Multiple years of ARM lidar data indicate that current satellite-based lidar instruments underestimate the global mean direct radiative effect of aerosols by up to 54%.
Aerosols, small particles in the atmosphere, can affect the Earth’s energy balance directly by scattering and absorbing sunlight or indirectly by serving as nuclei on which cloud particles form. Estimates of the direct radiative effects of aerosol are needed both to understand the Earth’s energy balance and to evaluate the simulation of aerosols and their effects in Earth system models. Recent studies have used a spaceborne lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) to provide an estimate of the global mean aerosol direct radiative effect. While CALIPSO provides global coverage, its sensitivity may not be high enough to detect all radiatively important aerosol. In the current study, scientists use very sensitive high-resolution ground-based lidars operated by the Atmospheric Radiation Measurement (ARM) Facility to examine how much aerosol is not detected by the spaceborne lidar instrument.
Comparisons between observations from CALIPSO and multiple years of ARM’s ground-based Raman lidars show that CALIPSO does not detect all radiatively significant aerosol, i.e., aerosol that directly modifies the Earth’s radiation budget. The study estimates that using CALIPSO observations results in an underestimate of the magnitude of the global mean aerosol direct radiative effect (DRE) by up to 54%. The scientists use the ARM Raman lidar data sets along with NASA Langley airborne high spectral resolution lidar data to determine the detection sensitivity required for a spaceborne lidar to accurately resolve the aerosol DRE.
CALIPSO provides vertically resolved aerosol properties over all surface types during both day and night and can more accurately separate cloud from aerosol in the same profile than passive satellite sensors. Recognizing these advantages, recent studies have used CALIPSO to provide new all-sky estimates of the global top of atmosphere shortwave aerosol direct radiative effects. Notably, the clear-sky ocean aerosol direct radiative effect from these CALIPSO-based estimates are significantly smaller in magnitude than the passive sensor-based ones. Validating CALIPSO relative to advanced ground-based or airborne lidars that directly measure the extinction profile allows for the separation of CALIPSO errors due to assumed lidar ratios (the ratio of extinction to backscatter) and those errors from undetected aerosol.
This study first examines biases in the new version 4 of the CALIPSO data following the methodology of a previous study. It then assesses how well the biases found over the two ARM sites (Darwin, Australia and Oklahoma) can characterize the biases present in the global CALIPSO data set. The ARM Raman lidar data along with data from the airborne NASA Langley high-spectral resolution lidar (HSRL) are used to compute the detection sensitivity required for a lidar to fully resolve radiatively significant aerosol. The study also discusses how future space-based lidars might improve knowledge of aerosol radiative effects.
Contacts (BER PM)
ARM Program Manager
ASR Program Manager
NASA Langley Research Center
This research was supported by the NASA Aerosol-Clouds-Ecosystem (ACE) mission study program. Q. Fu was supported by the Office of Science (BER) U.S. Department of Energy grant DE-SC0010557 and NASA grant NNX16AO95G. The Raman lidar RL-FEX is available as an evaluation VAP from the ARM data archive (www.archive.arm.gov). The combined Raman and HSRL CHARMS data set is available as a PI product from the ARM data archive. The CALIPSO data sets were obtained from the NASA Langley Research Center Atmospheric Science Data Center. The NASA Langley HSRL data sets can be obtained from science.larc.nasa.gov/hsrl/.
Thorsen, T. J., R. A. Ferrare, C. A. Hostetler, M. A. Vaughan, and Q. Fu. “The impact of lidar detection sensitivity on assessing aerosol direct radiative effects,” Geophys. Res. Lett., 44:9059-9067, (2017). doi: 10.1002/2017GL074521.
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