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The COVID-19 pandemic caused significant economic disruption in 2020 and severely impacted air traffic. We use a state-of-the-art Earth system model and ensembles of tightly constrained simulations to evaluate the effect of the reductions in aviation traffic on contrail radiative forcing and climate in 2020. In the absence of any COVID-19-pandemic-caused reductions, the model simulates a contrail effective radiative forcing (ERF) of 62 ± 59 mW m−2 (2 standard deviations). The contrail ERF has complex spatial and seasonal patterns that combine the offsetting effect of shortwave (solar) cooling and longwave (infrared) heating from contrails and contrail cirrus. Cooling is larger in June–August due to the preponderance of aviation in the Northern Hemisphere, while warming occurs throughout the year. The spatial and seasonal forcing variations also map onto surface temperature variations. The net land surface temperature change due to contrails in a normal year is estimated at 0.13 ± 0.04 K (2 standard deviations), with some regions warming as much as 0.7 K. The effect of COVID-19 reductions in flight traffic decreased contrails. The unique timing of such reductions, which were maximum in Northern Hemisphere spring and summer when the largest contrail cooling occurs, means that cooling due to fewer contrails in boreal spring and fall was offset by warming due to fewer contrails in boreal summer to give no significant annual averaged ERF from contrail changes in 2020. Despite no net significant global ERF, because of the spatial and seasonal timing of contrail ERF, some land regions would have cooled slightly (minimum −0.2 K) but significantly from contrail changes in 2020. The implications for future climate impacts of contrails are discussed.

Abstract The Community Earth System Model version 2 (CESM2) simulates a high equilibrium climate sensitivity (ECS > 5°C) and a Last Glacial Maximum (LGM) that is substantially colder than proxy temperatures. In this study, we examine the role of cloud parameterizations in simulating the LGM cooling in CESM2. Through substituting different versions of cloud schemes in the atmosphere model, we attribute the excessive LGM cooling to the new CESM2 schemes of cloud microphysics and ice nucleation. Further exploration suggests that removing an inappropriate limiter on cloud ice number (NoNimax) and decreasing the time‐step size (substepping) in cloud microphysics largely eliminate the excessive LGM cooling. NoNimax produces a more physically consistent treatment of mixed‐phase clouds, which leads to an increase in cloud ice content and a weaker shortwave cloud feedback over mid‐to‐high latitudes and the Southern Hemisphere subtropics. Microphysical substepping further weakens the shortwave cloud feedback. Based on NoNimax and microphysical substepping, we have developed a paleoclimate‐calibrated CESM2 (PaleoCalibr), which simulates well the observed twentieth century warming and spatial characteristics of key cloud and climate variables. PaleoCalibr has a lower ECS (∼4°C) and a 20% weaker aerosol‐cloud interaction than CESM2. PaleoCalibr represents a physically more consistent treatment of cloud microphysics than CESM2 and is a valuable tool in climate change studies, especially when a large climate forcing is involved. Our study highlights the unique value of paleoclimate constraints in informing the cloud parameterizations and ultimately the future climate projection.

The radiative forcing from aerosols (particularly through their interaction with clouds) remains one of the most uncertain components of the human forcing of the climate. Observation-based studies have typically found a smaller aerosol effective radiative forcing than in model simulations and were given preferential weighting in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). With their own sources of uncertainty, it is not clear that observation-based estimates are more reliable. Understanding the source of the model and observational differences is thus vital to reduce uncertainty in the impact of aerosols on the climate. These reported discrepancies arise from the different methods of separating the components of aerosol forcing used in model and observational studies. Applying the observational decomposition to global climate model (GCM) output, the two different lines of evidence are surprisingly similar, with a much better agreement on the magnitude of aerosol impacts on cloud properties. Cloud adjustments remain a significant source of uncertainty, particularly for ice clouds. However, they are consistent with the uncertainty from observation-based methods, with the liquid water path adjustment usually enhancing the Twomey effect by less than 50 %. Depending on different sets of assumptions, this work suggests that model and observation-based estimates could be more equally weighted in future synthesis studies.

