Search

Robust estimates of historical changes in aerosols are key for accurate constraints on climate sensitivity. Dry deposition is a primary sink of aerosols from the atmosphere. However, most global climate models do not accurately represent observed strong dependencies of dry deposition following turbulent transport on aerosol size. It is unclear whether there is a substantial impact of mischaracterized aerosol deposition velocities on historical aerosol changes. Here we describe improved mechanistic representation of aerosol dry deposition in the NASA Goddard Institute for Space Studies (GISS) global climate model, ModelE, and illustrate the impact on 1850–2000 changes in global aerosol burdens as well as aerosol direct and cloud albedo effects using a set of 1850 and 2000 time slice simulations. We employ two aerosol configurations of ModelE (a "bulk" mass‐based configuration and a configuration that more explicitly represents aerosol size distributions, internal mixing, and microphysics) to explore how model structural differences in aerosol representation alter the response to representation of dry deposition. Both configurations show larger historical increases in the global burdens of non‐dust aerosols with the new dry deposition scheme, by 11% in the simpler mass‐based configuration and 23% in the more complex microphysical configuration. Historical radiative forcing responses, which vary in magnitude from 5% to 12% as well as sign, depend on the aerosol configuration. Plain Language Summary: Numerical models representing the Earth system are important tools for understanding the drivers of climate change and variability. Particles (also known as aerosols) in the atmosphere can influence climate by scattering or absorbing solar radiation and influencing clouds. How the amount of particles in the atmosphere has changed since preindustrial times is very uncertain. Many processes impact particle spatial distributions and changes with time, as well as how particles influence climate. Sources and sinks of particles need to be represented well in order to have confidence in estimates of changes in particles. Here we more accurately simulate dry deposition, which is a sink of particles, in a numerical model that represents the Earth system, and examine impacts on changes in the amount of particles in the atmosphere from preindustrial times to present day and the particles' influence on climate. Key Points: ModelE now has process‐based representation of aerosol dry deposition, and captures strong observed dependencies on particle sizeIncreases from 1850 to 2000 in the global non‐dust aerosol annual burdens are 11%–23% larger with more mechanistic dry depositionHistorical radiative forcing responses (−12% to +6%) depend on aerosol representation (e.g., microphysics and mixing state) [ABSTRACT FROM AUTHOR]

Over the CMIP6 historical period (1850–2014), aerosols provided the largest negative forcing compared to all other climate forcings via their ability to absorb or scatter solar radiation and alter clouds. Aerosols played an important role in counterbalancing warming by greenhouse gases (GHGs). Here we study aerosol forcing trends in the CMIP6 simulations of the NASA Goddard Institute for Space Studies (GISS) ocean‐atmosphere ModelE version 2.1 (GISS‐E2.1‐G) using a fully coupled atmospheric composition configuration, including interactive gas‐phase chemistry, and either an aerosol microphysical (MATRIX) or a mass‐based aerosol (OMA) module. Simulations of the CMIP6 historical period are analyzed as well as four Shared Socioeconomic Pathway (SSP) future scenarios for 2015–2100: SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5. The main conclusion of this study is that aerosol forcing in the GISS model has reached its turning point, switching from globally increasing to a decreasing trend in the first decade of the 21st century. This result is robust, independent of which aerosol module or SSP scenario is used. Non‐linear aerosol‐cloud interactions dominate as a forcing agent over aerosol‐radiation interactions. Aerosols' ability to counterbalance GHG forcing on the global scale is today at a level comparable to that at the beginning of the last century. In the 1980s, the decade of largest global aerosol loads, aerosols balanced up to 80% of GHG forcing. As a consequence, global warming of the last decades, which is primarily driven by greenhouse gases, has been augmented by the effect of decreasing aerosol cooling in our model. By the end of this century, following the SSP scenarios, aerosols will only counterbalance 0%–20% of GHG forcing, depending on model and on scenario. Plain Language Summary: Climate change is the result of the aggregate effect of a number of individual forcing agents changing the radiative balance at the top of the atmosphere over time. As a result, if positive radiative forcings dominate over negative forcings, the Earth's surface warms. Over the historical period, since the pre‐industrial era, greenhouse gases (GHG) and aerosol have provided the largest positive and negative forcings, respectively. However, the relationship between GHG and aerosols have rapidly changed in the last decades, and future projections show much more dramatic dominance of GHG over aerosols. This study investigates the connection between emissions, atmospheric composition and climate forcing. We find that aerosols' ability to counterbalance GHG forcing reached its maximum effect in the 1980s, and that since the first decade of the 21st century, aerosol effects are globally on a decreasing trajectory. Reduced aerosol loads are important for health, but accelerate global warming, in the absence of concurrent GHG reductions. The results presented here are based upon the NASA GISS climate model, and the four future scenarios used. These scenarios are not intended as predictions, but represent a range of possible changes in atmospheric composition (including greenhouse gases) based on differing assumptions about future energy policies. Key Points: Aerosol forcing in the Goddard Institute for Space Studies model reached its turning point in the first decade of the 21st centuryNon‐linear aerosol‐cloud forcing dominates in magnitude over aerosol direct forcing and pinpoint the timing of the turning pointWithin the next 25 years, global aerosol forcing might balance only 0%–20% of greenhouse gas forcing, compared to 80% in 1980–1990 [ABSTRACT FROM AUTHOR]

