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Application of Aircraft Observations over Beijing in Cloud Microphysical Property Retrievals from CloudSat 被引量:4

Application of Aircraft Observations over Beijing in Cloud Microphysical Property Retrievals from CloudSat
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摘要 Cloud microphysical property retrievals from the active microwave instrument on a satellite require the cloud droplet size distribution obtained from aircraft observations as a priori data in the iteration procedure.The cloud lognormal size distributions derived from 12 flights over Beijing,China,in 2008-09 were characterized to evaluate and improve regional CloudSat cloud water content retrievals.We present the distribution parameters of stratiform cloud droplet (diameter <500 tm and <1500 μm) and discuss the effect of large particles on distribution parameter fitting.Based on three retrieval schemes with different lognormal size distribution parameters,the vertical distribution of cloud liquid and ice water content were derived and then compared with the aircraft observations.The results showed that the liquid water content (LWC) retrievals from large particle size distributions were more consistent with the vertical distribution of cloud water content profiles derived from in situ data on 25 September 2006.We then applied two schemes with different a priori data derived from flight data to CloudSat overpasses in northern China during April-October in 2008 and 2009.The CloudSat cloud water path (CWP) retrievals were compared with Moderate Resolution Imaging Spectroradiometer (MODIS) liquid water path (LWP) data.The results indicated that considering a priori data including large particle size information can significantly improve the consistency between the CloudSat CWP and MODIS CWP.These results strongly suggest that it is necessary to consider particles with diameters greater than 50 tm in CloudSat LWC retrievals. Cloud microphysical property retrievals from the active microwave instrument on a satellite require the cloud droplet size distribution obtained from aircraft observations as a priori data in the iteration procedure.The cloud lognormal size distributions derived from 12 flights over Beijing,China,in 2008-09 were characterized to evaluate and improve regional CloudSat cloud water content retrievals.We present the distribution parameters of stratiform cloud droplet (diameter <500 tm and <1500 μm) and discuss the effect of large particles on distribution parameter fitting.Based on three retrieval schemes with different lognormal size distribution parameters,the vertical distribution of cloud liquid and ice water content were derived and then compared with the aircraft observations.The results showed that the liquid water content (LWC) retrievals from large particle size distributions were more consistent with the vertical distribution of cloud water content profiles derived from in situ data on 25 September 2006.We then applied two schemes with different a priori data derived from flight data to CloudSat overpasses in northern China during April-October in 2008 and 2009.The CloudSat cloud water path (CWP) retrievals were compared with Moderate Resolution Imaging Spectroradiometer (MODIS) liquid water path (LWP) data.The results indicated that considering a priori data including large particle size information can significantly improve the consistency between the CloudSat CWP and MODIS CWP.These results strongly suggest that it is necessary to consider particles with diameters greater than 50 tm in CloudSat LWC retrievals.
出处 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2014年第4期926-937,共12页 大气科学进展(英文版)
基金 supported by China public science and technology research funds projects of meteorology (Grant No. GYHY201406015) the Chinese Academy of Sciences (Grant No. XDA05040000) the National High-Tech R&D Program of China (Grant No. SQ2010AA1221583001) National Science Foundation program (Grant Nos. 41375024, 40775002, 41175020, and 41375008) the basic research program (Grant No. 2010CB950802) the NASA CloudSat project for making CloudSat data available to the scientific community
关键词 CLOUDSAT liquid water content a priori data aircraft observations CloudSat liquid water content a priori data aircraft observations
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