Abstract To explore the interactions among column processes in the Community Atmosphere Model (CAM), the single‐column version of CAM (SCAM) is integrated for 1000 days in radiative‐convective equilibrium (RCE) with tropical values of boundary conditions, spanning a parameter or configuration space of model physics versions (v5 vs. v6), vertical resolution (standard and 60 levels), sea surface temperature (SST), and some interpretation‐driven experiments. The simulated time‐mean climate is reasonable, near observations and RCE of a cyclic cloud‐resolving model. Updraft detrainment in the deep convection scheme produces distinctive grid‐scale structures in humidity and cloud, which also interact with radiative transfer processes. These grid artifacts average out in multi‐column RCE results reported elsewhere, illustrating the nuts‐and‐bolts interpretability that SCAM adds to the hierarchy of model configurations. Multi‐day oscillations of precipitation arise from descent of warm convection‐capping layers starting near the tropopause, eventually reset by a burst of convective deepening. Experiments reveal how these oscillations depend critically on an internal parameter that controls the number of neutral buoyancy levels allowed for determining cloud top and computing dilute convective available potential energy in the deep convection scheme, and merely modified a little by disabling cloud‐base radiation (heating of cloud base). This strong dependence of transient behavior in 1D on this parameter will be tested in the second part of this work, in which SCAM is coupled to a parameterized dynamics of two‐dimensional, linearized gravity wave, and in the 3D simulations in future study.

We present an analysis of version 5.1 of the Community Atmospheric Model (CAM5.1) at a high horizontal resolution. Intercomparison of this global model at approximately 0.25°, 1°, and 2° is presented for extreme daily precipitation as well as for a suite of seasonal mean fields. In general, extreme precipitation amounts are larger in high resolution than in lower-resolution configurations. In many but not all locations and/or seasons, extreme daily precipitation rates in the high-resolution configuration are higher and more realistic. The high-resolution configuration produces tropical cyclones up to category 5 on the Saffir-Simpson scale and a comparison to observations reveals both realistic and unrealistic model behavior. In the absence of extensive model tuning at high resolution, simulation of many of the mean fields analyzed in this study is degraded compared to the tuned lower-resolution public released version of the model.

Extended, high-resolution (0.23° latitude × 0.31° longitude) simulations with Community Atmosphere Model versions 4 and 5 (CAM4 and CAM5) are examined and compared with results from climate simulations conducted at a more typical resolution of 0.9° latitude × 1.25° longitude. Overall, the simulated climate of the high-resolution experiments is not dramatically better than that of their low-resolution counterparts. Improvements appear primarily where topographic effects may be playing a role, including a substantially improved summertime Indian monsoon simulation in CAM4 at high resolution. Significant sensitivity to resolution is found in simulated precipitation over the southeast United States during winter. Some aspects of the simulated seasonal mean precipitation deteriorate notably at high resolution. Prominent among these is an exacerbated Pacific "double ITCZ"bias in both models. Nevertheless, while large-scale seasonal means are not dramatically better at high resolution, realistic tropical cyclone (TC) distributions are obtained. Some skill in reproducing interannual variability in TC statistics also appears. © 2014 American Meteorological Society.

General circulation models' (GCMs) estimates of the liquid water path adjustment to anthropogenic aerosol emissions differ in sign from other lines of evidence. This reduces confidence in estimates of the effective radiative forcing of the climate by aerosol–cloud interactions (ERFaci). The discrepancy is thought to stem in part from GCMs' inability to represent the turbulence–microphysics interactions in cloud-top entrainment, a mechanism that leads to a reduction in liquid water in response to an anthropogenic increase in aerosols. In the real atmosphere, enhanced cloud-top entrainment is thought to be the dominant adjustment mechanism for liquid water path, weakening the overall ERFaci. We show that the latest generation of GCMs includes models that produce a negative correlation between the present-day cloud droplet number and liquid water path, a key piece of observational evidence supporting liquid water path reduction by anthropogenic aerosols and one that earlier-generation GCMs could not reproduce. However, even in GCMs with this negative correlation, the increase in anthropogenic aerosols from preindustrial to present-day values still leads to an increase in the simulated liquid water path due to the parameterized precipitation suppression mechanism. This adds to the evidence that correlations in the present-day climate are not necessarily causal. We investigate sources of confounding to explain the noncausal correlation between liquid water path and droplet number. These results are a reminder that assessments of climate parameters based on multiple lines of evidence must carefully consider the complementary strengths of different lines when the lines disagree. [ABSTRACT FROM AUTHOR]