The Earth's climate is rapidly changing. Over the past centuries, aerosols, via their ability to absorb or scatter solar radiation and alter clouds, played an important role in counterbalancing some of the greenhouse gas (GHG) caused global warming. The multicentury anthropogenic aerosol cooling effect prevented present‐day climate from reaching even higher surface air temperatures and subsequent more dramatic climate impacts. Trends in aerosol concentrations and optical depth show that in many polluted regions such as Europe and the United States, aerosol precursor emissions decreased back to levels of the 1950s. More recent polluting countries such as China may have reached a turning point in recent years as well, while India still follows an upward trend. Here we study aerosol trends in the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations of the GISS ModelE2.1 climate model using a fully coupled atmosphere composition configuration, including interactive gas‐phase chemistry and either an aerosol microphysical (MATRIX) or a mass‐based (One‐Moment Aerosol, OMA) aerosol module. Results show that whether global aerosol radiative forcing is already declining depends on the aerosol scheme used. Using the aerosol microphysical scheme, where the aerosol system reacts more strongly to the trend in sulfur dioxide (SO2) emissions, global peak direct aerosol forcing was reached in the 1980s, whereas the mass‐based scheme simulates peak direct aerosol forcing around 2010. Plain Language Summary: The National Aeronautics and Space Administration (NASA) Earth system model, GISS ModelE2.1, has released new interactive composition climate simulations from 1850 to 2014 into the Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima protocol archive. The GISS model includes two different schemes to simulate aerosols in the atmosphere, driven by natural and anthropogenic emissions. The two aerosol schemes differ by degree of complexity. One model better resolves aerosol microphysical processes, while the other model has more detailed chemistry regarding secondary organic aerosol formation. The models simulate different trends in aerosol radiative forcing. An evaluation with satellite data between 2001 and 2014 demonstrates that the model with more detailed aerosol microphysics has reached maximal aerosol direct forcing in the 1980s and is since on a decreasing global forcing trajectory. This has implications for using the trends over recent decades as predictive for greenhouse‐gas related changes in the future. Key Points: A discussion is presented of the AMIP aerosol simulations for the years 1850 to 2014 of the GISS ModelE2.1 for CMIP6, using two different aerosol schemesThe detailed treatment of aerosol microphysical processes greatly impacts aerosol forcing and forcing trendsOne model suggests that Earth has already exceeded the maximum negative forcing effects of anthropogenic aerosol in the 1980s [ABSTRACT FROM AUTHOR]

We used the EVAv6.0 system to estimate the present (2015) and future (2015–2050) global PM 2.5 and O 3 -related premature mortalities, using simulated surface concentrations from the GISS-E2.1-G Earth system model. The PM 2.5 -related global premature mortality is estimated to be 4.3 and 4.4 million by the non-linear and linear models, respectively. Ischemic heart diseases are found to be the leading cause of PM 2.5 -related premature deaths, contributing by 35% globally. Both long-term and short-term O 3 -related premature deaths are estimated to be around 1 million, globally. Overall, PM 2.5 and O 3 -related premature mortality leads to 5.3–5.4 million premature deaths, globally. The global burden of premature deaths is mainly driven by the Asian region, which in 2015 contributes by 75% of the total global premature deaths. An increase from 6.2% to 8% in the PM 2.5 relative risk as recommended by the WHO leads to an increase of PM 2.5 -related premature mortality by 28%, to 5.7 million. Finally, bias correcting the simulated PM 2.5 concentrations in 2015 leads to an increase of up to 73% in the global PM 2.5 -related premature mortality, leading to a total number of global premature deaths of up to 7.7 million, implying the necessity of bias correction to get more robust health burden estimates. PM 2.5 and O 3 -related premature mortality in 2050 decreases by up to 57% and 18%, respectively, due to emission reductions alone. However, the projected increase and aging of the population leads to increases of premature mortality by up to a factor of 2, showing that the population exposed to air pollution is more important than the level of air pollutants, highlighting that the population dynamics should be considered when setting up health assessment systems. • Present and future global PM 2.5 and O 3 -related premature mortality is estimated. • The present day global premature mortality is estimated to be 5.4 million. • Bias correction increases global PM 2.5 -related premature mortality to 7.7 million. • Emission reductions alone decreases premature mortality by up to 57% in 2050. • Aging population increases premature mortality by up to a factor of 2. [ABSTRACT FROM AUTHOR]

