64 results found
Stjern CW, Lund MT, Samset BH, et al., 2019, Arctic Amplification Response to Individual Climate Drivers, JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, Vol: 124, Pages: 6698-6717, ISSN: 2169-897X
Tang T, Shindell D, Faluvegi G, et al., 2019, Comparison of effective radiative forcing calculations using multiple methods, drivers, and models, Journal of Geophysical Research: Atmospheres, Vol: 124, Pages: 4382-4394, ISSN: 2169-897X
American Geophysical Union. All Rights Reserved. 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.
Nowack P, Ong QYE, Braesicke P, et al., Machine learning parameterizations for ozone in climate sensitivity simulations, Kurzfassungen der Meteorologentagung DACH
Richardson TB, Forster PM, Andrews T, et al., 2018, Drivers of Precipitation Change: An Energetic Understanding, Journal of Climate, Vol: 31, Pages: 9641-9657, ISSN: 0894-8755
The response of the hydrological cycle to climate forcings can be understood within the atmospheric energy budget framework. In this study precipitation and energy budget responses to five forcing agents are analyzed using 10 climate models from the Precipitation Driver Response Model Intercomparison Project (PDRMIP). Precipitation changes are split into a forcing-dependent fast response and a temperature-driven hydrological sensitivity. Globally, when normalized by top-of-atmosphere (TOA) forcing, fast precipitation changes are most sensitive to strongly absorbing drivers (CO2, black carbon). However, over land fast precipitation changes are most sensitive to weakly absorbing drivers (sulfate, solar) and are linked to rapid circulation changes. Despite this, land-mean fast responses to CO2 and black carbon exhibit more intermodel spread. Globally, the hydrological sensitivity is consistent across forcings, mainly associated with increased longwave cooling, which is highly correlated with intermodel spread. The land-mean hydrological sensitivity is weaker, consistent with limited moisture availability. The PDRMIP results are used to construct a simple model for land-mean and sea-mean precipitation change based on sea surface temperature change and TOA forcing. The model matches well with CMIP5 ensemble mean historical and future projections, and is used to understand the contributions of different drivers. During the twentieth century, temperature-driven intensification of land-mean precipitation has been masked by fast precipitation responses to anthropogenic sulfate and volcanic forcing, consistent with the small observed trend. However, as projected sulfate forcing decreases, and warming continues, land-mean precipitation is expected to increase more rapidly, and may become clearly observable by the mid-twenty-first century.
Smith CJ, Kramer RJ, Myhre G, et al., 2018, Understanding rapid adjustments to diverse forcing agents, Geophysical Research Letters, Vol: 45, Pages: 12023-12031, ISSN: 0094-8276
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.
Myhre G, Kramer RJ, Smith CJ, et al., 2018, Quantifying the importance of rapid adjustments for global precipitation changes, Geophysical Research Letters, Vol: 20, Pages: 11399-11405, ISSN: 0094-8276
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.
Shawki D, Voulgarakis A, Chakraborty A, et al., 2018, The South Asian monsoon response to remote aerosols: global and regional mechanisms, Journal of Geophysical Research, Vol: 123, Pages: 11585-11601, ISSN: 0148-0227
The South Asian summer monsoon has been suggested to be influenced by atmospheric aerosols, and this influence can be the result of either local or remote emissions. We have used the Hadley Centre Global Environment Model Version 3 (HadGEM3) coupled atmosphere‐ocean climate model to investigate for the first time the centennial‐scale South Asian precipitation response to emissions of sulfur dioxide (SO2), the dominant anthropogenic precursor of sulfate aerosol, from different midlatitude regions. Despite the localized nature of the regional heating that results from removing SO2 emissions, all experiments featured a similar large‐scale precipitation response over South Asia, driven by ocean‐modulated changes in the net cross‐equatorial heat transport and an opposing cross‐equatorial northward moisture transport. The effects are linearly additive, with the sum of the responses from the experiments where SO2 is removed from the United States, Europe, and East Asia resembling the response seen in the experiment where emissions are removed from the northern midlatitudes as a whole, but with East Asia being the largest contributor, even per unit of emission or top‐of‐atmosphere radiative forcing. This stems from the fact that East Asian emissions can more easily influence regional land‐sea thermal contrasts and sea level pressure differences that drive the monsoon circulation, compared to emissions from more remote regions. Our results suggest that radiative effects of remote pollution should not be neglected when examining changes in South Asian climate and that and it is important to examine such effects in coupled ocean‐atmosphere modeling frameworks.
