An Assessment of the Impacts of Cloud Vertical Heterogeneity on Global Ice Cloud Data Records From Passive Satellite Retrievals

The authors are grateful for support from the NASA Radiation Sciences Program. The computations in this study were performed at the UMBC High Performance Computing Facility (HPCF). The facility is supported by the U.S. National Science Foundation through the MRI program (grants CNS‐0821258 and CNS‐1228778) and the SCREMS program (grant DMS 0821311), with additional substantial support from UMBC. The Collection 6MODIS products (doi: http://dx.doi. org/10.5067/MODIS/MYD06_L2.006) are publicly available from the NASA and Atmosphere Archive and Distribution System (LAADS, http:// ladsweb.nascom.nasa.gov). The CloudSat/CALIPSO 2C‐ICE (version 4; doi:10.1002/2015JD023600) products are publicly available from the CloudSat Data Processing Center (http://www.cloudsat.cira.colostate.edu/data‐products). The instM_3d_asm_Np products (3D,monthly mean instantaneous, pressurelevel,assimilated meteorological fields,version 5.12.4) are from the Modern‐Era Retrospective Analysis for Research and Applications, Version 2 (MERRA‐2; doi: 10.1175/JCLI‐D‐16‐0758.1) and are publicly available from the NASA Goddard Earth Sciences (GES) Data and Information Services Center (https://disc.gsfc.nasa.gov/).

[1]  Steven Platnick,et al.  Impact of three‐dimensional radiative effects on satellite retrievals of cloud droplet sizes , 2006 .

[2]  T. Ackerman,et al.  Relating Cirrus Cloud Properties to Observed Fluxes: A Critical Assessment. , 1995 .

[3]  Roger Davies,et al.  Effects of Cloud Heterogeneities on Shortwave Radiation: Comparison of Cloud-Top Variability and Internal Heterogeneity , 1999 .

[4]  Q. Fu,et al.  Parameterization of the Radiative Properties of Cirrus Clouds , 1993 .

[5]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[6]  T. Andrews,et al.  An update on Earth's energy balance in light of the latest global observations , 2012 .

[7]  Eric J. Fetzer,et al.  Pixel‐scale assessment and uncertainty analysis of AIRS and MODIS ice cloud optical thickness and effective radius , 2015 .

[8]  W. Rossow,et al.  Advances in understanding clouds from ISCCP , 1999 .

[9]  Johannes Quaas,et al.  Frequency of occurrence of rain from liquid‐, mixed‐, and ice‐phase clouds derived from A‐Train satellite retrievals , 2015 .

[10]  Frédéric Parol,et al.  An improved derivation of the top‐of‐atmosphere albedo from POLDER/ADEOS‐2: Narrowband albedos , 2005 .

[11]  L. J. Cox Optical Properties of the Atmosphere , 1979 .

[12]  Bryan A. Baum,et al.  Spectrally Consistent Scattering, Absorption, and Polarization Properties of Atmospheric Ice Crystals at Wavelengths from 0.2 to 100 um , 2013 .

[13]  Jacques Pelon,et al.  Retrieval of Cloud Properties Using CALIPSO Imaging Infrared Radiometer. Part I: Effective Emissivity and Optical Depth , 2012 .

[14]  Mattias Ekström,et al.  Atmospheric Chemistry and Physics Comparison between Early Odin-smr, Aura Mls and Cloudsat Retrievals of Cloud Ice Mass in the Upper Tropical Troposphere , 2022 .

[15]  Hironobu Iwabuchi,et al.  Effects of Cloud Horizontal Inhomogeneity on the Optical Thickness Retrieved from Moderate-Resolution Satellite Data , 2002 .

[16]  Dong L. Wu,et al.  CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances , 2013, Atmospheric Measurement Techniques.

[17]  Jacques Pelon,et al.  A variational approach for retrieving ice cloud properties from infrared measurements: application in the context of two IIR validation campaigns , 2013 .