The authors simulate transient twentieth-century climate in the Goddard Institute for Space Studies (GISS) GCM, with aerosol and ozone chemistry fully coupled to one another and to climate including a full dynamic ocean. Aerosols include sulfate, black carbon (BC), organic carbon, nitrate, sea salt, and dust. Direct and BC-snow-albedo radiative effects are included. Model BC and sulfur trends agree fairly well with records from Greenland and European ice cores and with sulfur deposition in North America; however, the model underestimates the sulfur decline at the end of the century in Greenland. Global BC effects peak early in the century (1940s); afterward the BC effects decrease at high latitudes of the Northern Hemisphere but continue to increase at lower latitudes. The largest increase in aerosol optical depth occurs in the middle of the century (1940s--80s) when sulfate forcing peaks and causes global dimming. After this, aerosols decrease in eastern North America and northern Eurasia leading to regional positive forcing changes and brightening. These surface forcing changes have the correct trend but are too weak. Over the century, the net aerosol direct effect is −−0.41 W m−−2, the BC-albedo effect is −−0.02 W m−−2, and the net ozone forcing is ++0.24 W m−−2. The model polar stratospheric ozone depletion develops, beginning in the 1970s. Concurrently, the sea salt load and negative radiative flux increase over the oceans around Antarctica. Net warming over the century is modeled fairly well; however, the model fails to capture the dynamics of the observed midcentury cooling followed by the late century warming. Over the century, 20%% of Arctic warming and snow--ice cover loss is attributed to the BC-albedo effect. However, the decrease in this effect at the end of the century contributes to Arctic cooling. To test the climate responses to sulfate and BC pollution, two experiments were branched from 1970 that removed all pollution sulfate or BC. Averaged over 1970--2000, the respective radiative forcings relative to the full experiment were ++0.3 and −−0.3 W m−−2; the average surface air temperature changes were ++0.2°° and −−0.03°°C. The small impact of BC reduction on surface temperature resulted from reduced stability and loss of low-level clouds. [ABSTRACT FROM AUTHOR]

Analyzes the impact of background concentrations of ozone on regional scale photochemical modelling during a summer smog episode over Europe in July 1994. Definition of ozone categories; Percentage distribution of total ozone the smog episode; Determination of transport and chemical transformations of splitted ozone.

A meso-γ scale non-hydrostatic atmospheric model has been extended to determine gas-phase chemistry, transport, emission and deposition of chemical trace species. This coupled atmosphere-chemistry model calculates meteorological and chemical processes simultaneously. The model is nested into a coarser regional atmosphere-chemistry model which, in turn, is embedded in an even coarser framework. According to the evaluation case, the chain of mesoscale atmosphere-chemistry models is applied to the regions of Europe, Germany and Berlin-Brandenburg, respectively. The model performance is evaluated using time series of meteorological and chemical measurements and aircraft observations. The evaluation shows that the meteorological and chemical simulation reproduces reality excellent under urban conditions. But the amount of rural and upper level ozone is generally too low. [ABSTRACT FROM AUTHOR]

Volcanic super-eruptions have been theorized to cause severe global cooling, with the 74 kya Toba eruption purported to have driven humanity to near-extinction. However, this eruption left little physical evidence of its severity and models diverge greatly on the magnitude of post-eruption cooling. A key factor controlling the super-eruption climate response is the size of volcanic sulfate aerosol, a quantity that left no physical record and is poorly constrained by models. Here we show that this knowledge gap severely limits confidence in model-based estimates of super-volcanic cooling, and accounts for much of the disagreement among prior studies. By simulating super-eruptions over a range of aerosol sizes, we obtain global mean responses varying from extreme cooling all the way to the previously unexplored scenario of widespread warming. We also use an interactive aerosol model to evaluate the scaling between injected sulfur mass and aerosol size. Combining our model results with the available paleoclimate constraints applicable to large eruptions, we estimate that global volcanic cooling is unlikely to exceed 1.5°C no matter how massive the stratospheric injection. Super-eruptions, we conclude, may be incapable of altering global temperatures substantially more than the largest Common Era eruptions. This lack of exceptional cooling could explain why no single super-eruption event has resulted in firm evidence of widespread catastrophe for humans or ecosystems. Significance Statement: Whether volcanic super-eruptions pose a threat to humanity remains a subject of debate, with climate models disagreeing on the magnitude of global post-eruption cooling. We demonstrate that this disagreement primarily stems from a lack of constraint on the size of volcanic sulfate aerosol particles. By evaluating the range of aerosol size scenarios, we demonstrate that eruptions may be incapable of causing more than 1.5°C cooling no matter how much sulfur they inject into the stratosphere. This could explain why archaeological records provide no evidence of increased human mortality following the Toba super-eruption. Further, we raise the unexplored possibility that the largest super-eruptions could cause global-scale warming. [ABSTRACT FROM AUTHOR]

We report on a multiyear set of airborne field campaigns (2005–16) off the California coast to examine aerosols, clouds, and meteorology, and how lessons learned tie into the upcoming NASA Earth Venture Suborbital (EVS-3) campaign: Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE; 2019–23). The largest uncertainty in estimating global anthropogenic radiative forcing is associated with the interactions of aerosol particles with clouds, which stems from the variability of cloud systems and the multiple feedbacks that affect and hamper efforts to ascribe changes in cloud properties to aerosol perturbations. While past campaigns have been limited in flight hours and the ability to fly in and around clouds, efforts sponsored by the Office of Naval Research have resulted in 113 single aircraft flights (>500 flight hours) in a fixed region with warm marine boundary layer clouds. All flights used nearly the same payload of instruments on a Twin Otter to fly below, in, and above clouds, producing an unprecedented dataset. We provide here i) an overview of statistics of aerosol, cloud, and meteorological conditions encountered in those campaigns and ii) quantification of model-relevant metrics associated with aerosol–cloud interactions leveraging the high data volume and statistics. Based on lessons learned from those flights, we describe the pragmatic innovation in sampling strategy (dual-aircraft approach with combined in situ and remote sensing) that will be used in ACTIVATE to generate a dataset that can advance scientific understanding and improve physical parameterizations for Earth system and weather forecasting models, and for assessing next-generation remote sensing retrieval algorithms. [ABSTRACT FROM AUTHOR]

