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Direct aerosol forcing and uncertainty. Estimates of aerosol forcing can be made using models or, increasingly, directly from observations. CALIPSO two-wavelength and depolarization profiles provide vertically resolved information on aerosol distribution, extinction coefficient, hydration state, and discrimination of large and small particles. CALIPSO also offers an improved cloud-masking capability. These observations will allow improved assessments of the representation of aerosol distribution and properties in models. Use of CALIPSO observations, alone and together with other A-train observations, will allow improved observational assessments of aerosol direct forcing as well as improvements in model-based assessments.

Indirect aerosol forcing and uncertainty. Changes in aerosol can potentially affect cloud reflectance and lifetime, but there are many uncertainties in how effective these mechanisms are in the real world. Regional assessments based on global datasets are needed. CALIPSO profiles will provide information on the vertical location of aerosols and whether or not they are in contact with, and therefore able to influence, clouds. CALIPSO also offers improved cloud masking of aerosol data, providing an opportunity to assess possible aerosol biases introducing uncertainties in current assessments of aerosol indirect effects.

Surface and atmospheric fluxes. The components of the atmospheric energy balance (in particular, SW and LW radiative fluxes) provide powerful constraints with which to test the performance of global climate models. Current global datasets of surface and atmospheric radiative fluxes contain significant uncertainties, largely due to the effects of clouds on radiation and in particular to effects of cloud multilayering. CALIPSO and Cloudsat will provide comprehensive observations of cloud height, thickness and layering. Coincident cloud observations from CALIPSO, CloudSat, and MODIS together with measurements of TOA fluxes from CERES provide an opportunity to create a greatly improved dataset of surface and atmospheric radiative fluxes, particularly in the polar regions.

Cloud-climate feedbacks. The fundamental problem in modeling cloud-radiation feedbacks involves the prediction of cloud properties based on atmospheric state and then using these properties to compute radiative fluxes. Testing these modeled processes requires nearly simultaneous observations of clouds, radiation, and atmospheric state. Cloud profiles from CALIPSO and CloudSat, cloud properties from MODIS/Aqua, radiative fluxes from CERES/Aqua, and measurements of atmospheric state from AIRS and AMSR (Aqua) provide the most complete closure of the cloud-radiation-atmospheric state feedback loop in the foreseeable future.


The following table lists the measurements needed to address the CALIPSO science objectives and indicates a number of the synergies available from combining CALIPSO observations with the additional measurements available from the other instruments of the constellation.

Science Objective Measurement CALIPSO Constellation
Direct aerosol forcing Aerosol vertical distribution and extinction profiles CALIOP  
Aerosol optical depth CALIOP Aqua-MODIS, PARASOL
Aerosol type information CALIOP Aqua-MODIS, PARASOL
Aerosol absorption   Aura-OMI
Broadband radiances   Aqua-CERES
Indirect aerosol forcing Aerosol and cloud vertical distributions CALIOP  
Cloud reflectance and droplet size   Aqua-MODIS
Broadband radiances   Aqua-CERES
Longwave surface and atmospheric fluxes Cloud height and thickness, multilayering CALIOP (thin cloud) CloudSat-CPR (thick cloud)
Cloud ice/water phase CALIOP (profiles) PARASOL, Aqua-MODIS (cloud-top only)
Cirrus emissivity and particle size CALIOP + IIR + WFC Aqua-MODIS, AIRS
Other cloud properties   CloudSat, PARASOL, Aqua-MODIS, AIRS, AMSR/E
Broadband radiances   Aqua-CERES
Cloud radiative feedbacks All elements of longwave surface and atmospheric fluxes plus: Cloud optical depth CALIOP Aqua-MODIS, PARASOL

Last Updated: November 28, 2017
Curator: Charles R. Trepte
NASA Official: Charles R. Trepte

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