A single column model with parameterized large‐scale (LS) dynamics is used to better understand the response of steady‐state tropical precipitation to relative sea surface temperature under various representations of radiation, convection, and circulation. The large‐scale dynamics are parametrized via the weak temperature gradient (WTG), damped gravity wave (DGW), and spectral weak temperature gradient (Spectral WTG) method in NCAR's Single Column Atmosphere Model (SCAM6). Radiative cooling is either specified or interactive, and the convective parameterization is run using two different values of a parameter that controls the degree of convective inhibition. Results are interpreted in the context of the Global Atmospheric System Studies ‐Weak Temperature Gradient (GASS‐WTG) Intercomparison project. Using the same parameter settings and simulation configuration as in the GASS‐WTG Intercomparison project, SCAM6 under the WTG and DGW methods produces erratic results, suggestive of numerical instability. However, when key parameters are changed to weaken the large‐scale circulation's damping of tropospheric temperature variations, SCAM6 performs comparably to single column models in the GASS‐WTG Intercomparison project. The Spectral WTG method is less sensitive to changes in convection and radiation than are the other two methods, performing qualitatively similarly across all configurations considered. Under all three methods, circulation strength, represented in 1D by grid‐scale vertical velocity, is decreased when barriers to convection are reduced. This effect is most extreme under specified radiative cooling, and is shown to come from increased static stability in the column's reference radiative‐convective equilibrium profile. This argument can be extended to interactive radiation cases as well, though perhaps less conclusively. Plain Language Summary: Single column models, as the name suggests, only model the vertical dimension of the atmosphere. They are simpler than full‐scale 3D global circulation models, but nonetheless play an important role in model development and in better understanding physical phenomena. We use NCAR's Single Column Atmosphere Model (SCAM6) to better understand tropical rainfall. In a single column model, the atmospheric wind coming from other locations (the large‐scale circulation) must be either specified or approximated using a parameterization. We implement three different parameterizations of the large‐scale circulation into SCAM6 and assess how SCAM6 responds to various changes while using these parameterizations. The Global Atmospheric System Studies‐Weak Temperature Gradient (GASS‐WTG) Intercomparison project assessed the performance of various other single column models using two parameterizations of the large‐scale circulation. We fold SCAM6 into this Intercomparison, and we find that SCAM6 performs substantially differently to its peers under the settings used in the GASS‐WTG Intercomparison project, but more comparably to its peers when key circulation parameters are relaxed. Another notable finding is that, across all three parameterizations of large‐scale dynamics, circulation strength decreases when we reduce SCAM6's barrier to convection. Key Points: We use three different methods to parameterize the large‐scale (LS) dynamics in NCAR's single column atmospheric model (SCAM6)As in the Global Atmospheric System Studies Intercomparison, we test SCAM6's response to various boundary conditions and model parametersUnder all three methods, circulation strength is decreased when barriers to convection are reduced [ABSTRACT FROM AUTHOR]

Abstract The Community Earth System Model version 2 (CESM2) includes three main atmospheric configurations: the Community Atmosphere Model version 6 (CAM6) with simplified chemistry and a simplified organic aerosol (OA) scheme, CAM6 with comprehensive tropospheric and stratospheric chemistry representation (CAM6‐chem), and the Whole Atmosphere Community Climate Model version 6 (WACCM6). Both, CAM6‐chem and WACCM6 include a more comprehensive secondary organic aerosols (SOA) approach using the Volatility Basis Set (VBS) scheme and prognostic stratospheric aerosols. This paper describes the different OA schemes available in the different atmospheric configurations of CESM2 and discusses differences in aerosol burden and resulting climate forcings. Derived OA burden and trends differ due to differences in OA formation using the different approaches. Regional differences in Aerosol Optical Depth with larger values using the comprehensive approach occur over SOA source regions. Stronger increasing SOA trends between 1960 and 2015 in WACCM6 compared to CAM6 are due to increasing biogenic emissions aligned with increasing surface temperatures. Using the comprehensive SOA approach further leads to improved comparisons to aircraft observations and SOA formation of ≈143 Tg/yr. We further use WACCM6 to identify source contributions of OA from biogenic, fossil fuel, and biomass burning emissions, to quantify SOA amounts and trends from these sources. Increasing SOA trends between 1960 and 2015 are the result of increasing biogenic emissions aligned with increasing surface temperatures. Biogenic emissions are at least two thirds of the total SOA burden. In addition, SOA source contributions from fossil fuel emissions become more important, with largest values over Southeast Asia. The estimated total anthropogenic forcing of OA in WACCM6 for 1995–2010 conditions is −0.43 W/m2, mostly from the aerosol direct effect.