The gas-particle partitioning and chemical aging of semi-volatile organic aerosol are presented in a newly developed box model scheme, where its effect on the growth, composition, and mixing state of particles is examined. The volatility-basis set (VBS) framework is implemented into the aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves mass and number aerosol concentrations and in multiple mixing-state classes. The new scheme, MATRIX-VBS, has the potential to significantly advance the representation of organic aerosols in Earth system models by improving upon the conventional representation as non-volatile particulate organic matter, often also with an assumed fixed size distribution. We present results from idealized cases representing Beijing, Mexico City, a Finnish forest, and a southeastern US forest, and investigate the evolution of mass concentrations and volatility distributions for organic species across the gas and particle phases, as well as assessing their mixing state among aerosol populations. Emitted semi-volatile primary organic aerosols evaporate almost completely in the intermediatevolatility range, while they remain in the particle phase in the low-volatility range. Their volatility distribution at any point in time depends on the applied emission factors, oxidation by OH radicals, and temperature. We also compare against parallel simulations with the original scheme, which represented only the particulate and non-volatile component of the organic aerosol, examining how differently the condensedphase organic matter is distributed across the mixing states in the model. The results demonstrate the importance of representing organic aerosol as a semi-volatile aerosol, and explicitly calculating the partitioning of organic species between the gas and particulate phases. [ABSTRACT FROM AUTHOR]

We have implemented an existing aerosol microphysics scheme into a box model framework and extended it to represent gas-particle partitioning and chemical ageing of semi-volatile organic aerosols. We then applied this new research tool to investigate the effects of semi-volatile organic species on the growth, composition and mixing state of aerosol particles in case studies representing several different environments. The volatility-basis set (VBS) framework is implemented into the aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves mass and number aerosol concentrations and in multiple mixing-state classes. The new scheme, MATRIX-VBS, has the potential to significantly advance the representation of organic aerosols in Earth system models by improving upon the conventional representation as non-volatile particulate organic matter, often with also an assumed fixed size distribution. We present results from idealized cases representing Beijing, Mexico City, a Finnish and a Southeast U.S. forest, and investigate the evolution of mass concentrations and volatility distributions for organic species across the gas and particle phases, as well as assessing their mixing state among aerosol populations. Emitted semi-volatile primary organic aerosols evaporate almost completely in the high volatile range, while they remain in the particle phase in the low volatility range. Their volatility distribution depends on the applied emission factors, oxidation by OH radicals, and temperature. We also compare against parallel simulations with the original scheme, which represented only the particulate and non-volatile component of the organic aerosol, examining how differently the condensed phase organic matter is distributed across the mixing states in the model. The results demonstrate the importance of representing organic aerosol as a semi-volatile aerosol, and explicitly calculating the partitioning of organic species between the gas and particulate phases. [ABSTRACT FROM AUTHOR]

The radiative forcing of anthropogenic aerosols associated with aerosol‐cloud interactions (RFaci) remains the largest source of uncertainty in climate prediction. The calculation of particle number concentration (PNC), one of the critical parameters affecting RFaci, is generally simplified in climate models. Here we employ outputs from long‐term (30‐year) simulations of a global size‐resolved (sectional) aerosol microphysics model and a machine‐learning tool to develop a Random Forest Regression Model (RFRM) for PNC. We have implemented the PNC RFRM in GISS‐ModelE2.1 with a mass‐based One‐Moment Aerosol module, which is one of CMIP6 models. Compared to the default setting, the GISS‐ModelE2.1 simulation based on RFRM reduces the changes of cloud droplet number concentration associated with anthropogenic emissions, and decreases the RFaci from −1.46 to −1.11 W·m−2. This work highlights a promising approach based on machine learning to reduce uncertainties of climate models in predicting PNC and RFaci without compromising their computing efficiency. Plain Language Summary: The largest uncertainty in assessing climate change is due to the interaction of aerosols with clouds and its effect on the Earth's energy budget. To reduce this uncertainty, it is important to accurately quantify aerosols. This is possible by accounting for the physical processes and interactions happening at the scale of the aerosol sizes. However, such an approach would be computationally demanding on climate models, making them impractical to study historical changes. To address this dilemma, we use a machine learning/artificial intelligence (ML/AI) technique that learns aerosol microphysics. When coupled to a climate model, it speedily quantifies aerosols in strong agreement with atmospheric measurements. Compared to the climate model without this implicit physical treatment, the historical changes in cloud droplet numbers and the cooling effect of aerosols are now estimated lower and less uncertain. This highlights the potential of ML/AI in reducing climate model uncertainties without hindering their computational efficiency. Key Points: A physics‐guided machine learning (ML) model for particle number concentration (PNC) couples with a global climate model with low computational overheadML PNC are in better agreement with measurements and reduce cloud droplet number concentration changes caused by anthropogenic emissionsRadiative forcing due to aerosol‐cloud interactions indicates weaker cooling (−1.11 vs. −1.46 W·m−2) and is closer to IPCC median value [ABSTRACT FROM AUTHOR]