Nowack PJ, Braesicke P, Haigh J, et al., 2018, Using machine learning to build temperature-based ozone parameterizations for climate sensitivity simulations, Environmental Research Letters, Vol: 13, ISSN: 1748-9326
A number of studies have demonstrated the importance of ozone in climate change simulations, for example concerning global warming projections and atmospheric dynamics. However, fully interactive atmospheric chemistry schemes needed for calculating changes in ozone are computationally expensive. Climate modelers therefore often use climatological ozone fields, which are typically neither consistent with the actual climate state simulated by each model nor with the specific climate change scenario. This limitation applies in particular to standard modeling experiments such as preindustrial control or abrupt 4xCO2 climate sensitivity simulations. Here we suggest a novel method using a simple linear machine learning regression algorithm to predict ozone distributions for preindustrial and abrupt 4xCO2 simulations. Using the atmospheric temperature field as the only input, the regression reliably predicts three-dimensional ozone distributions at monthly to daily time intervals. In particular, the representation of stratospheric ozone variability is much improved compared with a fixed climatology, which is important for interactions with dynamical phenomena such as the polar vortices and the Quasi-Biennial Oscillation. Our method requires training data covering only a fraction of the usual length of simulations and thus promises to be an important stepping stone towards a range of new computationally efficient methods to consider ozone changes in long climate simulations. We highlight key development steps to further improve and extend the scope of machine learning-based ozone parameterizations.
Ryan E, Wild O, Voulgarakis A, et al., 2018, Fast sensitivity analysis methods for computationally expensive models with multi-dimensional output, GEOSCIENTIFIC MODEL DEVELOPMENT, Vol: 11, Pages: 3131-3146, ISSN: 1991-959X
Global sensitivity analysis (GSA) is a powerful approach in identifying which inputs or parameters most affect a model's output. This determines which inputs to include when performing model calibration or uncertainty analysis. GSA allows quantification of the sensitivity index (SI) of a particular input – the percentage of the total variability in the output attributed to the changes in that input – by averaging over the other inputs rather than fixing them at specific values. Traditional methods of computing the SIs using the Sobol and extended Fourier Amplitude Sensitivity Test (eFAST) methods involve running a model thousands of times, but this may not be feasible for computationally expensive Earth system models. GSA methods that use a statistical emulator in place of the expensive model are popular, as they require far fewer model runs. We performed an eight-input GSA, using the Sobol and eFAST methods, on two computationally expensive atmospheric chemical transport models using emulators that were trained with 80 runs of the models. We considered two methods to further reduce the computational cost of GSA: (1) a dimension reduction approach and (2) an emulator-free approach. When the output of a model is multi-dimensional, it is common practice to build a separate emulator for each dimension of the output space. Here, we used principal component analysis (PCA) to reduce the output dimension, built an emulator for each of the transformed outputs, and then computed SIs of the reconstructed output using the Sobol method. We considered the global distribution of the annual column mean lifetime of atmospheric methane, which requires ∼ 2000 emulators without PCA but only 5–40 emulators with PCA. We also applied an emulator-free method using a generalised additive model (GAM) to estimate the SIs using only the training runs. Compared to the emulator-only methods, the emulator–PCA and GAM methods accurately estimated the SIs
Kasoar MR, Shawki D, Voulgarakis A, 2018, Similar spatial patterns of global climate response to aerosols from different regions, npj Climate and Atmospheric Science, Vol: 12, ISSN: 2397-3722
Anthropogenic aerosol forcing is spatially heterogeneous, mostly localised around industrialised regions like North America, Europe, East and South Asia. Emission reductions in each of these regions will force the climate in different locations, which could have diverse impacts on regional and global climate. Here, we show that removing sulphur dioxide (SO2) emissions from any of these northern-hemisphere regions in a global composition-climate model results in significant warming across the hemisphere, regardless of the emission region. Although the temperature response to these regionally localised forcings varies considerably in magnitude depending on the emission region, it shows a preferred spatial pattern independent of the location of the forcing. Using empirical orthogonal function analysis, we show that the structure of the response is tied to existing modes of internal climate variability in the model. This has implications for assessing impacts of emission reduction policies, and our understanding of how climate responds to heterogeneous forcings.
