A document by Isabel L. McCoy. Click on the document to view its contents.

Aerosol increases over the 20th century delayed the rate at which Earth warmed as a result of increases in greenhouse gases (GHGs). Aggressive aerosol mitigation policies arrested aerosol radiative forcing from ~1980 to ~2010. Recent evidence supports decreases in forcing magnitude since then. Using the approximate partial radiative perturbation (APRP) method, future shortwave aerosol effective radiative forcing changes are isolated from other shortwave changes in an 18-member ensemble of ScenarioMIP projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). APRP-derived near-term (2020-2050) aerosol forcing trends are correlated with published model emulation values but are 30-50% weaker. Differences are likely explained by location shifts of aerosol-impacting emissions and their resultant influences on susceptible clouds. Despite weaker changes, implementation of aggressive aerosol cleanup policies will have a major impact on global warming rates over 2020-2050. APRP-derived aerosol radiative forcings are used together with a forcing and impulse response model to estimate global temperature trends. Strong mitigation of GHGs, as in SSP1-2.6, likely prevents warming exceeding 2C since preindustrial but the strong aerosol cleanup in this scenario increases the probability of exceeding 2C by 2050 from near zero without aerosol changes to 6% with cleanup. When the same aerosol forcing is applied to a more likely GHG forcing scenario (i.e., SSP2-4.5), aggressive aerosol cleanup more than doubles the probability of reaching 2C by 2050 from 30% to 80%. It is thus critical to quantify and simulate the impacts of changes in aerosol radiative forcing over the next few decades.

Controls on pristine aerosol over the Southern Ocean (SO) are critical for constraining the strength of global aerosol indirect forcing. Observations of summertime SO clouds and aerosols in synoptically varied conditions during the 2018 SOCRATES aircraft campaign reveal novel mechanisms influencing pristine aerosol-cloud interactions. The SO free troposphere (3-6 km) is characterized by widespread, frequent new particle formation events contributing to much larger concentrations (≥ 1000 mg-1) of condensation nuclei (diameters > 0.01 μm) than in typical sub-tropical regions. Synoptic-scale uplift in warm conveyor belts and sub-polar vortices lifts marine biogenic sulfur-containing gases to free-tropospheric environments favorable for generating Aitken-mode aerosol particles (0.01-0.1 μm). Free-tropospheric Aitken particles subside into the boundary layer, where they grow in size to dominate the sulfur-based cloud condensation nuclei (CCN) driving SO cloud droplet number concentrations (Nd ~ 60-100 cm-3). Evidence is presented for a hypothesized Aitken-buffering mechanism which maintains persistently high summertime SO Nd against precipitation removal through CCN replenishment from activation and growth of boundary layer Aitken particles. Nudged hindcasts from the Community Atmosphere Model (CAM6) are found to underpredict Aitken and accumulation mode aerosols and Nd, impacting summertime cloud brightness and aerosol-cloud interactions and indicating incomplete representations of aerosol mechanisms associated with ocean biology.

Marine boundary layer clouds tend to organize into closed or open mesoscale cellular convection (MCC). Here, two-dimensional wavelet analysis is applied for the first time to passive microwave retrievals of cloud water path (CWP), water vapor path (WVP), and rain rate from AMSR-E in 2008 over the Northeast and Southeast Pacific, and the Southeast Atlantic subtropical stratocumulus to cumulus transition regions. The (co-)variability between CWP, WVP, and rain rate in 160x160 km2 analysis boxes is partitioned between four mesoscale wavelength octaves (20, 40, 80, and 160 km). The cell scale is identified as the wavelength of the peak CWP variance. Together with a machine-learning classification of cell type, this allows the statistical characteristics of open and closed MCC of various scales, and its relation to WVP, rain rate and potential environmental controlling factors to be analyzed across a very large set of cases. The results show that the cell wavelength is most commonly 40-80 km. Cell-scale CWP perturbations are good predictors of the WVP and rain rate perturbations. A universal cubic dependence of rain rate on CWP is found in closed and open cells of all scales. This suggests that aerosol control on precipitation susceptibility is not as important for open cell formation as are processes that cause increases in cloud water. For cells larger than 20 km, there is no obvious dependence of cell scale on the environmental controlling factors tested, suggesting that the cell scale may depend more on its historical evolution than the current environmental conditions.

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 six-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 was 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.