This paper presents the response to anthropogenic forcing in the GISS‐E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non‐interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One‐Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1‐G) and HYCOM (E2.1‐H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1‐2.6, SSP2‐4.5, SSP4‐6.0, and SSP5‐8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high‐mitigation scenarios SSP1‐1.9 and SSP1‐2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1‐H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5‐8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1‐G (−1.21 × 106 km2/°C) and E2.1‐H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5‐8.5 in the E2.1‐G model, comparable to the reduction in the corresponding CMIP5 GISS‐E2 RCP8.5 simulation. Both low‐end scenarios SSP1‐1.9 and SSP1‐2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century). Plain Language Summary: The projections of future climate change are uncertain because they are dependent on different possible scenarios of human‐caused emissions and their interaction with natural forcings, internal climate variability, and inter‐model differences. This paper presents the results of the climate model of the NASA Goddard Institute for Space Studies, GISS‐E2.1, for the anthropogenically forced climate response for the twenty first century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The sensitivity of the model response to different magnitudes of anthropogenic forcings in the twenty‐first‐century scenarios were performed using two different versions for the atmospheric composition and two different ocean general circulation models. Compared to CMIP5 GISS‐E2 versions, the CMIP6 GISS‐E2.1 climate model shows a stronger warming by 2100 in comparable scenarios due to larger effective climate sensitivity and transient climate response. Both climate models with two different ocean components project decreases in the Atlantic overturning stream function by 2100. Key Points: GISS E2.1 model with different configurations is used to carry out 134 Shared Socioeconomic Pathway (SSP) experimentsGISS‐E2.1 climate model shows a stronger warming by 2,100 in comparable Representative Concentration Pathway scenarios in CMIP5 due to larger effective climate sensitivity and stronger transient climate responseBoth coupled models, E2.1‐G and E2.1‐H, project decreases in the Atlantic overturning stream function by 2100 with the largest decrease in the warmest scenario SSP5‐8.5 in the E2.1‐G model [ABSTRACT FROM AUTHOR]

Biases in aerosol optical depths (AOD) and land surface albedos in the AeroCom models are manifested in the top‐of‐atmosphere (TOA) clear‐sky reflected shortwave (SW) fluxes. Biases in the SW fluxes from AeroCom models are quantitatively related to biases in AOD and land surface albedo by using their radiative kernels. Over ocean, AOD contributes about 25% to the 60°S–60°N mean SW flux bias for the multi‐model mean (MMM) result. Over land, AOD and land surface albedo contribute about 40% and 30%, respectively, to the 60°S–60°N mean SW flux bias for the MMM result. Furthermore, the spatial patterns of the SW flux biases derived from the radiative kernels are very similar to those between models and CERES observation, with the correlation coefficient of 0.6 over ocean and 0.76 over land for MMM using data of 2010. Satellite data used in this evaluation are derived independently from each other, consistencies in their bias patterns when compared with model simulations suggest that these patterns are robust. This highlights the importance of evaluating related variables in a synergistic manner to provide an unambiguous assessment of the models, as results from single parameter assessments are often confounded by measurement uncertainty. Model biases in land surface albedos can and must be corrected to accurately calculate TOA flux. We also compare the AOD trend from three models with the observation‐based counterpart. These models reproduce all notable trends in AOD except the decreasing trend over eastern China and the adjacent oceanic regions due to limitations in the emission data set. Plain Language Summary: Aerosol optical depths (AOD) from satellite retrievals have been used to evaluate the AeroCom models. However, these evaluations are often non‐conclusive due to uncertainties in the retrievals and the differences among many products. In this study, biases in top‐of‐atmosphere (TOA) reflected SW fluxes are linked to biases in AOD and surface albedo by using their respective radiative kernels. We found that biases in AOD and land surface albedo can explain significant amount of the SW flux biases on both global and regional scales. This study highlights the importance of evaluating related variables in a synergistic manner to provide an unambiguous assessment of the models, as results from single parameter assessments are often confounded by measurement uncertainty. This study clearly demonstrates the deficiency of land surface albedo used by the AeroCom models and usage of observation‐based land surface albedo should be required for all models participating in AeroCom experiments. Key Points: Over ocean, aerosol optical depth (AOD) bias contributes about 25% to the 60°S–60°N mean shortwave (SW) flux bias for the multi‐model mean (MMM) resultOver land, AOD and land surface albedo biases contribute about 40% and 30% to the 60°S–60°N mean SW flux bias for the MMM resultObservation‐based land surface albedo should be used by all models to accurately calculate the top‐of‐atmosphere (TOA) SW fluxes [ABSTRACT FROM AUTHOR]

