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We study the sensitivity of South Asian Summer Monsoon (SASM) precipitation to Southern Hemisphere (SH) subtropical Absorbed Solar Radiation (ASR) changes using Community Earth System Model 2 simulations. Reducing positive ASR biases over the SH subtropics impacts SASM, and is sensitive to the ocean basin where changes are imposed. Radiation changes over the SH subtropical Indian Ocean (IO) shifts rainfall over the equatorial IO northward causing 1–2 mm/day drying south of equator, changes over the SH subtropical Pacific increases precipitation over northern continental regions by 1–2 mm/day, and changes over the SH subtropical Atlantic have little effect on SASM precipitation. Radiation changes over the subtropical Pacific impacts the SASM through zonal circulation changes, while changes over the IO modify meridional circulation to bring about changes in precipitation over northern IO. Our findings suggest that reducing SH subtropical radiation biases in climate models may also reduce SASM precipitation biases. Plain Language Summary: Precipitation from South Asian Summer Monsoon (SASM) is of high significance to the livelihoods of over a billion people. As the global climate continues to evolve, it is essential to have a clear understanding of the possible future changes to the SASM. However, current state‐of‐the‐art climate models have difficulties in simulating climatological mean SASM precipitations. Here we study sensitivity of SASM precipitation to subtropical southern ocean radiation as one of the possible causes of SASM precipitation bias. Our experiments indicate that SASM precipitation is sensitive to southern hemisphere (SH) subtropical radiation changes particularly to those in subtropical Pacific. These findings imply that improving SH subtropical radiation biases might improve SASM precipitation simulations in climate models. Key Points: We test if biases in southern hemisphere shortwave radiation contributes to biases in South Asian summer monsoon precipitation in the CESM2Reducing incoming shortwave radiation in the subtropical southern hemisphere reduces dry biases over continental South AsiaThis effect is mostly due to forcing in the South Pacific, with less impact from the Atlantic or Indian Ocean [ABSTRACT FROM AUTHOR]

This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1 ∘ horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of changes in 10-year mean zonal averages include the following: up to 0.5 K of warming in the lower troposphere and cooling in the tropical and subtropical upper troposphere, 1 %–10 % decreases in relative humidity throughout the troposphere, and 10 %–20 % decreases in cloud fraction in the upper troposphere and decreases exceeding 20 % in the subtropical lower troposphere. In terms of the 10-year mean geographical distribution, systematic decreases of 20 %–50 % are seen in total cloud cover and cloud radiative effects in the subtropics. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; to regain optimal climate fidelity in the absence of those truncation errors, the model would require retuning. A coarse-grained attribution of the time step sensitivities is carried out by shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection, and stratiform cloud macrophysics and microphysics parameterizations but rather by the step sizes used outside those subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM significantly affects the subtropical marine stratocumulus decks, while deep convection has significant impacts on trade cumulus. The step size of the cloud macrophysics and microphysics subcycle itself appears to have a primary impact on cloud fraction in the upper troposphere and also in the midlatitude near-surface layers. Impacts of step sizes used by the dynamical core and the radiation parameterization appear to be relatively small. These results provide useful clues for future studies aiming at understanding and addressing the root causes of sensitivities to time step sizes and process coupling frequencies in EAM. While this study focuses on EAMv1 and the conclusions are likely model-specific, the presented experimentation strategy has general value for weather and climate model development, as the methodology can help researchers identify and understand sources of time integration error in sophisticated multi-component models. [ABSTRACT FROM AUTHOR]

This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1-degree horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of such changes include warming in the lower troposphere, cooling in the tropical and subtropical upper troposphere, as well as decreases of relative humidity throughout the troposphere accompanied by cloud fraction decreases. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; the model would require retuning to regain optimal climate fidelity in the absence of those truncation errors. A coarse-grained attribution of the time step sensitivities is carried out by separately shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the counter-intuitive finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection and stratiform cloud macro- and microphysics parameterizations but by the step sizes used outside the subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM has a substantial impact on the marine stratocumulus decks while the deep convection parameterization has a significant impact on trade cumulus. The step size of the cloud macro- and microphysics subcycles appears to have a primary impact on cloud fraction at most latitudes in the upper troposphere as well as in the mid-latitude near-surface layers. Impacts of step sizes used by the dynamical core and radiation appear to be relatively small. These results provide useful clues to help better understand the root causes of time step sensitivities in EAM. The experimentation strategy used here can also provide a pathway for other models to identify and reduce time integration errors. [ABSTRACT FROM AUTHOR]

