We examine tropical rainfall from Geophysical Fluid Dynamics Laboratory’s Atmosphere Model version 4 (GFDL AM4) at three horizontal resolutions of 100 km, 50 km, and 25 km. The model produces more intense rainfall at finer resolutions, but a large discrepancy still exists between the simulated and the observed frequency distribution. We use a theoretical precipitation scaling diagnostic to examine the frequency distribution of the simulated rainfall. The scaling accurately produces the frequency distribution at moderate-to-high intensity (≥10 mm day-1). Intense tropical rainfall at finer resolutions is produced primarily from the increased contribution of resolved precipitation and enhanced updrafts. The model becomes more sensitive to the grid-scale updrafts than local thermodynamics at high rain rates as the contribution from the resolved precipitation increases. On the contrary, the observed tropical precipitation extremes do not show a strong sensitivity to the grid-scale updrafts.

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We investigate the dependence of radiative feedback on the pattern of sea-surface temperature (SST) change in fourteen Atmospheric General Circulation Models (AGCMs) forced with observed variations in SST and sea-ice over the historical record from 1871 to near-present. We find that over 1871-1980, the Earth warmed with feedbacks largely consistent and strongly correlated with long-term climate sensitivity feedbacks (diagnosed from corresponding atmosphere-ocean GCM abrupt-4xCO2 simulations). Post 1980 however, the Earth warmed with unusual trends in tropical Pacific SSTs (enhanced warming in the west, cooling in the east) that drove climate feedback to be uncorrelated with – and indicating much lower climate sensitivity than – that expected for long-term CO2 increase. We show that these conclusions are not strongly dependent on the AMIP II SST dataset used to force the AGCMs, though the magnitude of feedback post 1980 is generally smaller in eight AGCMs forced with alternative HadISST1 SST boundary conditions. We quantify a ‘pattern effect’ (defined as the difference between historical and long-term CO2 feedback) equal to 0.44 ± 0.47 [5-95%] W m-2 K-1 for the time-period 1871-2010, which increases by 0.05 ± 0.04 W m-2 K-1 if calculated over 1871-2014. Assessed changes in the Earth’s historical energy budget are in agreement with the AGCM feedback estimates. Furthermore satellite observations of changes in top-of-atmosphere radiative fluxes since 1985 suggest that the pattern effect was particularly strong over recent decades, though this may be waning post 2014 due to a warming of the eastern Pacific.

Climate models struggle to accurately represent the highly reflective boundary layer clouds overlying the remote and stormy Southern Ocean. We use in-situ aircraft observations from the Southern Ocean Clouds, Radiation and Aerosol Transport Experimental Study (SOCRATES) to evaluate Southern Ocean clouds in a cloud-resolving large-eddy simulation (LES) and two coarse resolution global atmospheric models, the CESM Community Atmosphere Model (CAM6) and the GFDL global atmosphere model (AM4), run in a nudged hindcast framework. We develop six case studies from SOCRATES data which span the range of observed cloud and boundary layer properties. For each case, the LES is run once forced purely using reanalysis data (‘ERA5-based’) and once strongly nudged to an aircraft profile (‘Obs-based’). The ERA5-based LES can be compared with the global models, which are also nudged to reanalysis data, and is better for simulating cumulus. The Obs-based LES closely matches an observed cloud profile and is useful for microphysical comparisons and sensitivity tests, and simulating multi-layer stratiform clouds. We use two-moment Morrison microphysics in the LES and find that it simulates too few frozen particles in clouds occurring within the Hallett-Mossop temperature range. We modify the Hallett-Mossop parameterization so that it activates within boundary layer clouds and we achieve better agreement between observed and simulated microphysics. The nudged GCMs achieve reasonable supercooled liquid water dominated clouds in most cases but struggle to represent multi-layer stratiform clouds and to maintain liquid water in cumulus clouds. CAM6 has low droplet concentrations in all cases and underestimates stratiform cloud-driven turbulence.

The effect of stratospheric ozone depletion is simulated in GFDL AM4 model with three ozone schemes: prescribing monthly zonal mean ozone concentration, full interactive stratospheric chemistry, and a simplified linear ozone chemistry scheme but with full dynamical interactions. While similar amounts of ozone loss are simulated by the three schemes, the two interactive ozone schemes produce significantly stronger stratospheric cooling than the prescribed one. We find that this temperature difference is driven by the dynamical responses to ozone depletion. In particular, the existence of ozone hole leads to strong ozone eddies that are in-phase with the temperature eddies. The coherence between ozone and temperature anomalies leads to a weaker radiative damping as ozone absorbs shortwave radiation that compensates for the longwave cooling. As a result, less wave dissipates at the lower stratosphere, leading to a weaker descending and dynamical heating over the polar lower stratosphere, and hence a stronger net cooling there. The covariance between ozone and temperature is largely suppressed when ozone is prescribed as monthly zonal mean time series, as is the reduction in the radiative damping following ozone depletion. With much lower computational cost, the simplified ozone scheme is capable of producing similar magnitude of ozone loss and the consequent dynamical responses to those simulated by the full chemistry.

Using nine chemistry-climate and eight associated no-chemistry models, we investigate the persistence and timing of cold episodes occurring in the Arctic and Antarctic stratosphere during the period 1980-2014. We find systematic differences in behavior between members of these model pairs. In a first group of chemistry models whose dynamical configurations mirror their no-chemistry counterparts, we find an increased persistence of such cold polar vortices, such that these cold episodes both start earlier and last longer, relative to the times of occurrence of the lowest temperatures. Also the date of occurrence of the lowest temperatures, both in the Arctic and the Antarctic, is delayed by 1-3 weeks in chemistry models, versus their no-chemistry counterparts. This behavior exacerbates a widespread problem occurring in most or all models, a delayed occurrence, in the median, of the most anomalously cold day during such cold winters. In a second group of model pairs there are differences beyond just ozone chemistry. In particular, here the chemistry models feature more levels in the stratosphere, a raised model top, and differences in non-orographic gravity wave drag versus their no-chemistry counterparts. Such additional dynamical differences can completely mask the above influence of ozone chemistry. The results point towards a need to retune chemistry-climate models versus their no-chemistry counterparts.

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.