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Qiang Fu

Publications and source records attributed to Qiang Fu.

13 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Improved Convective Ice Microphysics Parameterization in the NCAR CAM Model

Partitioning deep convective cloud condensates into components that sediment and detrain, known to be a challenge for global climate models, is important for cloud vertical distribution and anvil cloud formation. In this study, we address this issue by improving the convective microphysics scheme in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 (CAM5.3). The improvements include: (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four-class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. Results from the default and modified CAM5.3 models were evaluated against observations from the U.S. Department of Energy Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field campaign. The default model overestimates ice amount, which is largely attributed to the underestimation of convective ice particle sedimentation. By considering cloud ice sedimentation and rimed ice particles and applying a new convective snow terminal velocity parameterization, the vertical distribution of ice amount is much improved in the midtroposphere and upper troposphere when compared to observations. The vertical distribution of ice condensate also agrees well with observational best estimates upon considering snow detrainment. Comparison with observed convective updrafts reveals that current bulk model fails to reproduce the observed updraft magnitude and occurrence frequency, suggesting spectral distributions be required to simulate the subgrid updraft heterogeneity.

terminal velocity↗
NASA NTRS2017

The Impact of Lidar Detection Sensitivity on Assessing Aerosol Direct Radiative Effects

Spaceborne lidar observations have great potential to provide accurate global estimates of the aerosol direct radiative effect (DRE) in both clear and cloudy conditions. However, comparisons between observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) and multiple years of Atmospheric Radiation Measurement (ARM) program’s ground-based Raman lidars (RL) show that CALIPSO does not detect all radiatively significant aerosol, i.e. aerosol that directly modifies the Earth’s radiation budget. We estimated that using CALIPSO observations results in an underestimate of the magnitude of the global mean aerosol DRE by up to 54%. The ARM RL datasets along with NASA Langley airborne high spectral resolution lidar (HSRL) data from multiple field campaigns are used to compute the detection sensitivity required to accurately resolve the aerosol DRE. This shows that a lidar with a backscatter coefficient detection sensitivity of about 1−2x10(exp -4)km(exp -1)sr(exp -1) at 532nm would resolve all the aerosol needed to derive the DRE to within 1%.

Tyler J. Thorsen↗