An earlier study evaluating dust life cycle in the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1) has revealed that the simulated global mean dust lifetime is substantially shorter when higher vertical resolution is used, primarily due to significant strengthening of dust dry removal in source regions. This paper demonstrates that the sequential splitting of aerosol emissions, dry removal, and turbulent mixing in the model's time integration loop, especially the calculation of dry removal after surface emissions and before turbulent mixing, is the primary reason for the vertical resolution sensitivity reported in that earlier study. Based on this reasoning, we propose a revised numerical process coupling scheme that requires the least amount of code changes, in which the surface emissions are applied before turbulent mixing instead of before dry removal. The revised scheme allows newly emitted particles to be transported aloft by turbulence before being removed from the atmosphere, and hence better resembles the dust life cycle in the real world. Sensitivity experiments show that the revised process coupling substantially weakens dry removal and strengthens vertical mixing in dust source regions. It also strengthens the large-scale transport from source to non-source regions, strengthens dry removal outside the source regions, and strengthens wet removal and activation globally. In transient simulations of the years 2000–2009 conducted using 1 ∘ horizontal grid spacing, 72 vertical layers, and unchanged tuning parameters of emission strength, the revised process coupling leads to a 40 % increase in the global total dust burden and an increase of dust lifetime from 1.8 to 2.5 d in terms of 10-year averages. Weakened dry removal and increased mixing ratios are also seen for other aerosol species that have substantial surface emissions, although the changes in mixing ratio are considerably smaller for the submicron species than for dust and sea salt. Numerical experiments confirm that the revised coupling scheme significantly reduces the strong and non-physical sensitivities of model results to vertical resolution in the original EAMv1. This provides a motivation for adopting the revised scheme in EAM as well as for further improvements on the simple revision presented in this paper. [ABSTRACT FROM AUTHOR]

Bjerknes compensation (BJC) refers to the anticorrelation observed between atmospheric and oceanic heat transport (AHT/OHT) variability, particularly on decadal to longer time scales that may be important to the predictability of the climate system. This study investigates the spread in BJC across fully coupled simulations of phase 6 of the Coupled Model Intercomparison Project (CMIP6) and critical processes (particularly related to sea ice and clouds) that may contribute to that spread. BJC on decadal to longer time scales is confirmed across all the simulations evaluated, and it is strongest in the Northern Hemisphere (NH) between 60° and 70°N. At these latitudes, BJC appears to be primarily driven by the exchange of turbulent fluxes (sensible and latent) in the Greenland, Iceland, and Barents Seas. Metrics to break down how sea ice and clouds uniquely modify the radiative balance of the polar atmosphere during anomalous OHT events are presented. These metrics quantify the impacts of sea ice and clouds on surface and top of atmosphere (latent, sensible, longwave, and shortwave radiative) energy fluxes. Cloud responses tend to counter the clear sky impacts over the Marginal Ice Zone (MIZ). It is further shown that the degree of BJC present in a simulation at high latitudes is heavily influenced by the sensitivity of the sea ice to OHT, which is most influential over the MIZ. These results are qualitatively robust across models and explain the intermodel spread in NH BJC in the preindustrial control experiment. [ABSTRACT FROM AUTHOR]

Since the winter of 2013-2014, California has experienced its most severe drought in recorded history, causing statewide water stress, severe economic loss and an extraordinary increase in wildfires. Identifying the effects of global warming on regional water cycle extremes, such as the ongoing drought in California, remains a challenge. Here we analyse large-ensemble and multi-model simulations that project the future of water cycle extremes in California as well as to understand those associations that pertain to changing climate oscillations under global warming. Both intense drought and excessive flooding are projected to increase by at least 50% towards the end of the twenty-first century; this projected increase in water cycle extremes is associated with a strengthened relation to El Niño and the Southern Oscillation (ENSO)-in particular, extreme El Niño and La Niña events that modulate California's climate not only through its warm and cold phases but also its precursor patterns. [ABSTRACT FROM AUTHOR]

