This study uses cloud and radiative properties collected from in situ and remote sensing instruments during two coordinated campaigns over the Southern Ocean between Tasmania and Antarctica in January–February 2018 to evaluate the simulations of clouds and precipitation in nudged‐meteorology simulations with the CAM6 and AM4 global climate models sampled at the times and locations of the observations. Fifteen SOCRATES research flights sampled cloud water content, cloud droplet number concentration, and particle size distributions in mixed‐phase boundary layer clouds at temperatures down to −25°C. The 6‐week CAPRICORN2 research cruise encountered all cloud regimes across the region. Data from vertically pointing 94 GHz radars deployed was compared with radar simulator output from both models. Satellite data were compared with simulated top‐of‐atmosphere (TOA) radiative fluxes. Both models simulate observed cloud properties fairly well within the variability of observations. Cloud base and top in both models are generally biased low. CAM6 overestimates cloud occurrence and optical thickness while cloud droplet number concentrations are biased low, leading to excessive TOA reflected shortwave radiation. In general, low clouds in CAM6 precipitate at the same frequency but are more homogeneous compared to observations. Deep clouds are better simulated but produce snow too frequently. AM4 underestimates cloud occurrence but overestimates cloud optical thickness even more than CAM6, causing excessive outgoing longwave radiation fluxes but comparable reflected shortwave radiation. AM4 cloud droplet number concentrations match observations better than CAM6. Precipitating low and deep clouds in AM4 have too little snow. Further investigation of these microphysical biases is needed for both models.
Abstract. There has been a growing concern that most climate models predict precipitation that is too frequent, likely due to lack of reliable subgrid variabilityand vertical variations in microphysical processes in low-level warm clouds.In this study, the warm-cloud physics parameterizations in the singe-columnconfigurations of NCAR Community Atmospheric Model version 6 and 5 (SCAM6and SCAM5, respectively) are evaluated using ground-based and airborneobservations from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the EasternNorth Atlantic (ACE-ENA) field campaign near the Azores islands during2017–2018. The 8-month single-column model (SCM) simulations show that both SCAM6 and SCAM5 cangenerally reproduce marine boundary layer cloud structure, majormacrophysical properties, and their transition. The improvement in warm-cloud properties from the Community Atmospheric Model 5 and 6 (CAM5 to CAM6) physics can be found through comparison with the observations. Meanwhile, both physical schemes underestimate cloud liquidwater content, cloud droplet size, and rain liquid water content butoverestimate surface rainfall. Modeled cloud condensation nuclei (CCN)concentrations are comparable with aircraft-observed ones in the summer but areoverestimated by a factor of 2 in winter, largely due to the biases in thelong-range transport of anthropogenic aerosols like sulfate. We also testthe newly recalibrated autoconversion and accretion parameterizations thataccount for vertical variations in droplet size. Compared to theobservations, more significant improvement is found in SCAM5 than in SCAM6.This result is likely explained by the introduction of subgrid variationsin cloud properties in CAM6 cloud microphysics, which further suppresses thescheme's sensitivity to individual warm-rain microphysical parameters. Thepredicted cloud susceptibilities to CCN perturbations in CAM6 are within areasonable range, indicating significant progress since CAM5 which produces anaerosol indirect effect that is too strong. The present study emphasizes theimportance of understanding biases in cloud physics parameterizations bycombining SCM with in situ observations.
more » « less- Award ID(s):
- 2031751
- NSF-PAR ID:
- 10475407
- Publisher / Repository:
- EGU
- Date Published:
- Journal Name:
- Atmospheric Chemistry and Physics
- Volume:
- 23
- Issue:
- 15
- ISSN:
- 1680-7324
- Page Range / eLocation ID:
- 8591 to 8605
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract A framework is introduced to investigate the indirect effect of aerosol loading on tropical deep convection using three-dimensional limited-domain idealized cloud-system-resolving model simulations coupled with large-scale dynamics over fixed sea surface temperature. The large-scale circulation is parameterized using the spectral weak temperature gradient (WTG) approximation that utilizes the dominant balance between adiabatic cooling and diabatic heating in the tropics. The aerosol loading effect is examined by varying the number of cloud condensation nuclei (CCN) available to form cloud droplets in the two-moment bulk microphysics scheme over a wide range of environments from 30 to 5000 cm−3. The radiative heating is held at a constant prescribed rate in order to isolate the microphysical effects. Analyses are performed over the period after equilibrium is achieved between convection and the large-scale environment. Mean precipitation is found to decrease modestly and monotonically when the aerosol number concentration increases as convection gets weaker, despite the increase in cloud liquid water in the warm-rain region and ice crystals aloft. This reduction is traced down to the reduction in surface enthalpy fluxes as an energy source to the atmospheric column induced by the coupling of the large-scale motion, though the gross moist stability remains constant. Increasing CCN concentration leads to 1) a cooler free troposphere because of a reduction in the diabatic heating and 2) a warmer boundary layer because of suppressed evaporative cooling. This dipole temperature structure is associated with anomalously descending large-scale vertical motion above the boundary layer and ascending motion at lower levels. Sensitivity tests suggest that changes in convection and mean precipitation are unlikely to be caused by the impact of aerosols on cloud droplets and microphysical properties but rather by accounting for the feedback from convective adjustment with the large-scale dynamics. Furthermore, a simple scaling argument is derived based on the vertically integrated moist static energy budget, which enables estimation of changes in precipitation given known changes in surfaces enthalpy fluxes and the constant gross moist stability. The impact on cloud hydrometeors and microphysical properties is also examined, and it is consistent with the macrophysical picture.
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/acp-23-8591-2023