[18]  P. Eriksson,et al.  An update on global atmospheric ice estimates from satellite observations and reanalyses , 2018, Atmospheric Chemistry and Physics.

[19]  E. O'connor,et al.  The CloudSat mission and the A-train: a new dimension of space-based observations of clouds and precipitation , 2002 .

[20]  Andrew Gettelman,et al.  Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA “A-Train” satellite observations , 2012 .

[21]  K. Shine,et al.  An estimate of the global impact of multiple scattering by clouds on outgoing long‐wave radiation , 2006 .

[22]  Larry Di Girolamo,et al.  Bias in MODIS cloud drop effective radius for oceanic water clouds as deduced from optical thickness variability across scattering angles , 2015 .

[23]  Steven Platnick,et al.  The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: A theoretical study based on large‐eddy simulations of shallow marine boundary layer clouds , 2016, Journal of geophysical research. Atmospheres : JGR.

[24]  Kerry Meyer,et al.  A framework based on 2‐D Taylor expansion for quantifying the impacts of subpixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral method , 2016, Journal of geophysical research. Atmospheres : JGR.

[25]  Steven Platnick,et al.  The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples From Terra and Aqua , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[26]  Jana Mendrok,et al.  SPARE‐ICE: Synergistic ice water path from passive operational sensors , 2014 .

[27]  Brad Baker,et al.  Improvement in Determination of Ice Water Content from Two-Dimensional Particle Imagery. Part I: Image-to-Mass Relationships , 2006 .

[28]  Fuzhong Weng,et al.  NOAA operational hydrological products derived from the advanced microwave sounding unit , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[29]  Xianglei Huang,et al.  An Observationally Based Global Band-by-Band Surface Emissivity Dataset for Climate and Weather Simulations , 2016 .

[30]  Mathias Milz,et al.  Assessing observed and modelled spatial distributions of ice water path using satellite data , 2011 .

[31]  Sunny Sun-Mack,et al.  CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data—Part I: Algorithms , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[32]  H. Deneke,et al.  View angle dependence of MODIS liquid water path retrievals in warm oceanic clouds , 2014, Journal of geophysical research. Atmospheres : JGR.

[33]  C. Kuo,et al.  Impact of Multiple Scattering on Longwave Radiative Transfer Involving Clouds , 2017 .

[34]  Zhibo Zhang,et al.  Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 2. Retrieval evaluation , 2016 .

[35]  Robert Wood,et al.  The effect of solar zenith angle on MODIS cloud optical and microphysical retrievals within marine liquid water clouds , 2014 .

[36]  J. Otkin,et al.  Comparison of WRF Model-Simulated and MODIS-Derived Cloud Data , 2008 .

[37]  G. Mace,et al.  Tropical composition, cloud and climate coupling experiment validation for cirrus cloud profiling retrieval using cloudsat radar and CALIPSO lidar , 2010 .

[38]  Andi Walther,et al.  The Pathfinder Atmospheres–Extended AVHRR Climate Dataset , 2014 .

[39]  M. Zelinka,et al.  An Analysis of the Short-Term Cloud Feedback Using MODIS Data , 2013 .

[40]  Steven Platnick,et al.  Retrieval of Ice Cloud Optical Thickness and Effective Particle Size Using a Fast Infrared Radiative Transfer Model , 2011 .

[41]  Simone Tanelli,et al.  Comparisons of global cloud ice from MLS, CloudSat, and correlative data sets , 2009 .

[42]  W. Paul Menzel,et al.  Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[43]  Ákos Horváth,et al.  Global assessment of AMSR-E and MODIS cloud liquid water path retrievals in warm oceanic clouds , 2009 .

[44]  J. Delanoë,et al.  Ice water content vertical profiles of high-level clouds: classification and impact on radiative fluxes , 2015 .

