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

Fauchez, Thomas; Platnick, S.; Sourdeval, Odran; Wang, C.; Meyer, Kerry; Cornet, Céline; Szczap, Frédéric

doi:10.1029/2018jd028726

Cited by 9 publications

(6 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…IIR De might be larger than MODIS 3.7 and in better agreement with MODIS 2.1 for opaque clouds at Tr < 220 K because the IIR weighting function is deeper into the cloud than at 3.7 µm, which is agreement with simulations by Zhang et al (2010). In conclusion, distinct sensitivity to 490 possible cloud vertical and horizontal (Fauchez et al, 2018) inhomogeneity likely contributes to the observed differences.…”

Section: Comparisons With Modissupporting

confidence: 69%

Version 4 CALIPSO IIR ice and liquid water cloud microphysical properties, Part II: results over oceans

Pelon¹,

Pichon²,

Vaughan³

et al. 2020

Preprint

View full text Add to dashboard Cite

Abstract. Following the release of the Version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version 4 (V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version (V3) as a result of the significant changes implemented in the V4 algorithms, which are presented in a companion paper (Part I). The analysis of the three-channel IIR observations (08.65 μm, 10.6 μm, and 12.05 μm) is informed by the scene classification provided in the V4 CALIOP 5-km cloud layer and aerosol layer products. Thanks to the reduction of inter-channel effective emissivity biases in semi-transparent (ST) clouds when the oceanic background radiance is derived from model computations, the number of unbiased emissivity retrievals is increased by a factor 3 in V4. In V3, these biases caused inconsistencies between the effective diameters retrieved from the 12/10 and 12/08 pairs of channels at emissivities smaller than 0.5. In V4, microphysical retrievals in ST ice clouds are possible in more than 80 % of the pixels down to effective emissivities of 0.05 (or visible optical depth ~ 0.1). For the month of January 2008 chosen to illustrate the results, median ice De and ice water path (IWP) are, respectively, 38 µm and 3 g⋅m−2 in ST clouds, with random uncertainty estimates of 50 %. The relationship between the V4 IIR 12/10 and 12/08 microphysical indices is in better agreement with the severely roughened single column ice crystal model than with the severely roughened 8-element aggregate model for 80 % of the pixels in the coldest clouds ( 230 K). Retrievals in opaque ice clouds are improved in V4, especially at night and for 12/10 pair of channels, owing to corrections of the V3 radiative temperature estimates derived from CALIOP geometric altitudes. Median ice De and IWP are 58 µm and 97 g⋅m−2 at night in opaque clouds, with again random uncertainty estimates of 50 %. Comparisons of ice retrievals with Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) in the tropics show a better agreement of IIR De with MODIS visible/3.7 µm than with MODIS visible/2.1 µm in the coldest ST clouds and the opposite for opaque clouds. In prevailingly supercooled liquid water clouds with centroid altitudes above 4 km, retrieved median De and liquid water path are 13 µm and 3.4 g.m−2 in ST clouds, with estimated random uncertainties of 45 % and 35 % respectively. In opaque liquid clouds, these values are 18 µm and 31 g.m−2 at night, with estimated uncertainties of 50 %. IIR De in opaque liquid clouds is smaller than MODIS visible/2.1 and visible/3.7 by 8 µm and 3 µm, respectively.

show abstract

Section: Comparisons With Modissupporting

confidence: 69%

Version 4 CALIPSO IIR ice and liquid water cloud microphysical properties, Part II: results over oceans

Pelon¹,

Pichon²,

Vaughan³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Here, average values are reported of at least 1,000 POLDER pixels, and most random errors can be assumed to average out. Local biases because of, for example, subpixel inhomogeneity (Fauchez et al, 2018; Zhang et al, 2016 ) cannot be ruled out. If we take as a measure for inhomogeneity the standard deviation of MODIS cloud optical thicknesses within a POLDER footprint, as provided in the combined POLDER‐MODIS data set, relative to the corresponding mean optical thickness, we find that inhomogeneity increases with mean optical thickness but do not find any other apparent correlation with inhomogeneity and retrieved ice properties.…”

