Eric J. Fetzer
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Co-Authored Publications:
- Ding, F., et al. (2020), Assessing the Impacts of Two Averaging Methods on AIRS Level 3 Monthly Products and Multiyear Monthly Means, J. Atmos. Oceanic Technol., 37, 1027-1050, doi:10.1175/JTECH-D-19-0129.1.
- Tian, B., E. J. Fetzer, and E. M. Manning (2019), The Atmospheric Infrared Sounder Obs4MIPs version 2 data set., Earth and Space Science, 6, 324-333, doi:10.1029/2018EA000508.
- Yue, Q., et al. (2019), Temporal and Spatial Characteristics of Short-Term Cloud Feedback on Global and Local Interannual Climate Fluctuations from A-Train Observations, J. Climate, 32, 1875-1893, doi:10.1175/JCLI-D-18-0335.1.
- Guillaume, A., et al. (2018), Horizontal and Vertical Scaling of Cloud Geometry Inferred from CloudSat Data, J. Atmos. Sci., 75, 2187-2197, doi:10.1175/JAS-D-17-0111.1.
- Irion, F. W., et al. (2018), Single-footprint retrievals of temperature, water vapor and cloud properties from AIRS, Atmos. Meas. Tech., 11, 971-995, doi:10.5194/amt-11-971-2018.
- Wong, S., et al. (2018), Coupling of Precipitation and Cloud Structures in Oceanic Extratropical Cyclones to Large-Scale Moisture Flux Convergence, J. Climate, 31, 9565-9584, doi:10.1175/JCLI-D-18-0115.1.
- Kahn, B., et al. (2017), An A-train and MERRA view of cloud, thermodynamic, and dynamic variability within the subtropical marine boundary layer, Atmos. Chem. Phys., 17, 9451-9468, doi:10.5194/acp-17-9451-2017.
- Yue, Q., et al. (2017), On the response of MODIS cloud coverage to global mean surface air temperature, J. Geophys. Res., 122, 966-979, doi:10.1002/2016JD025174.
- Behrangi, A., et al. (2016), Status of high-latitude precipitation estimates from observations and reanalyses, J. Geophys. Res., 121, 4468-4486, doi:10.1002/2015JD024546.
- Devasthale, A., et al. (2016), A Decade Of Spaceborne Observations Of The Arctic Atmosphere: Novel Insights from NASA’s AIRS Instrument, Bull. Am. Meteorol. Soc., 2163, doi:10.1175/BAMS-D-14-00202.1.
- Devasthale, A., et al. (2016), A Decade Of Spaceborne Observations Of The Arctic Atmosphere: Novel Insights from NASA’s AIRS Instrument, Bull. Am. Meteorol. Soc., 97, 2163-2176, doi:10.1175/BAMS-D-14-00202.1.
- Li, J.-L. F., et al. (2016), The impacts of precipitating hydrometeors radiative effects on land surface temperature in contemporary GCMs using satellite observations, J. Geophys. Res., 121, 67-79, doi:10.1002/2015JD023776.
- Wang, T., et al. (2016), Validation of MODIS cloud mask and multilayer flag using CloudSat-CALIPSO cloud profiles and a cross-reference of their cloud classifications, J. Geophys. Res., 121, doi:10.1002/2016JD025239.
- Wong, S., et al. (2016), Responses of Tropical Ocean Clouds and Precipitation to the Large-Scale Circulation: Atmospheric-Water-Budget-Related Phase Space and Dynamical Regimes, J. Climate, 29, 7127-7143, doi:10.1175/JCLI-D-15-0712.1.
- Yue, Q., et al. (2016), Observation-Based Longwave Cloud Radiative Kernels Derived from the A-Train, J. Climate, 29, 2023-2040, doi:10.1175/JCLI-D-15-0257.1.
- Li, J.-L. F., et al. (2015), The impacts of cloud snow radiative effects on Pacific Ocean surface heat fluxes, surface wind stress, and ocean temperatures in coupled GCM simulations, J. Geophys. Res., 120, 2242-2260, doi:10.1002/2014JD022538.
- L'Ecuyer, T., et al. (2015), The Observed State of the Energy Budget in the Early Twenty-First Century, J. Climate, 28, 8319-8346, doi:10.1175/JCLI-D-14-00556.1.
- Hearty, T. J., et al. (2014), Estimating sampling biases and measurement uncertainties of AIRS/AMSU-A temperature and water vapor observations using MERRA reanalysis, J. Geophys. Res., 119, 2725-2741, doi:10.1002/2013JD021205.
- Li, J.-L. F., et al. (2014), Characterizing tropical Pacific water vapor and radiative biases in CMIP5 GCMs: Observation-based analyses and a snow and radiation interaction sensitivity experiment, J. Geophys. Res., 119, 10,981-10,995, doi:10.1002/2014JD021924.
- Tian, B., et al. (2012), Intraseasonal temperature variability in the upper troposphere and lower stratosphere from the GPS radio occultation measurements, J. Geophys. Res., 117, D15110, doi:10.1029/2012JD017715.
- Juárez, M. D., A. B. Davis, and E. J. Fetzer (2011), Scale-by-scale analysis of probability distributions for global MODIS-AQUA cloud properties: how the large scale signature of turbulence may impact statistical analyses of clouds, Atmos. Chem. Phys., 11, 2893-2901, doi:10.5194/acp-11-2893-2011.
- Liang, C. K., et al. (2011), Record of tropical interannual variability of temperature and water vapor from a combined AIRS‐MLS data set, J. Geophys. Res., 116, D06103, doi:10.1029/2010JD014841.
- Wong, S., et al. (2011), The Apparent Water Vapor Sinks and Heat Sources Associated with the Intraseasonal Oscillation of the Indian Summer Monsoon, J. Climate, 24, 4466-4479, doi:10.1175/2011JCLI4076.1.
- Tian, B., et al. (2010), Vertical Moist Thermodynamic Structure of the Madden–Julian Oscillation in Atmospheric Infrared Sounder Retrievals: An Update and a Comparison to ECMWF Interim Re-Analysis, Mon. Wea. Rev., 138, 4576-4582, doi:10.1175/2010MWR3486.1.
- Waliser, D. E., et al. (2009), How well can satellite data characterize the water cycle of the Madden-Julian Oscillation?, Geophys. Res. Lett., 36, L21803, doi:10.1029/2009GL040005.
- Tian, B., et al. (2007), Intraseasonal variations of the tropical total ozone and their connection to the Madden-Julian Oscillation, Geophys. Res. Lett., 34, L08704, doi:10.1029/2007GL029451.
- Tian, B., et al. (2006), Vertical Moist Thermodynamic Structure and Spatial–Temporal Evolution of the MJO in AIRS Observations, J. Atmos. Sci., 63, 2462-2485.
- Tian, B., D. E. Waliser, and E. J. Fetzer (2006), Modulation of the diurnal cycle of tropical deep convective clouds by the MJO, Geophys. Res. Lett., 33, L20704, doi:10.1029/2006GL027752.