Numerical weather, climate, or Earth system models involve the coupling of components. At a broad level, these components can be classified as the resolved fluid dynamics, unresolved fluid dynamical aspects (i.e., those represented by physical parameterizations such as subgrid-scale mixing), and nonfluid dynamical aspects such as radiation and microphysical processes. Typically, each component is developed, at least initially, independently. Once development is mature, the components are coupled to deliver a model of the required complexity. The implementation of the coupling can have a significant impact on the model. As the error associated with each component decreases, the errors introduced by the coupling will eventually dominate. Hence, any improvement in one of the components is unlikely to improve the performance of the overall system. The challenges associated with combining the components to create a coherent model are here termed physics–dynamics coupling. The issue goes beyond the coupling between the parameterizations and the resolved fluid dynamics. This paper highlights recent progress and some of the current challenges. It focuses on three objectives: to illustrate the phenomenology of the coupling problem with references to examples in the literature, to show how the problem can be analyzed, and to create awareness of the issue across the disciplines and specializations. The topics addressed are different ways of advancing full models in time, approaches to understanding the role of the coupling and evaluation of approaches, coupling ocean and atmosphere models, thermodynamic compatibility between model components, and emerging issues such as those that arise as model resolutions increase and/or models use variable resolutions. [ABSTRACT FROM AUTHOR]

A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN), either through geoengineering or other increased sources of Arctic aerosols. An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Albedo increases are stronger for pure liquid clouds than mixed-phase clouds. Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus, the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation owing to precipitation changes are small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering is unlikely to be effective as the sole means of altering the global radiation budget but could have substantial local radiative effects. [ABSTRACT FROM AUTHOR]

It has been proposed that increasing greenhouse gas (GHG) driven climate tipping point risks may prompt consideration of solar radiation modification (SRM) climate intervention to reduce those risks. Here, we study marine cloud brightening (MCB) SRM interventions in three subtropical oceanic regions using Community Earth System Model 2 experiments. We assess the MCB impact on tipping element‐related metrics to estimate the extent to which such interventions might reduce tipping element risks. Both the pattern and magnitude of the MCB cooling depend strongly on location of the MCB intervention. We find the MCB cooling effect reduces most tipping element impacts; though differences in MCB versus GHG climate response patterns mean MCB is an imperfect remedy. However, MCB applied in certain regions may exacerbate certain GHG tipping element impacts. Thus, it is crucial to carefully consider the pattern of MCB interventions and their teleconnected responses to avoid unintended climate effects. Plain Language Summary: Marine cloud brightening (MCB) is a proposal to spray sea salt particles into clouds over oceans to increase the reflection of sunlight by the clouds, thus cooling the surface. If greenhouse gas warming continues, technologies like MCB might be considered to avoid climate change impacts such as climate system tipping points. Here, we use state‐of‐the‐art climate model experiments to analyze the MCB impact on elements of the climate system that may have tipping points. In this model, MCB reduces risks for most tipping elements considered here, such as by reducing coral reef heat stress and increasing Atlantic overturning circulation. However, the impact of MCB depends on where it is applied and in some cases adds to GHG impacts, meaning the location of MCB deployments must be carefully considered to avoid unintended regional climate effects. Key Points: The magnitude and pattern of marine cloud brightening (MCB) climate impacts depend strongly on the location of the interventionWe find MCB impacts that have qualitative similarities to prior work, but there are discrepancies that suggest key inter‐model uncertaintiesMCB simulations generally show reduced tipping element risk overall, but certain MCB patterns may exacerbate some tipping element changes [ABSTRACT FROM AUTHOR]