Section: Methods and Datamentioning

confidence: 99%

Global Statistics of Ice Microphysical and Optical Properties at Tops of Optically Thick Ice Clouds

et al. 2020

View full text Add to dashboard Cite

The sizes and shapes of ice crystals in clouds affect fundamental microphysical processes, such as sedimentation and aggregation, as well as their optical properties. The evolution of ice crystal size and shape depends on temperature and supersaturation, as well as on other processes that may lead to various coexisting complex shapes. Here we present a global assessment of collocated size and shape characteristics and shortwave scattering properties of ice crystals at the tops of optically thick clouds inferred from space‐borne multiwavelength reflectance measurements and multiangle polarimetry. The results indicate systematic covariations of ice size, shape, and distortion, as well as variations with temperature that can be plausibly related to simplified ice crystal growth theory and in situ and laboratory data. This simplicity may be attributable to the temperature dependence of cloud top ice size and shapes commonly being dominated by vapor growth at conditions similar to those at cloud top. Such a conclusion may be viewed as somewhat surprising given the expectation that ice properties at cloud top will be an integral manifestation of processes occurring at lower levels within updrafts. We also find that, contrary to commonly used models, ice scattering asymmetry parameters decrease with increasing effective radius, reducing sensitivity of cloud reflectance to particle size.

show abstract

“…In the process of retrieving cloud properties, each cloudy pixel is considered to be independent of its neighboring pixels [64]. Therefore, differences among neighboring MODIS pixel (with the original spatial resolution of 1 km) cloud properties may affect cloud properties of the collocated AHI and AGRI pixels (with product spatial resolutions of 4 km and 5 km).…”

Section: Impact Of Cloud Inhomogeneitymentioning

confidence: 99%

Comparison of Cloud Properties from Himawari-8 and FengYun-4A Geostationary Satellite Radiometers with MODIS Cloud Retrievals

Lai

Teng

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

With the development and the improvement of meteorological satellites, different instruments have significantly enhanced the ability to observe clouds over large spatial regions. Recent geostationary satellite radiometers, e.g., Advanced Himawari Imager (AHI) and Advanced Geosynchronous Radiation Imager (AGRI) onboard the Himawari-8 and the Fengyun-4A satellite, respectively, provide observations over similar regions at higher spatial and temporal resolutions for cloud and atmosphere studies. To better understand the reliability of AHI and AGRI retrieval products, we compare their cloud products with collocated Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products, especially in terms of the cloud optical thickness (COT) and cloud effective radius (CER). Our comparison indicates that cloud mask and cloud phase of these instruments are reasonably consistent, while clear differences are noticed for COT and CER results. The average relative differences (RDs) between AHI and AGRI ice COT and that of MODIS are both over 40%, and the RDs of ice CER are less than 20%. The consistency between AHI and MODIS water cloud results is much better, with the RDs of COT and CER being 29% and 9%, respectively, whereas the RDs of AGRI COT and CER are still larger than 30%. Many factors such as observation geometry, cloud horizontal homogeneity, and retrieval system (e.g., retrieval algorithm, forward model, and assumptions) may contribute to these differences. The RDs of COTs from different instruments for homogeneous clouds are about one-third smaller than the corresponding RDs for inhomogeneous clouds. By applying unified retrieval systems based on the forward radiative transfer models designed for each particular band, we find that 30% to 70% of the differences among the results from different instruments are caused by the retrieval system (e.g., different treatments or assumptions for the retrievals), and the rest may be due to sub-pixel inhomogeneity, parallax errors, and calibration.

show abstract

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

Cited by 9 publications

References 66 publications

Version 4 CALIPSO IIR ice and liquid water cloud microphysical properties, Part II: results over oceans

Version 4 CALIPSO IIR ice and liquid water cloud microphysical properties, Part II: results over oceans

Global Statistics of Ice Microphysical and Optical Properties at Tops of Optically Thick Ice Clouds

Comparison of Cloud Properties from Himawari-8 and FengYun-4A Geostationary Satellite Radiometers with MODIS Cloud Retrievals

Contact Info

Product

Resources

About