Analysis of Cloud Thermodynamic Phase
Using A­Train Observations
S. Zeng, J. Riedi, F. Thieuleux, C. Cornet and F. Parol Laboratoire d'Optique Atmosphérique, Université Lille 1 – Sciences et Technologies, France
ABSTRACT : The global spatial and diurnal distribution of cloud properties is a key issue for understanding the hydrological cycle, and critical for advancing efforts to improve numerical weather models and general circulation models. Satellite data provides the best way of gaining insight into global cloud properties. In particular, the determination of cloud thermodynamic phase is a critical first step in the process of inferring cloud optical and microphysical properties from satellite measurements. It is important that cloud phase be derived together with an estimate of the confidence of this determination, so that this information can be included with subsequent retrievals (optical thickness, effective particle radius, and ice/liquid water content).
In this study, we compared two different and well documented cloud phase products derived from POLDER3/PARASOL (POLarization and Directionality of the Earth Reflectances) and MODIS/AQUA (MODerate resolution Imaging Spectroradiometer) operating in the framework of the A­Train mission. Both POLDER and MODIS have been used to derive key parameters needed to improve our knowledge of cloud properties (Platnick et al, 2003; Parol et al 2004). The potential of using polarization measurements of the reflected shortwave radiation to infer cloud phase has been clearly demonstrated using POLDER observations (Goloub et al, 2000; Riedi et al 2001). The MODIS instrument provides information on cloud phase using two methods that rely on spectral measurements in the visible, shortwave to midrange infrared, and thermal infrared (Platnick et al, 2003). Both the instruments and the specifically designed retrieval algorithms have limitations that need to be understood and recognized to prevent drawing misleading conclusions from analysis of the data products. Products are analyzed globally and focus is made on identification and attribution of main differences. The analysis is carried out by analyzing differences and agreement between the two datasets in view of observations provided by CALIPSO. This in particular, allow us to understand and quantify the impact of thin cirrus and multilayer cloud systems on global statistics of cloud thermodynamic phase derived from POLDER and MODIS. Global POLDER/MODIS agreement and confusion
Figure 1. Global statistics of agreement and confusion in cloud phase identification from POLDER and MODIS for one year period from Dec 2007 to November 2008. Results are presented for different cloud systems and surface type.
Identification of algorithm angular biases
Global
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liquid,
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Figure 2. Global distribution of agreement and confusion in cloud phase identification from POLDER and MODIS for one year period from Dec 2007 to November 2008. Results are presented in terms of cloud fraction for each class.
Sensitivity to thin cirrus
The authors are very grateful to CNES and NASA for providing the POLDER, MODIS, and CALIOP data used in this study. We thank the ICARE Data and Services Center for providing access to the data and for general assistance and development support. This research has been supported by CNES, CNRS, the University of Lille, and Region Nord­
Pas­de­Calais.
CALIOP sampling zone
Figure 3. Angular occurrence frequency of phases (a) and frequency of agreement and confusion in cloud phase identification (b) from POLDER and MODIS for one year period from Dec 2007 to November 2008.
Acknowledgements :
Figure 4. Phase detection vs top cirrus layer optical thickness determined from CALIOP.
Validation of POLDER/MODIS Phase against CALIOP observations : case of opaque clouds
Figure 6. Statistics of liquid and ice fractions determined by CALIPSO for each POLDER vs MODIS class.
Goloub, P., Herman, M., Chepfer, H., Riedi, J., Brogniez, G., Couvert, P. and S´eze, G: Cloud Thermodynamical Phase Classification from the POLDER Spaceborne instrument, J. Geophy. Res., 105, 14 747–14 759, 2000.
Parol, P., Buriez, J. C., Vanbauce, C., Riedi, J., Labonnote, L. C., Doutriaux­Boucher, M., Vesperini, M., Seze, G., Couvert, P., Viollier, M., Bréon, F. M.: Capabilities of multi­angle polarization cloud measurements from satellite: POLDER results, Adv. Space Res., 33, 1080–1088.
Platnick S., King, M. D., Ackerman, S. A., Menzel, W. P., Baum, B. A., Riedi, J., and Frey, R. A.: The MODIS Cloud Products : Algorithms and Examples from Terra. IEEE, Trans. Geo. And Remote Sensing, 41, 459–473, 2003. Riedi J., Goloub, P., and Marchand, R. T.: Comparison of POLDER cloud phase retrievals to active remote sensors measurements at the ARM SGP site. Geophys. Res. Lett., 28–11, 2185–2188, 2001.
LOA, 15th June 2010
Figure 5. Statistics of integrated backscatter signal against depolarization ratio observed by CALIOP for opaque clouds as a function of POLDER vs MODIS cloud phase decision.