Discretized numerical models of the atmosphere are usually intended to faithfully represent an underlying set of continuous equations, but this necessary condition is violated sometimes by subtle pathologies that have crept into the discretized equations. Such pathologies can introduce undesirable artifacts, such as sawtooth noise, into the model solutions. The presence of these pathologies can be detected by numerical convergence testing. This study employs convergence testing to verify the discretization of the Cloud Layers Unified By Binormals (CLUBB) model of clouds and turbulence. That convergence testing identifies two aspects of CLUBB's equation set that contribute to undesirable noise in the solutions. First, numerical limiters (i.e., clipping) used by CLUBB introduce discontinuities or slope discontinuities in model fields. Second, nonlinear artificial diffusion employed for improving numerical stability can introduce unintended small‐scale features into the solution of the model equations. Smoothing the limiters and using linear artificial diffusion reduces the noise and restores the expected first‐order convergence in CLUBB's solutions. These model reformulations enhance our confidence in the trustworthiness of solutions from CLUBB by eliminating the unphysical oscillations in high‐resolution simulations. The improvements in the results at coarser, near‐operational grid spacing and timestep are also seen in cumulus cloud and dry turbulence tests. In addition, convergence testing is proven to be a valuable tool for detecting pathologies, including unintended discontinuities and grid dependence, in the model equation set. Plain Language Summary: In order to detect pathologies in a numerical model of the atmosphere, a diagnostic test is used here that has been widely adopted in the applied mathematics community. The diagnostic test, if set up properly, proves to be effective at detecting the pathologies caused by issues associated with numerical discretization. Both the method of testing and the particular pathologies detected are expected to be relevant to other atmospheric models. Key Points: Numerical limiters and nonlinear artificial diffusion can inject unintended small‐scale features into the solution of the model equationsImproved treatment of limiters and artificial diffusion can reduce noise and improve the quality of solutions and numerical convergenceConvergence testing is a valuable tool for detecting noise in the model solution, as well as unintended discontinuities and grid dependence [ABSTRACT FROM AUTHOR]

The present study examines the characteristics of the Madden–Julian Oscillation (MJO) events represented in the Energy Exascale Earth System Model version 1 (E3SMv1), DOE's new Earth system model. The coupled E3SMv1 realistically simulates the eastward propagation of precipitation and moist static energy (MSE) anomalies associated with the MJO. As in observations, horizontal moisture advection and longwave radiative feedback are found to be the dominant processes in E3SMv1 that lead to the eastward movement and maintenance of the MJO MSE anomalies, respectively. Modulation of the diurnal cycle of precipitation in the Maritime Continent region by the MJO is also well represented in the model despite systematic biases in the magnitude and phase of the precipitation diurnal cycle. On the MJO impact over the midlatitude, E3SMv1 reasonably captures the pattern of the MJO teleconnections across the North Pacific and North America, with improvement in the performance in a high‐resolution version, despite the magnitude being a bit weaker than the observed. Regarding the interannual variability of the MJO, the El Niño‐Southern Oscillation (ENSO) modulation of the zonal extent of MJO's eastward propagation, as well as associated changes in the mean state moisture gradient in the tropical west Pacific, are well reproduced in the model. However, MJO in E3SMv1 exhibits no sensitivity to the Quasi‐Biennial Oscillation (QBO), with the MJO propagation characteristics being almost identical between easterly QBO and westerly QBO years. Processes that have been suggested as critical to MJO simulation are also examined by utilizing recently developed process‐oriented diagnostics. Plain Language Summary: The United States Department of Energy developed a new computer model that simulates Earth's climate systems, called Energy Exascale Earth System Model version 1 (E3SMv1). This study examines how well the model reproduces the characteristics of the Madden–Julian Oscillation (MJO), a tropical climate phenomenon that impacts weather and climate around the globe. We find that the strength and eastward movement of the MJO is realistically represented in the model. Variability of water vapor and radiation are the dominant processes for the MJO simulation, which agree well with the real‐world observations. Despite some unrealistic features, E3SMv1 successfully simulates the impact of the MJO on tropical precipitation at shorter than daily time scale and on large‐scale atmospheric circulation in the midlatitude. The model also exhibits realistic year‐to‐year changes in east‐west expansion of the MJO by the El Niño‐Southern Oscillation, while no noticeable changes can be detected when stratospheric wind reverses its direction over the equator in every 1 or 2 years. Key Points: Energy Exascale Earth System Model version 1 (E3SMv1) simulates Madden‐Julian Oscillation (MJOs) that exhibit realistic eastward propagation over the Indo‐Pacific warm poolModeled processes of the MJO, revealed through column‐integrated moist static energy anomalies, match well with those in observationsDespite the decent MJO simulation fidelity, the observed MJO–Quasi‐Biennial Oscillation coupling is not simulated in E3SMv1 [ABSTRACT FROM AUTHOR]