[45]  Jacques Pelon,et al.  Retrieval of Cloud Properties Using CALIPSO Imaging Infrared Radiometer. Part II: Effective Diameter and Ice Water Path , 2013 .

[46]  M. Flanner,et al.  Sensitivity of modeled far‐IR radiation budgets in polar continents to treatments of snow surface and ice cloud radiative properties , 2014 .

[47]  Roger Davies,et al.  Comparison of Microwave and Optical Cloud Water Path Estimates From TMI, MODIS, and MISR , 2007 .

[48]  J. Dufresne,et al.  Diagnosis of regime‐dependent cloud simulation errors in CMIP5 models using “A‐Train” satellite observations and reanalysis data , 2013 .

[49]  Moustafa T. Chahine,et al.  The hydrological cycle and its influence on climate , 1992, Nature.

[50]  Zhien Wang,et al.  A global view of midlevel liquid-layer topped stratiform cloud distribution and phase partition from CALIPSO and CloudSat measurements , 2010 .

[51]  F. Szczap,et al.  Scale Dependence of Cirrus Horizontal Heterogeneity Effects on TOA Measurements. Part I; MODIS Brightness Temperatures in the Thermal Infrared , 2017 .

[52]  M. King,et al.  Determination of the optical thickness and effective particle radius of clouds from reflected solar , 1990 .

[53]  Steven Platnick,et al.  Effects of ice particle size vertical inhomogeneity on the passive remote sensing of ice clouds , 2010 .

[54]  Larry Di Girolamo,et al.  Impacts of 3‐D radiative effects on satellite cloud detection and their consequences on cloud fraction and aerosol optical depth retrievals , 2008 .

[55]  David M. Winker,et al.  The global 3-D distribution of tropospheric aerosols as characterized by CALIOP , 2012 .

[56]  J. Bacmeister,et al.  Development of two-moment cloud microphysics for liquid and ice within the NASA Goddard Earth Observing System Model (GEOS-5) , 2013 .

[57]  S. Twomey,et al.  Remote sensing of cloud parameters from spectral reflectance in the near-infrared , 1989 .

[58]  Matthew Bailey,et al.  Nucleation effects on the habit of vapour grown ice crystals from −18 to −42°C , 2002 .

[59]  J. Pelon,et al.  Impacts of cloud heterogeneities on cirrus optical properties retrieved from space-based thermal infrared radiometry , 2014 .

[60]  T. L’Ecuyer,et al.  Information content of visible and midinfrared radiances for retrieving tropical ice cloud properties , 2017 .

[61]  M. Pieters,et al.  Coronal heating and solar wind acceleration for electrons, protons, and minor ions obtained from kinetic models based on kappa distributions , 2014 .

[62]  Steven Platnick,et al.  Vertical Photon Transport in Cloud Remote Sensing Problems , 2013 .

[63]  Eni G. Njoku,et al.  Global water cycle agreement in the climate models assessed in the IPCC AR4 , 2007 .

[64]  R. Wood,et al.  Spatial variability of liquid water path in marine low cloud : The importance of mesoscale cellular convection , 2006 .

[65]  A. Davis,et al.  A fast hybrid (3‐D/1‐D) model for thermal radiative transfer in cirrus via successive orders of scattering , 2017 .

[66]  Bin Zhao,et al.  The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). , 2017, Journal of climate.

[67]  Michael D. King,et al.  A comparison of Aqua MODIS ice and liquid water cloud physical and optical properties between collection 6 and collection 5.1: Pixel‐to‐pixel comparisons , 2017 .

[68]  Chao Liu,et al.  Effects and Applications of Satellite Radiometer 2.25- $\mu$ m Channel on Cloud Property Retrievals , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[69]  G. Mace,et al.  CloudSat 2C‐ICE product update with a new Ze parameterization in lidar‐only region , 2015, Journal of geophysical research. Atmospheres : JGR.

