Kuan Man Xu (PI)
NASA Langley Research Center
k.m.xu@larc.nasa.gov

Cloud Object Analysis and Modeling of Cloud Aerosols Interactions and Cloud Feedbacks with the Combined CERES and CALIPSO Data

An integrated approach to modeling and observational analysis is required to reduce the large uncertainties in current estimates of aerosol forcings and cloud feedbacks in the climate system. The proposed investigation is an extension of an integrated cloud-object approach that combines observational analysis and modeling of various types of cloud objects using the Clouds and the Earth’s Radiant Energy System (CERES) data, whereas cloud objects are defined as contiguous regions of the Earth with a single dominant cloud-system type. Two new cloud-object types, thin cirrus cloud and polar cloud types, will be analyzed under this investigation by taking advantage of the vertical layering information from the CALIPSO satellite and the high spatial and temporal sampling of the polar regions by the polar-orbiting satellites. The cloud-object approach can reduce the cloud/aerosol variabilities by grouping data from the same cloud-system type and similar aerosol environment. It can also reduce the sampling noise by combining data from a wide range of geographic regions. This means that cloud feedbacks and aerosol indirect forcings can be more accurately determined, compared to those determined by using the conventional monthly-mean gridded data. The newly available CALIPSO measurements will be integrated into the Aqua/CERES cloud object analysis to address the following questions:   (1) How well can our current understanding of cloud feedbacks associated tropical anvil clouds and polar clouds be improved by incorporating vertically-resolved cloud information from CALIPSO?  (2) How are polar clouds affected by aerosol indirect forcings and how well can the effects be quantified?  The Aqua/CERES data provide a horizontal (x-y) view of the cloud system while the CALIPSO data give a vertical slice (y-z) view along the mostly north/south satellite ground track. The identified cloud objects are matched with instantaneous atmospheric state data from the GMAO GEOS 5. These two new cloud object types will be further categorized according to aerosol types and cloud/aerosol overlapping information, etc. Two cloud-object categories, each with a hundred to a thousand cloud objects, are quantitatively compared (using the bootstrap method) in order to provide a more accurate estimate of the aerosol indirect forcing and cloud feedback.  In addition to the cloud object data analysis, we propose to improve modeling capability in a cloud-resolving model (CRM) that includes the coupling of a chemical reaction and aerosol microphysics module with a newly developed two-moment cloud microphysics scheme and an improved treatment of the radiative properties of different ice crystal habits and the feedbacks of aerosol to radiation. The improved CRM will be extensively validated against large ensembles of observed cloud objects. Sensitivity tests will then be performed to address important issues related to aerosol indirect effects. Extensive analyses will be performed to develop new parameterizations for cloud-aerosol interaction mechanisms for use in climate models.  CALIPSO will provide new observations of critical importance to modeling efforts. The CALIPSO lidar is able to observe aerosol and cloud in the same atmospheric column and will greatly aid investigations of aerosol-cloud interactions. CALIPSO will also observe aerosol in the polar regions, where passive observations are extremely limited due to lighting conditions, the high albedo of snow and ice, and the low thermal infrared contrast of cloud and snow/ice temperature. The two CALIPSO wavelengths provide unambiguous discrimination of cloud from small particle (< 1 m) aerosols including anthropogenic, industrial and biomass burning aerosols, allowing improved aerosol retrievals in cloudy environments and assessments of cloud biases in existing aerosol datasets. CALIPSO polarization also provides a vertically resolved discrimination of cloud ice/water phase, which will be important in the development and classification of cloud object types in the polar regions. Part of this effort will involve extensive analysis to generate cloud/aerosol statistics from the high-resolution CALIPSO data which are useful in testing and improving model performance.

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