Cloud-Base Height Estimation from VIIRS. Part II: A Statistical Algorithm Based on A-Train Satellite Data

AbstractKnowledge of cloud-base height (CBH) is important to describe cloud radiative feedbacks in numerical models and is of practical relevance to the aviation community. Whereas satellite remote sensing with passive radiometers traditionally has provided a ready means for estimating cloud-top height (CTH) and cloud water path (CWP), assignment of CBH requires heavy assumptions on the distribution of CWP within the cloud profile. An attempt to retrieve CBH has been included as part of the VIIRS environmental data records, produced operationally as part of the Suomi–National Polar-Orbiting Partnership (SNPP) and the forthcoming Joint Polar Satellite System. Through formal validation studies tied to the program, it was found that the operational CBH algorithm failed to meet performance specifications in many cases. This paper presents a new methodology for retrieving CBH of the uppermost cloud layer, developed through statistical analyses relating cloud geometric thickness (CGT) to CTH and CWP. The semiem...

[1]  Robert L. Vislocky,et al.  An Automated, Observations-Based System for Short-Term Prediction of Ceiling and Visibility , 1997 .

[2]  Tobias Wehr,et al.  A 3D cloud‐construction algorithm for the EarthCARE satellite mission , 2011 .

[3]  P.,et al.  ESTIMATION OF LOW CLOUD BASE HEIGHTS AT NIGHT FROM SATELLITE INFRARED AND SURFACE TEMPERATURE DATA , 2011 .

[4]  Howard W. Barker,et al.  Satellite‐based estimation of cloud‐base heights using constrained spectral radiance matching , 2016 .

[5]  John M. Forsythe,et al.  How Total Precipitable Water Vapor Anomalies Relate to Cloud Vertical Structure , 2012 .

[6]  Jonathan H. Jiang,et al.  Touring the Atmosphere Aboard the A‐Train , 2011 .

[7]  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.

[8]  Michael J. Pavolonis,et al.  Gazing at Cirrus Clouds for 25 Years through a Split Window. Part I: Methodology , 2009 .

[9]  Keith D. Hutchison,et al.  Retrieval of cloud base heights from passive microwave and cloud top temperature data , 2000, IEEE Trans. Geosci. Remote. Sens..

[10]  R. Marchand,et al.  Hydrometeor Detection Using Cloudsat—An Earth-Orbiting 94-GHz Cloud Radar , 2008 .

[11]  Steven D. Miller,et al.  Estimating Three-Dimensional Cloud Structure via Statistically Blended Satellite Observations , 2014 .

[12]  Ralf Bennartz,et al.  Global assessment of marine boundary layer cloud droplet number concentration from satellite , 2007 .

[13]  K. Hutchison,et al.  The retrieval of cloud base heights from MODIS and three-dimensional cloud fields from NASA's EOS Aqua mission , 2002 .

[14]  D. Mccleese,et al.  Cloud top heights from temperature sounding instruments , 1976 .

[15]  Caren Marzban,et al.  Ceiling and Visibility Forecasts via Neural Networks , 2007 .

[16]  Steven Platnick,et al.  Retrieval of Cirrus Cloud Optical Depth under Day and Night Conditions from MODIS Collection 6 Cloud Property Data , 2015, Remote. Sens..

[17]  Bjarne Hansen.  A Fuzzy Logic-Based Analog Forecasting System for Ceiling and Visibility , 2007 .

[18]  David R. Doelling,et al.  Cloud Thickness Estimation from GOES-8 Satellite Data Over the ARM-SGP Site , 2002 .

[19]  Michael J. Pavolonis,et al.  Daytime Cloud Overlap Detection from AVHRR and VIIRS , 2004 .

[20]  Jun Li,et al.  Evaluation of single field‐of‐view cloud top height retrievals from hyperspectral infrared sounder radiances with CloudSat and CALIPSO measurements , 2013 .

[21]  Gsfc Jpss Cmo.  Joint Polar Satellite System (JPSS) VIIRS Cloud Base Height Algorithm Theoretical Basis Document (ATBD) , 2011 .

[22]  Andi Walther,et al.  Implementation of the Daytime Cloud Optical and Microphysical Properties Algorithm (DCOMP) in PATMOS-x , 2012 .

[23]  M. Goldberg,et al.  Joint Polar Satellite System: The United States next generation civilian polar‐orbiting environmental satellite system , 2013 .

[24]  Keith D. Hutchison,et al.  Cloud base heights retrieved during night‐time conditions with MODIS data , 2006 .

[25]  Donald L. Reinke,et al.  Cloud-Base Height Estimates Using a Combination of Meteorological Satellite Imagery and Surface Reports , 2000 .

[26]  Steven D. Miller,et al.  The expected performance of cloud optical and microphysical properties derived from Suomi NPP VIIRS day/night band lunar reflectance , 2013 .

[27]  Donald W. Hillger,et al.  First-Light Imagery from Suomi NPP VIIRS , 2013 .

[28]  David A. Randall,et al.  Cloud Parameterization for Climate Modeling: Status and Prospects , 1989 .

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

[30]  D. Winker,et al.  Overview of the CALIPSO Mission and CALIOP Data Processing Algorithms , 2009 .

[31]  A. Slingo,et al.  The response of a general circulation model to cloud longwave radiative forcing. I: Introduction and initial experiments , 1988 .

[32]  W. Paul Menzel,et al.  MODIS Global Cloud-Top Pressure and Amount Estimation: Algorithm Description and Results , 2008 .

[33]  Mona Witkowski,et al.  CloudSat Anomaly Recovery and Operational Lessons Learned , 2012 .

[34]  Steven D. Miller,et al.  Cloud-Base Height Estimation from VIIRS. Part I: Operational Algorithm Validation against CloudSat , 2017 .

[35]  William L. Smith,et al.  Improved Cloud Motion Wind Vector and Altitude Assignment Using VAS. , 1983 .

[36]  Hung-Lung Huang,et al.  Cloudy sounding and cloud-top height retrieval from AIRS alone single 1 field-of-view radiance measurements 2 3 , 2007 .

[37]  Susanne Crewell,et al.  Cloud base height retrieval from multi-angle satellite data , 2018, Atmospheric Measurement Techniques.

[38]  Patrick Minnis,et al.  Aviation Applications for Satellite-Based Observations of Cloud Properties, Convection Initiation, In-Flight Icing, Turbulence, and Volcanic Ash , 2007 .