[70]  Clive D Rodgers,et al.  Inverse Methods for Atmospheric Sounding: Theory and Practice , 2000 .

[71]  Gerald G. Mace,et al.  The CloudSat radar‐lidar geometrical profile product (RL‐GeoProf): Updates, improvements, and selected results , 2014 .

[72]  Steven Platnick,et al.  A global view of one‐dimensional solar radiative transfer through oceanic water clouds , 2010 .

[73]  S. Miller,et al.  Liquid‐top mixed‐phase cloud detection from shortwave‐infrared satellite radiometer observations: A physical basis , 2014 .

[74]  H. Chepfer,et al.  Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel , 2013 .

[75]  Dong L. Wu,et al.  Cloud ice: A climate model challenge with signs and expectations of progress , 2007 .

[76]  Rob Roebeling,et al.  Cloud property retrievals for climate monitoring: Implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT‐8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA‐17 , 2006 .

[77]  Zhibo Zhang,et al.  Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 1. Forward model, error analysis, and information content , 2016, Journal of geophysical research. Atmospheres : JGR.

[78]  B. Cairns,et al.  Vertical variation of ice particle size in convective cloud tops , 2016, Geophysical research letters.

[79]  G. McFarquhar,et al.  Cloud Ice Properties: In Situ Measurement Challenges , 2017 .

[80]  Andrew J. Heymsfield,et al.  The Dimensional Characteristics of Ice Crystal Aggregates from Fractal Geometry , 2010 .

[81]  Shepard A. Clough,et al.  Atmospheric radiative transfer modeling: a summary of the AER codes , 2005 .

[82]  Steven Platnick,et al.  Influence of ice particle model on satellite ice cloud retrieval: lessons learned from MODIS and POLDER cloud product comparison , 2009 .

[83]  H. Morrison,et al.  Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part I: Scheme Description and Idealized Tests , 2015 .

[84]  Steven Platnick,et al.  Effects of Cloud Horizontal Inhomogeneity and Drizzle on Remote Sensing of Cloud Droplet Effective Radius: Case Studies Based on Large-eddy Simulations , 2012 .

[85]  F. Szczap,et al.  Cirrus Horizontal Heterogeneity and 3‐D Radiative Effects on Cloud Optical Property Retrievals From MODIS Near to Thermal Infrared Channels as a Function of Spatial Resolution , 2018, Journal of Geophysical Research: Atmospheres.

[86]  S. Platnick,et al.  Cirrus cloud optical and microphysical property retrievals from eMAS during SEAC4RS using bi-spectral reflectance measurements within the 1.88 μm water vapor absorption band. , 2016, Atmospheric measurement techniques.

[87]  Fuzhong Weng,et al.  Impact of the Vertical Variation of Cloud Droplet Size on the Estimation of Cloud Liquid Water Path and Rain Detection , 2007 .

[88]  Matthew Bailey,et al.  Growth Rates and Habits of Ice Crystals between −20° and −70°C , 2004 .

[89]  S. Kato,et al.  Vertical structure of ice cloud layers from CloudSat and CALIPSO measurements and comparison to NICAM simulations , 2013 .

[90]  Steven Platnick,et al.  A Validation of a Satellite Cloud Retrieval during ASTEX , 1995 .

[91]  Christian D. Kummerow,et al.  The Remote Sensing of Clouds and Precipitation from Space: A Review , 2007 .

[92]  H. Iwabuchi,et al.  Vertical Profiles of Ice Cloud Microphysical Properties and Their Impacts on Cloud Retrieval Using Thermal Infrared Measurements , 2018 .

[93]  K. Stamnes,et al.  Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. , 1988, Applied optics.

[94]  Steven Platnick,et al.  Differences Between Collection 4 and 5 MODIS Ice Cloud Optical/Microphysical Products and Their Impact on Radiative Forcing Simulations , 2007, IEEE Transactions on Geoscience and Remote Sensing.