An advanced aerosol treatment, with a focus on semivolatile nitrate formation, is introduced into the Community Atmosphere Model version 5 with interactive chemistry (CAM5‐chem) by coupling the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) with the 7‐mode Modal Aerosol Module (MAM7). An important feature of MOSAIC is dynamic partitioning of all condensable gases to the different fine and coarse mode aerosols, as governed by mode‐resolved thermodynamics and heterogeneous chemical reactions. Applied in the free‐running mode from 1995 to 2005 with prescribed historical climatological conditions, the model simulates global distributions of sulfate, nitrate, and ammonium in good agreement with observations and previous studies. Inclusion of nitrate resulted in ∼10% higher global average accumulation mode number concentrations, indicating enhanced growth of Aitken mode aerosols from nitrate formation. While the simulated accumulation mode nitrate burdens are high over the anthropogenic source regions, the sea‐salt and dust modes respectively constitute about 74% and 17% of the annual global average nitrate burden. Regional clear‐sky shortwave radiative cooling of up to −5 W m−2 due to nitrate is seen, with a much smaller global average cooling of −0.05 W m−2. Significant enhancements in regional cloud condensation nuclei (at 0.1% supersaturation) and cloud droplet number concentrations are also attributed to nitrate, causing an additional global average shortwave cooling of −0.8 W m−2. Taking into consideration of changes in both longwave and shortwave radiation under all‐sky conditions, the net change in the top of the atmosphere radiative fluxes induced by including nitrate aerosol is −0.7 W m−2. Plain Language Summary: Atmospheric aerosols and aerosol‐cloud interactions continue to be a major source of uncertainty in global climate models that are used to assess the impacts of anthropogenic emissions on climate change. A notable fraction of aerosols is composed of ammonium nitrate, which forms in the atmosphere when ammonia combines with nitric acid produced from oxidation of nitrogen oxides. Both precursor gases are emitted in large amounts from anthropogenic activities as well as natural sources. However, a faithful numerical representation of nitrate aerosol in global models has been difficult owing to the semivolatile nature of ammonium nitrate. In this work, we introduce and evaluate an advanced and computationally efficient aerosol chemistry module in a state‐of‐the‐science global climate model to properly simulate the dynamics of nitrate aerosol formation and its interactions with the naturally occurring sea‐salt and dust aerosols. Inclusion of nitrate results in about 10% higher global average number concentrations of aerosols in the size range that efficiently interacts with solar radiation and acts as seeds upon which cloud droplets can form. Consequently, nitrate accounts for an additional radiative cooling, largely due to the changes in cloud formation. Key Points: A modal version of the advanced aerosol chemistry module MOSAIC is developed and introduced in a climate model to simulate nitrate aerosolMOSAIC provides an accurate and efficient treatment for dynamically partitioning semivolatile gases over to entire aerosol size distributionThe modeled global distribution of nitrate is in good agreement with observations and its impact on the radiative effects is quantified [ABSTRACT FROM AUTHOR]