Socioeconomic development in low- and middle-income countries has been accompanied by increased emissions of air pollutants, such as nitrogen oxides [NOx: nitrogen dioxide (NO2) + nitric oxide (NO)], which affect human health. In sub-Saharan Africa, fossil fuel combustion has nearly doubled since 2000. At the same time, landscape biomass burning--another important NOx source--has declined in north equatorial Africa, attributed to changes in climate and anthropogenic fire management. Here, we use satellite observations of tropospheric NO2 vertical column densities (VCDs) and burned area to identify NO2 trends and drivers over Africa. Across the northern ecosystems where biomass burning occurs--home to hundreds of millions of people--mean annual tropospheric NO2 VCDs decreased by 4.5% from 2005 through 2017 during the dry season of November through February. Reductions in burned area explained the majority of variation in NO2 VCDs, though changes in fossil fuel emissions also explained some variation. Over Africa's biomass burning regions, raising mean GDP density (USD·km-2) above its lowest levels is associated with lower NO2 VCDs during the dry season, suggesting that economic development mitigates net NO2 emissions during these highly polluted months. In contrast to the traditional notion that socioeconomic development increases air pollutant concentrations in low- and middle-income nations, our results suggest that countries in Africa's northern biomass-burning region are following a different pathway during the fire season, resulting in potential air quality benefits. However, these benefits may be lost with increasing fossil fuel use and are absent during the rainy season. [ABSTRACT FROM AUTHOR]

Simulations of the CMIP6 historical period 1850–2014, characterized by the emergence of anthropogenic climate drivers like greenhouse gases, are presented for different configurations of the NASA Goddard Institute for Space Studies (GISS) Earth System ModelE2.1. The GISS‐E2.1 ensembles are more sensitive to greenhouse gas forcing than their CMIP5 predecessors (GISS‐E2) but warm less during recent decades due to a forcing reduction that is attributed to greater longwave opacity in the GISS‐E2.1 pre‐industrial simulations. This results in an atmosphere less sensitive to increases in opacity from rising greenhouse gas concentrations, demonstrating the importance of the base climatology to forcing and forced climate trends. Most model versions match observed temperature trends since 1979 from the ocean to the stratosphere. The choice of ocean model is important to the transient climate response, as found previously in CMIP5 GISS‐E2: the model that more efficiently exports heat to the deep ocean shows a smaller rise in tropospheric temperature. Model sea level rise over the historical period is traced to excessive drawdown of aquifers to meet irrigation demand with a smaller contribution from thermal expansion. This shows how fully coupled models can provide indirect observational constraints upon forcing, in this case, constraining irrigation rates with observed sea level changes. The overall agreement of GISS‐E2.1 with observed trends is familiar from evaluation of its predecessors, as is the conclusion that these trends are almost entirely anthropogenic in origin. Plain Language Summary: Measurements show clear evidence of warming over the twentieth century and up to the present day. Our anticipation of future change comes from computer models of climate. These are based upon well‐established physical principles like Newton's laws of motion and radiative transfer theory; the models are closely related to those used for weather forecasting. We can never predict the weather on a particular day, 50 years in the future, but we can calculate whether that future decade will be warmer than our present climate. Part of our confidence in such a forecast comes from testing a climate model's ability to reproduce warming and other changes measured over the past century. We use observations of atmospheric composition and the sunlight received by our planet to calculate how the model responds to their changes. The climate model of the NASA Goddard Institute for Space Studies, GISS‐E2.1, closely follows changes measured in the ocean and atmosphere as the concentrations of greenhouse gases and other pollutants rise. This agreement suggests that future warming by greenhouse gases will be reliably predicted by GISS‐E2.1. This suggests that the warming we already experience is due to our consumption of fossil fuels that has led to the increase of carbon dioxide and other greenhouse gases in the atmosphere over the past two centuries. Key Points: Tropospheric warming and ocean heat uptake by 2014 are smaller in GISS‐E2.1 and closer to observed trends than in its CMIP5 predecessorGISS‐E2.1 climate sensitivity is higher than in CMIP5 GISS‐E2, but forcing by greenhouse gases is smallerAtmospheric trends vary among model configurations with the storage of heat beneath the thermocline [ABSTRACT FROM AUTHOR]

