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Comparison of Co-Incident MISR, Terra MODIS and ISS-CATS Cloud Top Heights
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  • Arka Mitra,
  • Larry Di Girolamo,
  • Yulan Hong,
  • Yizhe Zhan,
  • Kevin Mueller
Arka Mitra
University of Illinois

Corresponding Author:[email protected]

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Larry Di Girolamo
University of Illinois
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Yulan Hong
University of Illinois
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Yizhe Zhan
Metservice, New Zealand
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Kevin Mueller
Jet Propulsion Laboratory, California Institute of Technology
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Abstract

Cloud-top heights (CTH) from the Multiangle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra constitute our longest-running single-platform CTH record from a stable orbit. Here, we provide the first evaluation of the Terra Level 2 CTH record against collocated International Space Station Cloud-Aerosol Transport System (CATS) lidar observations between 50ºN - 50ºS. Bias and precision of Terra CTH relative to CATS, calculated from the normality of CTH error histograms, are shown to be strongly tied to cloud horizontal and vertical heterogeneity and altitude. For single-layered, unbroken, optically thick clouds observed for all altitudes, the uncertainty in MODIS and MISR CTH are -540±690 m and -280±370 m, respectively. The uncertainties are generally smaller for lower altitude clouds and larger for optically thinner clouds. For multi-layered clouds, errors are summarized herein using both absolute CTH and CATS-layer-altitude proximity to Terra CTH. We show that MISR detects the lower cloud in a two-layered system, provided top-layer optical depth < ~0.3, but MISR low-cloud errors are unaltered by the presence of thin cirrus. Systematic and random errors are propagated to explain inter-sensor disagreements, as well as to provide the first estimate of MISR stereo-opacity bias. For MISR, altitude-dependent wind-retrieval bias (-90 to -110 m) and stereo-opacity bias (-110 to -240 m) and for MODIS, bias due to low opacity near cloud-top lead to overall negative CTH bias. MISR’s precision is largely driven by wind-speed uncertainty (3.7 m s-1), whereas MODIS precision is driven by forward-modeling uncertainty.