The Community Atmosphere Model version 6 (CAM6), released in 2018 as part of the Community Earth System Model version 2 (CESM2), is a major upgrade over the previous CAM5 that has been used in numerous global and regional climate studies. Since CESM2–CAM6 will participate in the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6) and is likely to be adopted in many future studies, its simulation fidelity needs to be thoroughly examined. Here we evaluate the performance of a developmental version of the Community Atmosphere Model with parameterizations that will be used in version 6 (CAM6α), with a default 1∘ horizontal resolution (0.9∘×1.25∘, CAM6α-1∘) and a high-resolution configuration (approximately 0.25∘, CAM6α-0.25∘), against various observational and reanalysis datasets of precipitation over Asia. CAM6α performance is compared with CAM5 at default 1∘ horizontal resolution (CAM5-1∘) and a high-resolution configuration at 0.25∘ (CAM5-0.25∘). With the prognostic treatment of precipitation processes and the new microphysics module, CAM6α is able to better simulate climatological mean and extreme precipitation over Asia, better capture the heaviest precipitation events, better reproduce the diurnal cycle of precipitation rates over most of Asia, and better simulate the probability density distributions of daily precipitation over Tibet, Korea, Japan and northern China. Higher horizontal resolution in CAM6α improves the simulation of mean and extreme precipitation over northern China, but the performance degrades over the Maritime Continent. Moisture budget diagnosis suggests that the physical processes leading to model improvement are different over different regions. Both upgraded physical parameterizations and higher horizontal resolution affect the simulated precipitation response to the internal variability of the climate system (e.g., Asian monsoon variability, El Niño–Southern Oscillation – ENSO, Pacific Decadal Oscillation – PDO), but the effects vary across different regions. For example, higher horizontal resolution degrades the model performance in simulating precipitation variability over southern China associated with the East Asian summer monsoon. In contrast, precipitation variability associated with ENSO improves with upgraded physical parameterizations and higher horizontal resolution. CAM6α-0.25∘ and CAM6α-1∘ show an opposite response to the PDO over southern China. Basically, the response to increases in horizontal resolution is dependent on the CAM version.

Abstract Rimed hydrometeors (graupel or hail) are added to a stratiform cloud scheme for global models and tested in a variety of configurations. Off‐line tests compare well to other cloud microphysics schemes with rimed ice used in mesoscale models. Tests in single column and climate mode show expected production of small amounts of rimed ice in the middle troposphere and at high latitudes. The overall climate impacts of rimed ice (hail or graupel) at 100‐km horizontal grid spacing are small. There are some changes to partitioning between cloud ice and snow that affect upper troposphere water budgets and clouds. High‐resolution simulations are conducted with a global but regionally refined grid at 14 km over the Contiguous United States. High‐resolution simulations show local production of graupel with realistic size and number concentrations. The maximum graupel frequency at high resolution is over Western U.S. mountain ranges. Differences in total precipitation with the addition of rimed ice in 8‐year simulations are statistically significant only for orographic precipitation over the Cascade and Rocky mountains, reducing model biases when rimed ice is included. Rimed ice slightly improves summer precipitation intensity relative to observations. Thus, while the global climate impact of rimed ice in stratiform clouds may be negligible, there are potentially important and systematic regional effects, particularly for orographic precipitation. Rimed ice in cumulus clouds is not yet treated but is an important next step.

