Rapid adjustments are responses to forcing agents that cause a perturbation to the top of atmosphere energy budget but are uncoupled to changes in surface warming. Different mechanisms are ...responsible for these adjustments for a variety of climate drivers. These remain to be quantified in detail. It is shown that rapid adjustments reduce the effective radiative forcing (ERF) of black carbon by half of the instantaneous forcing, but for CO2 forcing, rapid adjustments increase ERF. Competing tropospheric adjustments for CO2 forcing are individually significant but sum to zero, such that the ERF equals the stratospherically adjusted radiative forcing, but this is not true for other forcing agents. Additional experiments of increase in the solar constant and increase in CH4 are used to show that a key factor of the rapid adjustment for an individual climate driver is changes in temperature in the upper troposphere and lower stratosphere.
Plain Language Summary
Long‐term global warming can be estimated with knowledge of how climate forcing agents affect the Earth's top‐of‐atmosphere energy imbalance or effective radiative forcing. Changes in climate forcers, such as greenhouse gases, the Sun's intensity, or emission of aerosol particles, typically impose a direct change in the energy budget, termed an instantaneous radiative forcing. Further to this, a climate forcer may induce changes in the atmosphere, such as a change in thermal structure, clouds, or humidity. These changes themselves, termed rapid adjustments, contribute to the top‐of‐atmosphere energy budget. Together, the instantaneous radiative forcing plus rapid adjustments equals the effective radiative forcing. We show that for different climate forcing agents, the rapid adjustments behave very differently and are driven by different atmospheric mechanisms. For example, rapid adjustments add to the instantaneous forcing for a carbon dioxide increase, due to a cooling of the stratosphere, but oppose instantaneous forcing for black carbon, driven by a warming troposphere and lowering of cloud height. Understanding rapid adjustments gives a more complete picture of the climate effects of different climate forcers.
Key Points
Rapid adjustments affect the Earth's energy balance in different ways for greenhouse gas, aerosol, and solar forcing
Radiative kernels and partial radiative perturbations are used to diagnose rapid adjustments from atmospheric and cloud changes
Noncloud adjustments agree well between models, whereas cloud adjustments exhibit more spread
While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small ...number of realizations to international climate model assessments e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5). As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. In response, the Community Earth System Model (CESM) community designed the CESM Large Ensemble (CESM-LE) with the explicit goal of enabling assessment of climate change in the presence of internal climate variability. All CESM-LE simulations use a single CMIP5 model (CESM with the Community Atmosphere Model, version 5). The core simulations replay the twenty to twenty-first century (1920–2100) 30 times under historical and representative concentration pathway 8.5 external forcing with small initial condition differences. Two companion 1000+-yr-long preindustrial control simulations (fully coupled, prognostic atmosphere and land only) allow assessment of internal climate variability in the absence of climate change. Comprehensive outputs, including many daily fields, are available as single-variable time series on the Earth System Grid for anyone to use. Early results demonstrate the substantial influence of internal climate variability on twentieth- to twenty-first-century climate trajectories. Global warming hiatus decades occur, similar to those recently observed. Internal climate variability alone can produce projection spread comparable to that in CMIP5. Scientists and stakeholders can use CESM-LE outputs to help interpret the observational record, to understand projection spread and to plan for a range of possible futures influenced by both internal climate variability and forced climate change.
The Community Earth System Model Version 2 (CESM2) has an equilibrium climate sensitivity (ECS) of 5.3 K. ECS is an emergent property of both climate feedbacks and aerosol forcing. The increase in ...ECS over the previous version (CESM1) is the result of cloud feedbacks. Interim versions of CESM2 had a land model that damped ECS. Part of the ECS change results from evolving the model configuration to reproduce the long‐term trend of global and regional surface temperature over the twentieth century in response to climate forcings. Changes made to reduce sensitivity to aerosols also impacted cloud feedbacks, which significantly influence ECS. CESM2 simulations compare very well to observations of present climate. It is critical to understand whether the high ECS, outside the best estimate range of 1.5–4.5 K, is plausible.
