Simulated multi-model "diversity" in aerosol direct radiative forcing estimates is often perceived as a measure of aerosol uncertainty. However, current models used for aerosol radiative forcing ...calculations vary considerably in model components relevant for forcing calculations and the associated "host-model uncertainties" are generally convoluted with the actual aerosol uncertainty. In this AeroCom Prescribed intercomparison study we systematically isolate and quantify host model uncertainties on aerosol forcing experiments through prescription of identical aerosol radiative properties in twelve participating models. Even with prescribed aerosol radiative properties, simulated clear-sky and all-sky aerosol radiative forcings show significant diversity. For a purely scattering case with globally constant optical depth of 0.2, the global-mean all-sky top-of-atmosphere radiative forcing is -4.47 Wm super(-2) and the inter-model standard deviation is 0.55 Wm super(-2), corresponding to a relative standard deviation of 12%. For a case with partially absorbing aerosol with an aerosol optical depth of 0.2 and single scattering albedo of 0.8, the forcing changes to 1.04 Wm super(-2), and the standard deviation increases to 1.01 W super(-2), corresponding to a significant relative standard deviation of 97%. However, the top-of-atmosphere forcing variability owing to absorption (subtracting the scattering case from the case with scattering and absorption) is low, with absolute (relative) standard deviations of 0.45 Wm super(-2) (8%) clear-sky and 0.62 Wm super(-2) (11%) all-sky. Scaling the forcing standard deviation for a purely scattering case to match the sulfate radiative forcing in the AeroCom Direct Effect experiment demonstrates that host model uncertainties could explain about 36% of the overall sulfate forcing diversity of 0.11 Wm super(-2) in the AeroCom Direct Radiative Effect experiment. Host model errors in aerosol radiative forcing are largest in regions of uncertain host model components, such as stratocumulus cloud decks or areas with poorly constrained surface albedos, such as sea ice. Our results demonstrate that host model uncertainties are an important component of aerosol forcing uncertainty that require further attention.
Over the past few decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and air pollution regulations. Here, ...we show the resulting changes to aerosol and ozone abundances and their radiative forcing using recently updated emission data for the period 1990-2015, as simulated by seven global atmospheric composition models. The models broadly reproduce large-scale changes in surface aerosol and ozone based on observations (e.g. 1 to 3 percent per year in aerosols over the USA and Europe). The global mean radiative forcing due to ozone and aerosol changes over the 1990-2015 period increased by 0.17 plus or minus 0.08 watts per square meter, with approximately one-third due to ozone. This increase is more strongly positive than that reported in IPCC AR5 (Intergovernmental Panel on Climate Change Fifth Assessment Report). The main reasons for the increased positive radiative forcing of aerosols over this period are the substantial reduction of global mean SO2 emissions, which is stronger in the new emission inventory compared to that used in the IPCC analysis, and higher black carbon emissions.
In this paper, we present the computational task-management tool Ganga, which allows for the specification, submission, bookkeeping and post-processing of computational tasks on a wide set of ...distributed resources. Ganga has been developed to solve a problem increasingly common in scientific projects, which is that researchers must regularly switch between different processing systems, each with its own command set, to complete their computational tasks. Ganga provides a homogeneous environment for processing data on heterogeneous resources. We give examples from High Energy Physics, demonstrating how an analysis can be developed on a local system and then transparently moved to a Grid system for processing of all available data. Ganga has an API that can be used via an interactive interface, in scripts, or through a GUI. Specific knowledge about types of tasks or computational resources is provided at run-time through a plugin system, making new developments easy to integrate. We give an overview of the Ganga architecture, give examples of current use, and demonstrate how Ganga can be used in many different areas of science.
Program title:Ganga
Catalogue identifier: AEEN_v1_0
Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEN_v1_0.html
Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland
Licensing provisions: GPL
No. of lines in distributed program, including test data, etc.: 224 590
No. of bytes in distributed program, including test data, etc.: 14 365 315
Distribution format: tar.gz
Programming language: Python
Computer: personal computers, laptops
Operating system: Linux/Unix
RAM: 1 MB
Classification: 6.2, 6.5
Nature of problem: Management of computational tasks for scientific applications on heterogenous distributed systems, including local, batch farms, opportunistic clusters and Grids.
Solution method: High-level job management interface, including command line, scripting and GUI components.
Restrictions: Access to the distributed resources depends on the installed, 3rd party software such as batch system client or Grid user interface.