Secondary organic aerosols (SOA) are large contributors to fine particle mass loading and number concentration and interact with clouds and radiation. Several processes affect the formation, chemical transformation, and removal of SOA in the atmosphere. For computational efficiency, global models use simplified SOA treatments, which often do not capture the dynamics of SOA formation. Here we test more complex SOA treatments within the global Energy Exascale Earth System Model (E3SM) to investigate how simulated SOA spatial distributions respond to some of the important but uncertain processes affecting SOA formation, removal, and lifetime. We evaluate model predictions with a suite of surface, aircraft, and satellite observations that span the globe and the full troposphere. Simulations indicate that both a strong production (achieved here by multigenerational aging of SOA precursors that includes moderate functionalization) and a strong sink of SOA (especially in the middle upper troposphere, achieved here by adding particle‐phase photolysis) are needed to reproduce the vertical distribution of organic aerosol (OA) measured during several aircraft field campaigns; without this sink, the simulated middle upper tropospheric OA is too large. Our results show that variations in SOA chemistry formulations change SOA wet removal lifetime by a factor of 3 due to changes in horizontal and vertical distributions of SOA. In all the SOA chemistry formulations tested here, an efficient chemical sink, that is, particle‐phase photolysis, was needed to reproduce the aircraft measurements of OA at high altitudes. Globally, SOA removal rates by photolysis are equal to the wet removal sink, and photolysis decreases SOA lifetimes from 10 to ~3 days. A recent review of multiple field studies found no increase in net OA formation over and downwind biomass burning regions, so we also tested an alternative, empirical SOA treatment that increases primary organic aerosol (POA) emissions near source region and converts POA to SOA with an aging time scale of 1 day. Although this empirical treatment performs surprisingly well in simulating OA loadings near the surface, it overestimates OA loadings in the middle and upper troposphere compared to aircraft measurements, likely due to strong convective transport to high altitudes where wet removal is weak. The default improved model formulation (multigenerational aging with moderate fragmentation and photolysis) performs much better than the empirical treatment in these regions. Differences in SOA treatments greatly affect the SOA direct radiative effect, which ranges from −0.65 (moderate fragmentation and photolysis) to −2 W m−2 (moderate fragmentation without photolysis). Notably, most SOA formulations predict similar global indirect forcing of SOA calculated as the difference in cloud forcing between present‐day and preindustrial simulations. Plain language Summary: Secondary organic aerosols (SOA) are formed in the atmosphere by oxidation of organic gases emitted from natural biogenic, anthropogenic, and biomass burning sources. In many regions of the atmosphere, SOA greatly contributes to fine particle mass loadings and number concentrations and affects clouds and radiation. Integrating insights from global atmospheric modeling and measurements, we show that strong chemical production achieved here by multigenerational chemistry including moderate fragmentation of SOA precursors and strong chemical sinks represented by particle‐phase photolysis are needed to explain the aircraft‐observed vertical profiles of SOA over multiple regions including North America, equatorial oceans, and the Southern Ocean. Photolysis reduces simulated global SOA lifetimes from 10 to 3 days. Within the same model physics and cloud treatments, we show that changes in SOA chemistry formulations change SOA wet removal lifetimes by a factor of 3. Simulations show that SOA exerts a strong direct radiative forcing in the present day ranging from −0.65 to −2 W m−2. Future measurements and modeling are needed to better constrain the photolytic and heterogeneous chemical removal of SOA at high‐altitude atmospheric conditions. Key Points: Gas‐phase multi‐generational aging of SOA precursors is a strong sourceLoss processes such as gas‐phase fragmentation pathways for SOA products need to be included for a more realistic model representation of OABoth strong sources and sinks are needed to explain global SOA distributions [ABSTRACT FROM AUTHOR]

