G. Faluvegi

Multimodel simulations of carbon monoxide: Comparison with observations and projected near-future changes

We analyze present-day and future carbon monoxide (CO) simulations in 26 state-of-the-art atmospheric chemistry models run to study future air quality and climate change. In comparison with near-global satellite observations from the MOPITT instrument and local surface measurements, the models show large underestimates of Northern Hemisphere (NH) extratropical CO, while typically performing reasonably well elsewhere. The results suggest that year-round emissions, probably from fossil fuel burning in east Asia and seasonal biomass burning emissions in south-central Africa, are greatly underestimated in current inventories such as IIASA and EDGAR3.2. Variability among models is large, likely resulting primarily from intermodel differences in representations and emissions of nonmethane volatile organic compounds (NMVOCs) and in hydrologic cycles, which affect OH and soluble hydrocarbon intermediates. Global mean projections of the 2030 CO response to emissions changes are quite robust. Global mean midtropospheric (500 hPa) CO increases by 12.6 ± 3.5 ppbv (16%) for the high-emissions (A2) scenario, by 1.7 ± 1.8 ppbv (2%) for the midrange (CLE) scenario, and decreases by 8.1 ± 2.3 ppbv (11%) for the low-emissions (MFR) scenario. Projected 2030 climate changes decrease global 500 hPa CO by 1.4 ± 1.4 ppbv. Local changes can be much larger. In response to climate change, substantial effects are seen in the tropics, but intermodel variability is quite large. The regional CO responses to emissions changes are robust across models, however. These range from decreases of 10–20 ppbv over much of the industrialized NH for the CLE scenario to CO increases worldwide and year-round under A2, with the largest changes over central Africa (20–30 ppbv), southern Brazil (20–35 ppbv) and south and east Asia (30–70 ppbv). The trajectory of future emissions thus has the potential to profoundly affect air quality over most of the worlds populated areas.

Climate simulations for 1880–2003 with GISS modelE

We carry out climate simulations for 1880–2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880–2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies include unrealistically weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. Greatest uncertainties in the forcings are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds.

Global Air Quality and Health Co-benefits of Mitigating Near-Term Climate Change through Methane and Black Carbon Emission Controls

Background: Tropospheric ozone and black carbon (BC), a component of fine particulate matter (PM ≤ 2.5 µm in aerodynamic diameter; PM2.5), are associated with premature mortality and they disrupt global and regional climate. Objectives: We examined the air quality and health benefits of 14 specific emission control measures targeting BC and methane, an ozone precursor, that were selected because of their potential to reduce the rate of climate change over the next 20–40 years. Methods: We simulated the impacts of mitigation measures on outdoor concentrations of PM2.5 and ozone using two composition-climate models, and calculated associated changes in premature PM2.5- and ozone-related deaths using epidemiologically derived concentration–response functions. Results: We estimated that, for PM2.5 and ozone, respectively, fully implementing these measures could reduce global population-weighted average surface concentrations by 23–34% and 7–17% and avoid 0.6–4.4 and 0.04–0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits are estimated to occur in Asia. We estimated that BC mitigation measures would achieve approximately 98% of the deaths that would be avoided if all BC and methane mitigation measures were implemented, due to reduced BC and associated reductions of nonmethane ozone precursor and organic carbon emissions as well as stronger mortality relationships for PM2.5 relative to ozone. Although subject to large uncertainty, these estimates and conclusions are not strongly dependent on assumptions for the concentration–response function. Conclusions: In addition to climate benefits, our findings indicate that the methane and BC emission control measures would have substantial co-benefits for air quality and public health worldwide, potentially reversing trends of increasing air pollution concentrations and mortality in Africa and South, West, and Central Asia. These projected benefits are independent of carbon dioxide mitigation measures. Benefits of BC measures are underestimated because we did not account for benefits from reduced indoor exposures and because outdoor exposure estimates were limited by model spatial resolution.

El Niño and health risks from landscape fire emissions in southeast Asia

Emissions from landscape fires affect both climate and air quality1. In this study, we combine satellite-derived fire estimates and atmospheric modeling to quantify health effects from fire emissions in Southeast Asia from 1997 to 2006. This region has large interannual variability in fire activity due to coupling between El Niño-induced droughts and anthropogenic land use change2,3. We show that during strong El Niño years, fires contribute up to 200 μg/m3 and 50 ppb in annual average fine particulate matter (PM2.5) and ozone (O3) surface concentrations near fire sources, respectively. This corresponds to a fire contribution of 200 additional days per year that exceed the World Health Organization (WHO) 50 μg/m3 24-hour PM2.5 interim target (IT-2)4 and an estimated 10,800 (6,800–14,300) person (~2%) annual increase in regional adult cardiovascular mortality. Our results indicate that reducing regional deforestation and degradation fires would improve public health along with widely established benefits from reducing carbon emissions, preserving biodiversity, and maintaining ecosystem services.

The vertical distribution of ozone instantaneous radiative forcing from satellite and chemistry climate models

find total tropospheric IRF biases from −0.4 to + 0.7 W/m 2 over large regions within the tropics and midlatitudes, due to ozone differences over the region in the lower and middle troposphere, enhanced by persistent bias in the upper troposphere‐lower stratospheric region. The zonal mean biases also range from −30 to +50 mW/m 2 for the models. However, the ensemble mean total tropospheric IRF bias is less than 0.2 W/m 2 within the entire troposphere.