We assess the effective radiative forcing due to ozone‐depleting substances using models participating in the Aerosols and Chemistry and Radiative Forcing Model Intercomparison Projects (AerChemMIP, RFMIP). A large intermodel spread in this globally averaged quantity necessitates an "emergent constraint" approach whereby we link the radiative forcing to ozone declines measured and simulated during 1979–2000, excluding two volcanically perturbed periods. During this period, ozone‐depleting substances were increasing, and several merged satellite‐based climatologies document the ensuing decline of total‐column ozone. Using these analyses, we find an effective radiative forcing of −0.05 to 0.13 W m−2. Our best estimate (0.04 W m−2) is on the edge of the "likely" range given by the Fifth Assessment Report of IPCC of 0.03 to 0.33 W m−2 but is in better agreement with two other literature results. Plain Language Summary: Chloroflourocarbons and other compounds involved in ozone depletion are also powerful greenhouse gases, but their contribution to global warming is reduced due to the cooling effect of the ozone loss which they induce. Models informing an upcoming climate report disagree on the ozone loss and thus on the climate influence of these gases. Here we use observed ozone loss to reduce the resultant uncertainty in their overall climate influence and infer a smaller warming influence of these substances than was considered likely in a 2013 climate report. The result implies a smaller benefit to climate due to their phase‐out, mandated under the Montreal Protocol, than would have been the case under previous understanding. Key Points: Effective radiative forcing of ozone‐depleting substances, as discerned from CMIP6 simulations, spans a large rangeUsing an emergent constraint approach, our new estimate is consistent with observational climatologies of total‐column ozoneThis range implies a smaller forcing than the estimate provided by the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [ABSTRACT FROM AUTHOR]

The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the primary future climate projections within the Coupled Model Intercomparison Project Phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models for concentration driven simulations. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century encompassing the Tier 1 experiments (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by 1.15 °C) reached at the upper end of the 5-95 % envelope of the highest scenario, SSP5-8.5. This is due to both the wider range of radiative forcing that the new scenarios cover and to higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensembles' spread, according to a set of initial condition ensemble simulations available under SSP3-7.0. The same experiments suggest a tendency for internal variability to decrease along the course of the century, a new result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP, but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades in mid-century, as represented in SSP5-3.4OS, does not affect the end outcome in terms of temperature and precipitation changes by 2100, which return to the same level as those reached by the gradually increasing SSP4-3.4. Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level show all scenarios reaching 1.5 °C of warming compared to the 1850-1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering 20-28 years from present. 2 °C of warming is reached as early as the late '30s by the ensemble mean under SSP5-8.5, but as late as the late '50s under SSP1-2.6. The highest warming level considered, 5 °C, is reached only by the ensemble mean under SSP5-8.5, and not until the mid-90s. [ABSTRACT FROM AUTHOR]

This paper describes the GISS‐E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS‐E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden‐Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2 × CO2 is slightly higher than previously at 2.7–3.1°C (depending on version) and is a result of lower CO2 radiative forcing and stronger positive feedbacks. Plain Language Summary: This paper describes the latest iteration of the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) climate model, which will be used for understanding historical climate change and to make projections for the future. We compare the model output to a wide range of observations over the recent era (1979–2014) and show that there has been a significant increase in how well the model performs compared to the previous version from 2014, particularly in the Southern Ocean, though some persistent biases remain. The model has a temperature response to the increase of carbon dioxide that is slightly higher than previous versions but is well within the range expected from observational and past climate constraints. Key Points: GISS‐E2.1 is an updated climate model version for use within the CMIP6 projectAtmospheric composition is calculated consistently in all model versionsResults demonstrate a significant improvement in skill in a climate model without changes to atmospheric resolution [ABSTRACT FROM AUTHOR]

Fires affect the composition of the atmosphere and Earth's radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth system model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS (Goddard Institute for Space Studies) interactive fire emissions module. The pyrE module is driven by environmental variables like flammability and cloud-to-ground lightning, calculated by the GISS ModelE ESM, and parameterized by anthropogenic impacts based on population density data. Fire emissions are generated from the flaming phase in pyrE (active fires). Using pyrE, we examine fire occurrence, regional fire suppression, burned area, fire emissions, and how it all affects atmospheric composition. To do so, we evaluate pyrE by comparing it to satellite-based datasets of fire count, burned area, fire emissions, and aerosol optical depth (AOD). We demonstrate pyrE's ability to simulate the daily and seasonal cycles of open fires and resulting emissions. Our results indicate that interactive fire emissions are biased low by 32 %–42 %, depending on emitted species, compared to the GFED4s (Global Fire Emissions Database) inventory. The bias in emissions drives underestimation in column densities, which is diluted by natural and anthropogenic emissions sources and production and loss mechanisms. Regionally, the resulting AOD of a simulation with interactive fire emissions is underestimated mostly over Indonesia compared to a simulation with GFED4s emissions and to MODIS AOD. In other parts of the world pyrE's performance in terms of AOD is marginal to a simulation with prescribed fire emissions. [ABSTRACT FROM AUTHOR]

Fires affect the composition of the atmosphere and Earth's radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth System Model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS interactive fire emissions module. The pyrE module is driven by environmental variables like flammability and cloud-to-ground lightning, calculated by the GISS ModelE ESM, and parameterized anthropogenic impacts based on population density data. Fire emissions are generated from the actual flaming phase in pyrE (fire count), not the scar left behind (burned area), as is commonly done in other interactive fire modules. Using pyrE, we examine fire behavior, regional fire suppression, burned area, fire emissions, and how it all affects atmospheric composition. To do so, we evaluate pyrE by comparing it to satellite-based datasets of fire count, burned area, fire emissions, and aerosol optical depth (AOD). We demonstrate pyrE's ability to simulate the daily and seasonal cycles of open fires and resulting emissions. Our results indicate that interactive fire emissions are bias low by 32-42 %, depending on emitted species, compared to the GFED4s inventory. The bias in emissions drives underestimation in column densities, which is diluted by natural and anthropogenic emissions sources and production and loss mechanisms. Yet, in terms of AOD, a simulation with interactive fire emissions performs just as well as a simulation with prescribed fire emissions. [ABSTRACT FROM AUTHOR]