Convergence testing is a common practice in the development of dynamical cores of atmospheric models but is not as often exercised for the parameterization of subgrid physics. An earlier study revealed that the stratiform cloud parameterizations in several predecessors of the Energy Exascale Earth System Model (E3SM) showed strong time step sensitivity and slower‐than‐expected convergence when the model's time step was systematically refined. In this work, a simplified atmosphere model is configured that consists of the spectral‐element dynamical core of the E3SM atmosphere model coupled with a large‐scale condensation parameterization based on commonly used assumptions. This simplified model also resembles E3SM and its predecessors in the numerical implementation of process coupling and shows poor time step convergence in short ensemble tests. We present a formal error analysis to reveal the expected time step convergence rate and the conditions for obtaining such convergence. Numerical experiments are conducted to investigate the root causes of convergence problems. We show that revisions in the process coupling and closure assumption help to improve convergence in short simulations using the simplified model; the same revisions applied to a full atmosphere model lead to significant changes in the simulated long‐term climate. This work demonstrates that causes of convergence issues in atmospheric simulations can be understood by combining analyses from physical and mathematical perspectives. Addressing convergence issues can help to obtain a discrete model that is more consistent with the intended representation of the physical phenomena. Plain Language Summary: Computer codes that simulate the time evolution of a physical system produce errors in the results due to the finite step sizes used to advance the calculations in time. These errors are expected to decrease as the time steps are shortened, at a rate determined by the characteristics of the equations and numerical methods. An earlier study revealed that the error reduction in several predecessors of the Energy Exascale Earth System Model (E3SM) was at a rate slower than expected. This study creates a simplified configuration of those models and investigates the causes of the unexpected behavior. We show that slow error reduction can be understood and improved by combining analyses from physical and mathematical perspectives. The required code modifications can lead to significant changes in the simulated long‐term behavior of a full‐fledged climate model. Furthermore, ensuring a proper rate of error reduction can help to obtain a computer code that is more consistent with the intended representation of the corresponding physical system. Key Points: Poor numerical convergence is seen in a simplified model that resembles design features of a full‐fledged climate modelRevisions in process coupling and closure assumption help improve convergence and avoid nonphysical behaviorThese revisions also affect long‐term climate in the corresponding full model [ABSTRACT FROM AUTHOR]

The sea ice-albedo feedback (SIAF) is the product of the ice sensitivity (IS), that is, how much the surface albedo in sea ice regions changes as the planet warms, and the radiative sensitivity (RS), that is, how much the top-of-atmosphere radiation changes as the surface albedo changes. We demonstrate that the RS calculated from radiative kernels in climate models is reproduced from calculations using the "approximate partial radiative perturbation" method that uses the climatological radiative fluxes at the top of the atmosphere and the assumption that the atmosphere is isotropic to shortwave radiation. This method facilitates the comparison of RS from satellite-based estimates of climatological radiative fluxes with RS estimates across a full suite of coupled climate models and, thus, allows model evaluation of a quantity important in characterizing the climate impact of sea ice concentration changes. The satellite-based RS is within the model range of RS that differs by a factor of 2 across climate models in both the Arctic and Southern Ocean. Observed trends in Arctic sea ice are used to estimate IS, which, in conjunction with the satellite-based RS, yields an SIAF of 0.16 ± 0.04 W m−2 K−1. This Arctic SIAF estimate suggests a modest amplification of future global surface temperature change by approximately 14% relative to a climate system with no SIAF. We calculate the global albedo feedback in climate models using model-specific RS and IS and find a model mean feedback parameter of 0.37 W m−2 K−1, which is 40% larger than the IPCC AR5 estimate based on using RS calculated from radiative kernel calculations in a single climate model. [ABSTRACT FROM AUTHOR]

We conduct sensitivity experiments using a general circulation model that has an explicit water source tagging capability forced by prescribed composites of pre-industrial sea-ice concentrations (SICs) and corresponding sea surface temperatures (SSTs) to understand the impact of sea-ice anomalies on regional evaporation, moisture transport and source–receptor relationships for Antarctic precipitation in the absence of anthropogenic forcing. Surface sensible heat fluxes, evaporation and column-integrated water vapor are larger over Southern Ocean (SO) areas with lower SICs. Changes in Antarctic precipitation and its source attribution with SICs have a strong spatial variability. Among the tagged source regions, the Southern Ocean (south of 50 ∘ S) contributes the most (40 %) to the Antarctic total precipitation, followed by more northerly ocean basins, most notably the South Pacific Ocean (27%), southern Indian Ocean (16 %) and South Atlantic Ocean (11 %). Comparing two experiments prescribed with high and low pre-industrial SICs, respectively, the annual mean Antarctic precipitation is about 150 Gt yr -1 (or 6 %) more in the lower SIC case than in the higher SIC case. This difference is larger than the model-simulated interannual variability in Antarctic precipitation (99 Gt yr -1). The contrast in contribution from the Southern Ocean, 102 Gt yr -1 , is even more significant compared to the interannual variability of 35 Gt yr -1 in Antarctic precipitation that originates from the Southern Ocean. The horizontal transport pathways from individual vapor source regions to Antarctica are largely determined by large-scale atmospheric circulation patterns. Vapor from lower-latitude source regions takes elevated pathways to Antarctica. In contrast, vapor from the Southern Ocean moves southward within the lower troposphere to the Antarctic continent along moist isentropes that are largely shaped by local ambient conditions and coastal topography. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies associated with natural variability on Antarctic precipitation. Our analyses of the seasonal contrast in changes of basin-scale evaporation, moisture flux and precipitation suggest that the impact of SIC anomalies on regional Antarctic precipitation depends on dynamic changes that arise from SIC–SST perturbations along with internal variability. The latter appears to have a more significant effect on the moisture transport in austral winter than in summer. [ABSTRACT FROM AUTHOR]