Fast and Slow Precipitation Responses to Individual Climate Forcers: A PDRMIP Multimodel Study

Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.

PDRMIP: A Precipitation Driver and Response Model Intercomparison Project—Protocol and Preliminary Results

As the global temperature increases with changing climate, precipitation rates and patterns are affected through a wide range of physical mechanisms. The globally averaged intensity of extreme precipitation also changes more rapidly than the globally averaged precipitation rate. While some aspects of the regional variation in precipitation predicted by climate models appear robust, there is still a large degree of inter-model differences unaccounted for. Individual drivers of climate change initially alter the energy budget of the atmosphere leading to distinct rapid adjustments involving changes in precipitation. Differences in how these rapid adjustment processes manifest themselves within models are likely to explain a large fraction of the present model spread and needs better quantifications to improve precipitation predictions. Here, we introduce the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where a set of idealized experiments designed to understand the role of different climate forcing mechanisms were performed by a large set of climate models. PDRMIP focuses on understanding how precipitation changes relating to rapid adjustments and slower responses to climate forcings are represented across models. Initial results show that rapid adjustments account for large regional differences in hydrological sensitivity across multiple drivers. The PDRMIP results are expected to dramatically improve our understanding of the causes of the present diversity in future climate projections.

Rapid Adjustments Cause Weak Surface Temperature Response to Increased Black Carbon Concentrations

We investigate the climate response to increased concentrations of black carbon (BC), as part of the Precipitation Driver Response Model Intercomparison Project (PDRMIP). A tenfold increase in BC is simulated by 9 global coupled-climate models, producing a model-median effective radiative forcing (ERF) of 0.82 (ranging from 0.41 to 2.91) Wm-2, and a warming of 0.67 (0.16 to 1.66) K globally and 1.24 (0.26 to 4.31) K in the Arctic. A strong positive instantaneous radiative forcing (median of 2.10 Wm-2 based on five of the models) is countered by negative rapid adjustments (-0.64 Wm-2 for the same five models), which dampen the total surface temperature signal. Unlike other drivers of climate change, the response of temperature and cloud profiles to the BC forcing is dominated by rapid adjustments. Low-level cloud amounts increase for all models, while higher-level clouds are diminished. The rapid temperature response is particularly strong above 400 hPa, where increased atmospheric stabilization and reduced cloud cover contrast the response pattern of the other drivers. In conclusion, we find that this substantial increase in BC concentrations does have considerable impacts on important aspects of the climate system. However, some of these effects tend to offset one another, leaving a relatively small global warming of 0.47 K per Wm-2 - about 20 % lower than the response to a doubling of CO2. Translating the tenfold increase in BC to the present-day impact of anthropogenic BC (given the emissions used in this work) would leave a warming of merely 0.07 K.

A PDRMIP multimodel study on the impacts of regional aerosol forcings on global and regional precipitation

Atmospheric aerosols such as sulfate and black carbon (BC) generate inhomogeneous radiative forcing and can affect precipitation in distinct ways compared to greenhouse gases (GHGs). Their regional effects on the atmospheric energy budget and circulation can be important for understanding and predicting global and regional precipitation changes, which act on top of the background GHG-induced hydrological changes. Under the framework of the Precipitation Driver Response Model Inter-comparison Project (PDRMIP), multiple models were used for the first time to simulate the influence of regional (Asian and European) sulfate and BC forcing on global and regional precipitation. The results show that, as in the case of global aerosol forcing, the global fast precipitation response to regional aerosol forcing scales with global atmospheric absorption, and the slow precipitation response scales with global surface temperature response. Asian sulphate aerosols appear to be a stronger driver of global temperature and precipitation change compared to European aerosols, but when the responses are normalised by unit radiative forcing or by aerosol burden change, the picture reverses, with European aerosols being more efficient in driving global change. The global apparent hydrological sensitivities of these regional forcing experiments are again consistent with those for corresponding global aerosol forcings found in the literature. However, the regional responses and regional apparent hydrological sensitivities do not align with the corresponding global values. Through a holistic approach involving analysis of the energy budget combined with exploring changes in atmospheric dynamics, we provide a framework for explaining the global and regional precipitation responses to regional aerosol forcing.

Weak hydrological sensitivity to temperature change over land, independent of climate forcing

We present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from ten climate models, we show how modeled global mean precipitation increases by 2–3% per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature-driven (slow) ocean HS of 3–5%/K, while the slow land HS is only 0–2%/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. We identify a particular need for model investigations and observational constraints on convective precipitation in the Arctic, and large-scale precipitation around the Equator.Climate change: Global warming increases rainfall most over oceansGlobal warming leads to more rain – but little of the change occurs over land. An international team of researchers, led by Bjørn H. Samset at the Norwegian CICERO Center for Climate Research, used ten global climate models to study how precipitation changes when just one factor in the climate system was allowed to change at a time. While models tend to give very different predictions of future rainfall for realistic scenarios, changes due solely to greenhouse gases, aerosols, or the amount of incoming sunlight, give clearer results. Overall, the amount of rain over oceans increases by 4% per degree Celsius, no matter what caused the surface warming. Over land, the increase is only 1–2%. This difference helps explain why observed rainfall changes over land have so far been modest.