The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol data set for each experiment to minimize differences in the applied volcanic forcing. It defines a set of initial conditions to assess how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically forced responses of the coupled ocean-atmosphere system are robustly simulated by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input data sets to be used. [ABSTRACT FROM AUTHOR]

The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Climate Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the model intercomparison project on the climate response to volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol dataset for each experiment to eliminate differences in the applied volcanic forcing, and defines a set of initial conditions to determine how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically-forced responses of the coupled ocean-atmosphere system are robustly simulated by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input datasets to be used. [ABSTRACT FROM AUTHOR]

Observations of climate change during the CMIP5 extended historical period (1850-2012) are compared to trends simulated by six versions of the NASA Goddard Institute for Space Studies ModelE2 Earth System Model. The six models are constructed from three versions of the ModelE2 atmospheric general circulation model, distinguished by their treatment of atmospheric composition and the aerosol indirect effect, combined with two ocean general circulation models, HYCOM and Russell. Forcings that perturb the model climate during the historical period are described. Five-member ensemble averages from each of the six versions of ModelE2 simulate trends of surface air temperature, atmospheric temperature, sea ice and ocean heat content that are in general agreement with observed trends, although simulated warming is slightly excessive within the past decade. Only simulations that include increasing concentrations of long-lived greenhouse gases match the warming observed during the twentieth century. Differences in twentieth-century warming among the six model versions can be attributed to differences in climate sensitivity, aerosol and ozone forcing, and heat uptake by the deep ocean. Coupled models with HYCOM export less heat to the deep ocean, associated with reduced surface warming in regions of deepwater formation, but greater warming elsewhere at high latitudes along with reduced sea ice. All ensembles show twentieth-century annular trends toward reduced surface pressure at southern high latitudes and a poleward shift of the midlatitude westerlies, consistent with observations. [ABSTRACT FROM AUTHOR]

We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980-2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics. [ABSTRACT FROM AUTHOR]

An intercomparison has been set up to study the representation of the atmospheric chemistry of the pre-industrial troposphere in earth system and other global tropospheric chemistry-transport models. The intercomparison employed a constrained box model and utilised tropospheric trace gas composition data for the pre-industrial times at ninety mid-latitude surface locations. Incremental additions of four organic compounds: methane, ethane, acetone and propane, were used to perturb the constrained box model and generate responses in hydroxyl radicals and tropospheric ozone at each location and with each chemical mechanism. Although the responses agreed well across the chemical mechanisms from the selected earth system and other global tropospheric chemistry-transport models, there were differences in the detailed responses between the chemical mechanisms that could be tracked down by sensitivity analysis to differences in the representation of C 1 –C 3 chemistry. Inter-mechanism ranges in NO x compensation points were about 0.17 ± 0.12 when expressed relative to the inter-mechanism average. Monte Carlo uncertainty analysis carried out with a single chemical mechanism put the intra-mechanism range a factor of three higher at 0.50 ± 0.12. Similar differences between inter-mechanism and intra-mechanism ranges were found for hydroxyl radical depletion but were up to a factor of six wider for ozone formation from incremental additions of organic compounds. The cause of the discrepancies between the inter- and intra-mechanism ranges was found to be the large uncertainties that are present in the laboratory determinations of the rate coefficients and product channel branching ratios of some key chemical reactions involving organic peroxy radicals and hydroperoxides. Whilst these large uncertainties are present in the laboratory determinations, there will be irreducible uncertainties in the predictions from the earth system and other chemistry-transport models of methane and tropospheric ozone trends since pre-industrial times and hence their contributions to the radiative forcing of climate change. Further definitive laboratory studies of the reaction rates and product yields of the reactions of the simple organic peroxy radicals and hydroperoxides are required to resolve and reduce current uncertainties in earth system and chemistry-transport model predictions. • Eight chemical mechanisms are carefully examined for pre-industrial times. • Inter-mechanism differences stem from representation of C 1 –C 3 chemistry. • Intra-mechanism ranges are wider than inter-mechanism ranges. [ABSTRACT FROM AUTHOR]

Evaluating multicomponent climate change mitigation strategies requires knowledge of the diverse direct and indirect effects of emissions. Methane, ozone, and aerosols are linked through atmospheric chemistry so that emissions of a single pollutant can affect several species. We calculated atmospheric composition changes, historical radiative forcing, and forcing per unit of emission due to aerosol and tropospheric ozone precursor emissions in a coupled composition-climate model. We found that gas-aerosol interactions substantially alter the relative importance of the various emissions. In particular, methane emissions have a larger impact than that used in current carbon-trading schemes or in the Kyoto Protocol Thus, assessments of multigas mitigation policies, as well as any separate efforts to mitigate warming from short-lived pollutants, should include gas-aerosol interactions. [ABSTRACT FROM AUTHOR]