Anthropogenic emissions of short-lived climate forcers (SLCFs) affect both air quality and climate. How much regional temperatures are affected by ambitious SLCF emission mitigation policies is, ...however, still uncertain. We investigate the potential temperature implications of stringent air quality policies by applying matrices of regional temperature responses to new pathways for future anthropogenic emissions of aerosols, methane (CH4), and other short-lived gases. These measures have only a minor impact on CO2 emissions. Two main options are explored, one with climate optimal reductions (i.e., constructed to yield a maximum global cooling) and one with the maximum technically feasible reductions. The temperature response is calculated for four latitude response bands (90–28∘ S, 28∘ S–28∘ N, 28–60∘ N, and 60–90∘ N) by using existing absolute regional temperature change potential (ARTP) values for four emission regions: Europe, East Asia, shipping, and the rest of the world. By 2050, we find that global surface temperature can be reduced by -0.3±0.08 ∘C with climate-optimal mitigation of SLCFs relative to a baseline scenario and as much as −0.7 ∘C in the Arctic. Cutting CH4 and black carbon (BC) emissions contributes the most. The net global cooling could offset warming equal to approximately 15 years of current global CO2 emissions. On the other hand, mitigation of other SLCFs (e.g., SO2) leads to warming. If SLCFs are mitigated heavily, we find a net warming of about 0.1 ∘C, but when uncertainties are included a slight cooling is also possible. In the climate optimal scenario, the largest contributions to cooling come from the energy, domestic, waste, and transportation sectors. In the maximum technically feasible mitigation scenario, emission changes from the industry, energy, and shipping sectors will cause warming. Some measures, such as those in the agriculture waste burning, domestic, transport, and industry sectors, have large impacts on the Arctic, especially by cutting BC emissions in winter in areas near the Arctic.
Changes in anthropogenic aerosol emissions have strongly contributed to global and regional trends in temperature, precipitation, and other climate characteristics and have been one of the dominant ...drivers of decadal trends in Asian and African precipitation. These and other influences on regional climate from changes in aerosol emissions are expected to continue and potentially strengthen in the coming decades. However, a combination of large uncertainties in emission pathways, radiative forcing, and the dynamical response to forcing makes anthropogenic aerosol a key factor in the spread of near-term climate projections, particularly on regional scales, and therefore an important one to constrain. For example, in terms of future emission pathways, the uncertainty in future global aerosol and precursor gas emissions by 2050 is as large as the total increase in emissions since 1850. In terms of aerosol effective radiative forcing, which remains the largest source of uncertainty in future climate change projections, CMIP6 models span a factor of 5, from −0.3 to −1.5 W m−2. Both of these sources of uncertainty are exacerbated on regional scales.
The Regional Aerosol Model Intercomparison Project (RAMIP) will deliver experiments designed to quantify the role of regional aerosol emissions changes in near-term projections. This is unlike any prior MIP, where the focus has been on changes in global emissions and/or very idealised aerosol experiments. Perturbing regional emissions makes RAMIP novel from a scientific standpoint and links the intended analyses more directly to mitigation and adaptation policy issues. From a science perspective, there is limited information on how realistic regional aerosol emissions impact local as well as remote climate conditions. Here, RAMIP will enable an evaluation of the full range of potential influences of realistic and regionally varied aerosol emission changes on near-future climate. From the policy perspective, RAMIP addresses the burning question of how local and remote decisions affecting emissions of aerosols influence climate change in any given region. Here, RAMIP will provide the information needed to make direct links between regional climate policies and regional climate change.
RAMIP experiments are designed to explore sensitivities to aerosol type and location and provide improved constraints on uncertainties driven by aerosol radiative forcing and the dynamical response to aerosol changes. The core experiments will assess the effects of differences in future global and regional (Africa and the Middle East, East Asia, North America and Europe, and South Asia) aerosol emission trajectories through 2051, while optional experiments will test the nonlinear effects of varying emission locations and aerosol types along this future trajectory. All experiments are based on the shared socioeconomic pathways and are intended to be performed with 6th Climate Model Intercomparison Project (CMIP6) generation models, initialised from the CMIP6 historical experiments, to facilitate comparisons with existing projections. Requested outputs will enable the analysis of the role of aerosol in near-future changes in, for example, temperature and precipitation means and extremes, storms, and air quality.
This study focuses on implications of differences between recent global emissions inventories for simulated trends in anthropogenic aerosol abundances and radiative forcing (RF) over the 1990–2019 ...period. We use the ECLIPSE version 6 (ECLv6) and CEDS year 2021 release (CEDS21) as input to the chemical transport model OsloCTM3 and compare the resulting aerosol evolution to corresponding results derived with the first CEDS release, as well as to observed trends in regional and global aerosol optical depth (AOD). Using CEDS21 and ECLv6 results in a 3 % and 6 % lower global mean AOD compared to CEDS in 2014, primarily driven by differences over China and India, where the area average AOD is up to 30 % lower. These differences are considerably larger than the satellite-derived interannual variability in AOD. A negative linear trend over 2005–2017 in global AOD following changes in anthropogenic emissions is found with all three inventories but is markedly stronger with CEDS21 and ECLv6. Furthermore, we confirm that the model better captures the sign and strength of the observed AOD trend over China with CEDS21 and ECLv6 compared to using CEDS, while the opposite is the case for South Asia. We estimate a net global mean aerosol-induced RF in 2014 relative to 1990 of 0.08 W m−2 for CEDS21 and 0.12 W m−2 for ECLv6, compared to 0.03 W m−2 with CEDS. Using CEDS21, we also estimate the RF in 2019 relative to 1990 to be 0.10 W m−2, reflecting the continuing decreasing trend in aerosol loads post-2014. Our results facilitate more rigorous comparison between existing and upcoming studies of climate and health effects of aerosols using different emission inventories.