Key Points
The Community Earth System Model Version 2 (CESM2) has an Equilibrium Climate Sensitivity (ECS) of 5.3 K
ECS change is mostly due to atmospheric cloud feedbacks, with land surface impacts in intermediate versions
Processes that impact ECS through cloud feedbacks also impact aerosol forcing of climate
The sensitivity of secondary organic aerosol (SOA) concentration to changes in climate and emissions is investigated using a coupled global atmosphere‐land model driven by the year 2100 IPCC A1B ...scenario predictions. The Community Atmosphere Model (CAM3) is updated with recent laboratory determined yields for SOA formation from monoterpene oxidation, isoprene photooxidation and aromatic photooxidation. Biogenic emissions of isoprene and monoterpenes are simulated interactively using the Model of Emissions of Gases and Aerosols (MEGAN2) within the Community Land Model (CLM3). The global mean SOA burden is predicted to increase by 36% in 2100, primarily the result of rising biogenic and anthropogenic emissions which independently increase the burden by 26% and 7%. The later includes enhanced biogenic SOA formation due to increased emissions of primary organic aerosol (5–25% increases in surface SOA concentrations in 2100). Climate change alone (via temperature, removal rates, and oxidative capacity) does not change the global mean SOA production, but the global burden increases by 6%. The global burden of anthropogenic SOA experiences proportionally more growth than biogenic SOA in 2100 from the net effect of climate and emissions (67% increase predicted). Projected anthropogenic land use change for 2100 (A2) is predicted to reduce the global SOA burden by 14%, largely the result of cropland expansion. South America is the largest global source region for SOA in the present day and 2100, but Asia experiences the largest relative growth in SOA production by 2100 because of the large predicted increases in Asian anthropogenic aromatic emissions. The projected decrease in global sulfur emissions implies that SOA will contribute a progressively larger fraction of the global aerosol burden.
The Community Atmosphere Model (CAM), version 5, is now coupled to extensive tropospheric and stratospheric chemistry, called CAM5-chem, and is available in addition to CAM4-chem in the Community ...Earth System Model (CESM) version 1.2. The main focus of this paper is to compare the performance of configurations with internally derived "free running" (FR) meteorology and "specified dynamics" (SD) against observations from surface, aircraft, and satellite, as well as understand the origin of the identified differences. We focus on the representation of aerosols and chemistry. All model configurations reproduce tropospheric ozone for most regions based on in situ and satellite observations. However, shortcomings exist in the representation of ozone precursors and aerosols. Tropospheric ozone in all model configurations agrees for the most part with ozonesondes and satellite observations in the tropics and the Northern Hemisphere within the variability of the observations. Southern hemispheric tropospheric ozone is consistently underestimated by up to 25%. Differences in convection and stratosphere to troposphere exchange processes are mostly responsible for differences in ozone in the different model configurations. Carbon monoxide (CO) and other volatile organic compounds are largely underestimated in Northern Hemisphere mid-latitudes based on satellite and aircraft observations. Nitrogen oxides (NOx) are biased low in the free tropical troposphere, whereas peroxyacetyl nitrate (PAN) is overestimated in particular in high northern latitudes. The present-day methane lifetime estimates are compared among the different model configurations. These range between 7.8 years in the SD configuration of CAM5-chem and 8.8 years in the FR configuration of CAM4-chem and are therefore underestimated compared to observational estimations. We find that differences in tropospheric aerosol surface area between CAM4 and CAM5 play an important role in controlling the burden of the tropical tropospheric hydroxyl radical (OH), which causes differences in tropical methane lifetime of about half a year between CAM4-chem and CAM5-chem. In addition, different distributions of NOx from lightning explain about half of the difference between SD and FR model versions in both CAM4-chem and CAM5-chem. Remaining differences in the tropical OH burden are due to enhanced tropical ozone burden in SD configurations compared to the FR versions, which are not only caused by differences in chemical production or loss but also by transport and mixing. For future studies, we recommend the use of CAM5-chem configurations, due to improved aerosol description and inclusion of aerosol–cloud interactions. However, smaller tropospheric surface area density in the current version of CAM5-chem compared to CAM4-chem results in larger oxidizing capacity in the troposphere and therefore a shorter methane lifetime.
Different climate drivers influence precipitation in different ways. Here we use radiative kernels to understand the influence of rapid adjustment processes on precipitation in climate models. Rapid ...adjustments are generally triggered by the initial heating or cooling of the atmosphere from an external climate driver. For precipitation changes, rapid adjustments due to changes in temperature, water vapor, and clouds are most important. In this study we have investigated five climate drivers (CO2, CH4, solar irradiance, black carbon, and sulfate aerosols). The fast precipitation responses to a doubling of CO2 and a 10‐fold increase in black carbon are found to be similar, despite very different instantaneous changes in the radiative cooling, individual rapid adjustments, and sensible heating. The model diversity in rapid adjustments is smaller for the experiment involving an increase in the solar irradiance compared to the other climate driver perturbations, and this is also seen in the precipitation changes.