Abstract The Single Column Atmosphere Model (SCAM) is a single column model version of the Community Atmosphere Model (CAM). Here we describe the functionality and features of SCAM6, available as part of CAM6 in the Community Earth System Model, version 2 (CESM2). SCAM6 features a wide selection of standard cases, as well as the ability to easily configure a case specified by the user based on a particular point in a CAM 3‐D simulation. This work illustrates how SCAM6 reproduces CAM6 results for physical parameterizations, mostly of moisture and clouds. We demonstrate how SCAM6 can be used for model development through different physics selections, as well as with parameter sweep experiments to highlight the sensitivity of cloud properties to the specification of the vapor deposition process in the cloud microphysics. Furthermore, we use SCAM6 to illustrate the sensitivity of CAM6 cloud radiative properties and precipitation to variable drop number (cloud microphysics properties). Finally, we illustrate how SCAM6 can be used to explore critical emergent processes such as cloud feedbacks and show that CAM6 cloud responses to surface warming in stratus and stratocumulus regimes are similar to those in CAM5. CAM6 has a larger response in the shallow cumulus regime than CAM5. CAM6 cloud feedbacks in the shallow cumulus regime are sensitive to turbulence parameters. SCAM6 is thus a valuable tool for model development, evaluation, and scientific analy sis and an important part of the model hierarchy in Community Earth System Model, version 2.

The impact of aerosols on cloud properties is one of the largest uncertainties in the anthropogenic radiative forcing of the climate. Significant progress has been made in constraining this forcing using observations, but uncertainty remains, particularly in the magnitude of cloud rapid adjustments to aerosol perturbations. Cloud liquid water path (LWP) is the leading control on liquid-cloud albedo, making it important to observationally constrain the aerosol impact on LWP. Previous modelling and observational studies have shown that multiple processes play a role in determining the LWP response to aerosol perturbations, but that the aerosol effect can be difficult to isolate. Following previous studies using mediating variables, this work investigates use of the relationship between cloud droplet number concentration (Nd) and LWP for constraining the role of aerosols. Using joint-probability histograms to account for the non-linear relationship, this work finds a relationship that is broadly consistent with previous studies. There is significant geographical variation in the relationship, partly due to role of meteorological factors (particularly relative humidity). The Nd–LWP relationship is negative in the majority of regions, suggesting that aerosol-induced LWP reductions could offset a significant fraction of the instantaneous radiative forcing from aerosol–cloud interactions (RFaci). However, variations in the Nd–LWP relationship in response to volcanic and shipping aerosol perturbations indicate that the Nd–LWP relationship overestimates the causal Nd impact on LWP due to the role of confounding factors. The weaker LWP reduction implied by these “natural experiments” means that this work provides an upper bound to the radiative forcing from aerosol-induced changes in the LWP.

Abstract 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 Clouds are critical for weather and climate prediction. The multiple scales of cloud processes make simulation difficult. Often models and measurements are used to develop empirical relationships for large‐scale models to be computationally efficient. Machine learning provides another potential tool to improve our empirical parameterizations of clouds. To explore these opportunities, we replace the warm rain formation process in a General Circulation Model (GCM) with a detailed treatment from a bin microphysical model that causes a 400% slowdown in the GCM. We analyze the changes in climate that result from the use of the bin microphysical calculation and find improvements in the rain onset and frequency of light rain compared to high resolution process models and observations. We also find a resulting change in the cloud feedback response of the model to warming, which will significantly impact the climate sensitivity. We then replace the bin microphysical model with several neural networks designed to emulate the autoconversion and accretion rates produced by the bin microphysical model. The neural networks are organized into two stages: the first stage identifies where tendencies will be nonzero (and the sign of the tendency), and the second stage predicts the magnitude of the autoconversion and accretion rates. We describe the risks of overfitting, extrapolation, and linearization by using perfect model experiments with and without the emulator. We can recover the solutions with the emulators in almost all respects, and get simulations that perform as the detailed model, but with the computational cost of the control simulation.

Non-technical summary We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements. Technical summary A synthesis is made of 10 topics within climate research, where there have been significant advances since January 2020. The insights are based on input from an international open call with broad disciplinary scope. Findings include: (1) the options to still keep global warming below 1.5 °C; (2) the impact of non-CO2 factors in global warming; (3) a new dimension of fire extremes forced by climate change; (4) the increasing pressure on interconnected climate tipping elements; (5) the dimensions of climate justice; (6) political challenges impeding the effectiveness of carbon pricing; (7) demand-side solutions as vehicles of climate mitigation; (8) the potentials and caveats of nature-based solutions; (9) how building resilience of marine ecosystems is possible; and (10) that the costs of climate change mitigation policies can be more than justified by the benefits to the health of humans and nature. Social media summary How do we limit global warming to 1.5 °C and why is it crucial? See highlights of latest climate science.