221-8237, doi:10.1029/2018JD028911.
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Yost, C.R., 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.
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Painemal, D., et al. (2017), Entrainment rate diurnal cycle in marine stratiform clouds estimated from geostationary satellite retrievals and a meteorological forecast model, Geophys. Res. Lett., 44, doi:10.1002/2017GL074481.
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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.
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Smith, W.L., et al. (2017), Arctic Radiation-Icebridge Sea And Ice Experiment: The Arctic Radiant Energy System during the Critical Seasonal Ice Transition, Bull. Am. Meteorol. Soc., 1399-1426, doi:10.1175/BAMS-D-14-00277.1.
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Creamean, J.M., et al. (2016), The relationships between insoluble precipitation residues, clouds, and precipitation over California’s southern Sierra Nevada during winter storms, Atmos. Environ., 140, 298-310, doi:10.1016/j.atmosenv.2016.06.016.
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Jones, T., et al. (2016), Storm-Scale Data Assimilation and Ensemble Forecasting with the NSSL Experimental Warn-on-Forecast System. Part II: Combined Radar and Satellite Data Experiments, Wea. Forecasting, 297, 297-327, doi:10.1175/WAF-D-15-0107.1.
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Chen, Y., et al. (2015), Variational Assimilation of Cloud Liquid/Ice Water Path and Its Impact on NWP, J. Appl. Meteor. Climat., 54, 1809-1825, doi:10.1175/JAMC-D-14-0243.1.
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Jones, T., et al. (2015), Simultaneous Radar and Satellite Data Storm-Scale Assimilation Using an Ensemble Kalman Filter Approach for 24 May 2011, Mon. Wea. Rev., 143, 165-194, doi:10.1175/MWR-D-14-00180.1.
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Painemal, D., et al. (2015), Mean Structure and Diurnal Cycle of Southeast Atlantic Boundary Layer Clouds: Insights from Satellite Observations and Multiscale Modeling Framework Simulations, J. Climate, 28, 324-341, doi:10.1175/JCLI-D-14-00368.1.
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Wood, R., et al. (2015), Clouds, Aerosols, And Precipitation In The Marine Boundary Layer: An ARM Mobile Facility Deployment, Bull. Am. Meteorol. Soc., 419.
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Hamann, U., et al. (2014), Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms, Atmos. Meas. Tech., 7, 2839-2867, doi:10.5194/amt-7-2839-2014.
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Painemal, D., et al. (2014), Mean Structure and diurnal cycle of Southeast Atlantic boundary layer clouds: Insights from satellite observations and multiscale modeling framework simulations, J. Climate-46 (submitted).
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Bedka, S., et al. (2013), Properties of linear contrails in the Northern Hemisphere derived from 2006 Aqua MODIS observations, Geophys. Res. Lett., 40, 1-6, doi:10.1029/2012GL054363.
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Jones, T., et al. (2013), Evaluation of a Forward Operator to Assimilate Cloud Water Path into WRF-DART, Mon. Wea. Rev., 141, 2272-2289, doi:10.1175/MWR-D-12-00238.1.
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Mecikalski, J., et al. (2013), Use of satellite derived cloud properties to quantify growing cumulus beneath cirrus clouds, Atmos. Res., 120–121, 192-201, doi:10.1016/j.atmosres.2012.08.017.
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Minnis, P., et al. (2013), Linear contrail and contrail cirrus properties determined from satellite data, Geophys. Res. Lett., 40, 3220-3226, doi:10.1002/grl.50569.
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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.
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Spangenberg, D., et al. (2013), Contrail radiative forcing over the Northern Hemisphere from 2006 Aqua MODIS data, Geophys. Res. Lett., 40, 1-6, doi:10.1002/GRL.50168.
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Jean-Paul, J.J., et al. (2013), Comment on “Large Volcanic Aerosol Load in the Stratosphere Linked to Asian Monsoon Transport”, Science, 339, 647-d, doi:10.1126/science.1227817.
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Smith, W.L., et al. (2012), Determining the Flight Icing Threat to Aircraft with Single-Layer Cloud Parameters Derived from Operational Satellite Data, J. Appl. Meteor. Climat., 51, 1794-1810, doi:10.1175/JAMC-D-12-057.1.
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Minnis, P., et al. (2011), CERES Edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data, Part II: Examples of average results and comparisons with other data, IEEE Trans. Geosci. Remote Sens., 49, 11-2892).
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Minnis, P., et al. (2011), CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data—Part II: Examples of Average Results and Comparisons With Other Data, IEEE Trans. Geosci. Remote Sens., 49, 4401-4430, doi:10.1109/TGRS.2011.2144602.
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Wood, R., et al. (2011), The VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx): goals, platforms, and field operations, Atmos. Chem. Phys., 11, 627-654, doi:10.5194/acp-11-627-2011.
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Chang, F., et al. (2010), A modified method for inferring upper troposphere cloud top height using the GOES 12 imager 10.7 and 13.3 mm data, J. Geophys. Res., 115, D06208, doi:10.1029/2009JD012304.
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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.
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Duda, D., et al. (2009), Relating observations of contrail persistence to numerical weather analysis output, Atmos. Chem. Phys., 9, 1357-1364, doi:10.5194/acp-9-1357-2009.
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Yost, C.R., et al. (2009), Parameterization of cirrus microphysical property profiles using GOES, CloudSat, and CALIPSO data. Eos Trans., AGU, 90, 14-17.
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Smith, W.L., et al. (2008), An evaluation of operational GOES-derived single-layer cloud top heights with ARSCL data over the ARM Southern Great Plains Site, Geophys. Res. Lett., 35, L13820, doi:10.1029/2008GL034275.
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Duda, D., et al. (2005), Estimated contrail frequency and coverage over the contiguous United States from numerical weather prediction analyses and flight track data, Meteorologische Zeitschrift, 14, 537-548, doi:10.1127/0941-2948/2005/0050.
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Minnis, P., et al. (2005), Contrail properties over the eastern North Pacific from AVHRR data, Meteorologische Zeitschrift, 14, 515-523, doi:10.1127/0941-2948/2005/0056.
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Duda, D., et al. (2004), A Case Study of the Development of Contrail Clusters over the Great Lakes, J. Atmos. Sci., 61, 1132-1146.
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Minnis, P., et al. (2004), Contrails, Cirrus Trends, and Climate, J. Climate, 17, 1671-1685.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.