Measurements of black carbon (BC) aerosol mass concentration in remote air are sparse, leading to poorly constrained regions that models struggle to represent. Here we present a new data set of BC ...concentration over the remote Pacific and Atlantic basins from 80 N to 65°S latitude that was obtained as part of NASA's Atmospheric Tomography campaign in July/August 2016. More than 100 vertical profiles, extending from ~0.2 to 13 km altitude above mean sea level, reveal sharp contrasts in loadings between the two basins. Over the Pacific, we found average BC concentration vertical profiles to be largely consistent with seasonally matched data obtained in 2011. Substantially higher loads were observed over the Atlantic in the low to middle troposphere than in the Pacific, likely due to strong regional sources and reduced convective removal in the tropics in this basin. Atlantic and Pacific BC concentrations converge in the upper troposphere and lower stratosphere, reflecting similar high‐altitude background concentrations. Comparison of the Atlantic data to the Aerosol Comparisons between Observations and Models suite of models (Phase II) reinforces previous speculation about the ensemble in the remote by quantifying an upper‐troposphere model‐high‐bias of as much as two orders of magnitude over wide latitude bands. However, these direct BC measurements reveal Aerosol Comparisons between Observations and Models ensemble underestimation of biomass burning BC in the outflow of continental Africa by nearly a factor of 5. This high‐BC loading region likely dominates BC's direct radiative effect over remote areas of the Pacific and Atlantic basins during the month of August.
Key Points
Black carbon loadings over the remote Atlantic are generally comparable to those over the Pacific, except at low-altitude near the equator
AeroCom's model‐ensemble average overestimates loadings, except in the lower troposphere of the equatorial Atlantic region
The direct radiative effect of BC over the remote Pacific and Atlantic in August is likely dominated by African biomass burning outflow
Black carbon aerosols (BC) influence precipitation through a range of processes. The climate response to the presence of BC is however highly dependent on its vertical distribution. Here, we analyze ...the changes in the energy budget and precipitation impacts of adding a layer of BC at a range of altitudes in two independent global climate models. The models are run with atmosphere‐only and slab ocean model setup to analyze both fast and slow responses, respectively. Globally, precipitation changes are tightly coupled to the energy budget. We decompose the precipitation change into contributions from absorption of solar radiation, atmospheric longwave radiative cooling, and sensible heat flux at the surface. We find that for atmosphere‐only simulations, BC rapidly suppress precipitation, independent of altitude, mainly because of strong atmospheric absorption. This reduction is offset by increased atmospheric radiative longwave cooling and reduced sensible heat flux at the surface, but not of sufficient magnitude to prevent reduced precipitation. On longer timescales, when the surface temperature is allowed to respond, we find that the precipitation increase associated with surface warming can compensate for the initial reduction, particularly for BC in the lower atmosphere. Even though the underlying processes are strikingly similar in the two models, the resulting change in precipitation and temperature by BC differ quite substantially.
We compare six methods of estimating effective radiative forcing (ERF) using a set of atmosphere‐ocean general circulation models. This is the first multiforcing agent, multimodel evaluation of ERF ...values calculated using different methods. We demonstrate that previously reported apparent consistency between the ERF values derived from fixed sea surface temperature simulations and linear regression holds for most climate forcings, excluding black carbon (BC). When land adjustment is accounted for, however, the fixed sea surface temperature ERF values are generally 10–30% larger than ERFs derived using linear regression across all forcing agents, with a much larger (~70–100%) discrepancy for BC. Except for BC, this difference can be largely reduced by either using radiative kernel techniques or by exponential regression. Responses of clouds and their effects on shortwave radiation show the strongest variability in all experiments, limiting the application of regression‐based ERF in small forcing simulations.
Plain Language Summary
Climate drivers such as greenhouse gases and aerosols influence the Earth's climate by perturbing the Earth's energy budget at the top of the atmosphere, which is referred to as effective radiative forcing (ERF) when the atmospheric response is included in the calculation. ERF plays a crucial role in understanding the climate response to these drivers and predicting long‐term climate change. Previously, ERFs have been estimated for greenhouse gases using two techniques that generally lead to similar values. Here we show that such consistency holds for most climate drivers. ERF values estimated from different methods may differ by 10–50%, and this difference may reach 70–100% for black carbon. Regression techniques do not work well in some models when imposed forcings are relatively small.
Key Points
ERF estimated using fixed SST simulations and linear regression are fairly consistent for most climate forcings
Multimodel mean ERF values vary by 10–50% with different methods, and this difference may reach 70–100% for black carbon
Internal variability limits the application of linear regression technique in small‐forcing experiments
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