The quasi‐biennial oscillation (QBO) of the zonal mean wind is a prominent feature of the tropical lower stratosphere and has been shown to influence stratospheric and tropospheric variability. Although observed for many decades, the QBO is difficult to be accurately captured in Earth system models. The newly developed U.S. Department of Energy Energy Exascale Earth System Model, Version 1 (E3SMv1) is capable of resolving stratospheric dynamics as it has a top at 0.1 hPa and 72 levels. The tropical oscillation of the zonal mean zonal wind in the default version of the model is too fast and too strong compared to the observed QBO. Here we evaluate the current simulation of the QBO and present simulations with modified convective gravity wave parameterization parameters that make the oscillation more realistic, especially in terms of the period. Although improvements in the QBO are obtained through modifications to the parameterized gravity waves, we find that the forcing of the QBO from Kelvin and mixed‐Rossby gravity waves is small due to weak sources in the troposphere. The changes to the parameterized convective gravity waves (and QBO) are primarily limited to the tropical stratosphere. Small changes to mean wind and temperature are also found in Northern Hemisphere winter in the uppermost troposphere between 10°N and 60°N. Modifications to parameterized convectively generated gravity waves result in changes in interannual variability, primarily in the Southern Hemisphere, and modest changes in sea level pressure variability over the Pacific are also noted. Key Points: Simulation of the QBO was improved in E3SMv1 by changing parameterized convectively generated gravity wavesKelvin and mixed‐Rossby gravity wave forcing of the QBO remains weak due to weak sources in the troposphereChanges in the QBO result in modest changes in surface variability [ABSTRACT FROM AUTHOR]

Climate simulations with more accurate process-level representation at finer resolutions (<100 km) are a pressing need in order to provide more detailed actionable information to policy makers regarding extreme events in a changing climate. Computational limitation is a major obstacle for building and running high-resolution (HR, here 0.25 ∘ average grid spacing at the Equator) models (HRMs). A more affordable path to HRMs is to use a global regionally refined model (RRM), which only simulates a portion of the globe at HR while the remaining is at low resolution (LR, 1 ∘). In this study, we compare the Energy Exascale Earth System Model (E3SM) atmosphere model version 1 (EAMv1) RRM with the HR mesh over the contiguous United States (CONUS) to its corresponding globally uniform LR and HR configurations as well as to observations and reanalysis data. The RRM has a significantly reduced computational cost (roughly proportional to the HR mesh size) relative to the globally uniform HRM. Over the CONUS, we evaluate the simulation of important dynamical and physical quantities as well as various precipitation measures. Differences between the RRM and HRM over the HR region are predominantly small, demonstrating that the RRM reproduces the precipitation metrics of the HRM over the CONUS. Further analysis based on RRM simulations with the LR vs. HR model parameters reveals that RRM performance is greatly influenced by the different parameter choices used in the LR and HR EAMv1. This is a result of the poor scale-aware behavior of physical parameterizations, especially for variables influencing sub-grid-scale physical processes. RRMs can serve as a useful framework to test physics schemes across a range of scales, leading to improved consistency in future E3SM versions. Applying nudging-to-observations techniques within the RRM framework also demonstrates significant advantages over a free-running configuration for use as a test bed and as such represents an efficient and more robust physics test bed capability. Our results provide additional confirmatory evidence that the RRM is an efficient and effective test bed for HRM development. [ABSTRACT FROM AUTHOR]