Plain Language Summary
Future projections of precipitation changes are uncertain, both on regional and global scales. Understanding the climate models' diversity of precipitation change and how these models respond to various climate drivers, such as greenhouse gases and aerosols, is a key topic in climate research. Using sophisticated techniques, we quantify the processes altering precipitation changes on a short time scale and show that changes in the vertical profile of temperature, water vapor, and clouds contribute very differently to precipitation changes for various climate drivers. Our results show that model diversity in precipitation changes varies strongly between the climate drivers.
Key Points
Separation of instantaneous and rapid adjustment contributions to precipitation changes
Contributions of rapid adjustments to precipitation changes differ substantially between climate drivers
Radiative kernels are applied to understand individual rapid adjustment terms
The Whole Atmosphere Community Climate Model version 6 (WACCM6) is a major update of the whole atmosphere modeling capability in the Community Earth System Model (CESM), featuring enhanced physical, ...chemical and aerosol parameterizations. This work describes WACCM6 and some of the important features of the model. WACCM6 can reproduce many modes of variability and trends in the middle atmosphere, including the quasi‐biennial oscillation, stratospheric sudden warmings, and the evolution of Southern Hemisphere springtime ozone depletion over the twentieth century. WACCM6 can also reproduce the climate and temperature trends of the 20th century throughout the atmospheric column. The representation of the climate has improved in WACCM6, relative to WACCM4. In addition, there are improvements in high‐latitude climate variability at the surface and sea ice extent in WACCM6 over the lower top version of the model (CAM6) that comes from the extended vertical domain and expanded aerosol chemistry in WACCM6, highlighting the importance of the stratosphere and tropospheric chemistry for high‐latitude climate variability.
Plain Language Summary
This manuscript describes the Whole Atmosphere Community Climate Model Version 6 (WACCM6), a chemistry and climate model which extends up to 140 km in the upper atmosphere. WACCM6 reproduces many important features of the climate system, and the addition of detailed chemistry and the higher than normal model top produces slightly improved simulations of the Arctic region.
Key Points
WACCM6 is a major upgrade to previous versions
WACCM6 can reproduce many modes of variability and trends in the middle atmosphere
WACCM6 provides improvements in high‐latitude climate variability at the surface and sea ice extent over a low top model
Two recent papers have quantified long‐term ozone (O3) changes observed at northern midlatitude sites that are believed to represent baseline (here understood as representative of continental to ...hemispheric scales) conditions. Three chemistry‐climate models (NCAR CAM‐chem, GFDL‐CM3, and GISS‐E2‐R) have calculated retrospective tropospheric O3 concentrations as part of the Atmospheric Chemistry and Climate Model Intercomparison Project and Coupled Model Intercomparison Project Phase 5 model intercomparisons. We present an approach for quantitative comparisons of model results with measurements for seasonally averaged O3 concentrations. There is considerable qualitative agreement between the measurements and the models, but there are also substantial and consistent quantitative disagreements. Most notably, models (1) overestimate absolute O3 mixing ratios, on average by ~5 to 17 ppbv in the year 2000, (2) capture only ~50% of O3 changes observed over the past five to six decades, and little of observed seasonal differences, and (3) capture ~25 to 45% of the rate of change of the long‐term changes. These disagreements are significant enough to indicate that only limited confidence can be placed on estimates of present‐day radiative forcing of tropospheric O3 derived from modeled historic concentration changes and on predicted future O3 concentrations. Evidently our understanding of tropospheric O3, or the incorporation of chemistry and transport processes into current chemical climate models, is incomplete. Modeled O3 trends approximately parallel estimated trends in anthropogenic emissions of NOx, an important O3 precursor, while measured O3 changes increase more rapidly than these emission estimates.
Key Points
CCM results disagree with measured long‐term changes of O3 concentrations
Reduced confidence implied for estimates of radiative forcing of tropospheric O3
Understanding of tropospheric O3 as it is incorporated into models is incomplete
PDF