Tang T, Shindell D, Samset BH, et al., 2018, Dynamical response of Mediterranean precipitation to greenhouse gases and aerosols, ATMOSPHERIC CHEMISTRY AND PHYSICS, Vol: 18, Pages: 8439-8452, ISSN: 1680-7316
Atmospheric aerosols and greenhouse gases affect cloud properties, radiative balance and, thus, the hydrological cycle. Observations show that precipitation has decreased in the Mediterranean since the beginning of the 20th century, and many studies have investigated possible mechanisms. So far, however, the effects of aerosol forcing on Mediterranean precipitation remain largely unknown. Here we compare the modeled dynamical response of Mediterranean precipitation to individual forcing agents in a set of global climate models (GCMs). Our analyses show that both greenhouse gases and aerosols can cause drying in the Mediterranean and that precipitation is more sensitive to black carbon (BC) forcing than to well-mixed greenhouse gases (WMGHGs) or sulfate aerosol. In addition to local heating, BC appears to reduce precipitation by causing an enhanced positive sea level pressure (SLP) pattern similar to the North Atlantic Oscillation–Arctic Oscillation, characterized by higher SLP at midlatitudes and lower SLP at high latitudes. WMGHGs cause a similar SLP change, and both are associated with a northward diversion of the jet stream and storm tracks, reducing precipitation in the Mediterranean while increasing precipitation in northern Europe. Though the applied forcings were much larger, if forcings are scaled to those of the historical period of 1901–2010, roughly one-third (31±17%) of the precipitation decrease would be attributable to global BC forcing with the remainder largely attributable to WMGHGs, whereas global scattering sulfate aerosols would have negligible impacts. Aerosol–cloud interactions appear to have minimal impacts on Mediterranean precipitation in these models, at least in part because many simulations did not fully include such processes; these merit further study. The findings from this study suggest that future BC and WMGHG emissions may significantly affect regional water resources, agricultural practices, ecosystems and
Liu L, Shawki D, Voulgarakis A, et al., 2018, A PDRMIP multi-model study on the impacts of regional aerosol forcings on global and regional precipitation, Journal of Climate, Vol: 31, Pages: 4429-4447, ISSN: 0894-8755
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.
Myhre G, Samset BH, Hodnebrog Ø, et al., 2018, Sensible heat has significantly affected the global hydrological cycle over the historical period, Nature Communications, Vol: 9, ISSN: 2041-1723
Globally, latent heating associated with a change in precipitation is balanced by changes to atmospheric radiative cooling and sensible heat fluxes. Both components can be altered by climate forcing mechanisms and through climate feedbacks, but the impacts of climate forcing and feedbacks on sensible heat fluxes have received much less attention. Here we show, using a range of climate modelling results, that changes in sensible heat are the dominant contributor to the present global-mean precipitation change since preindustrial time, because the radiative impact of forcings and feedbacks approximately compensate. The model results show a dissimilar influence on sensible heat and precipitation from various drivers of climate change. Due to its strong atmospheric absorption, black carbon is found to influence the sensible heat very differently compared to other aerosols and greenhouse gases. Our results indicate that this is likely caused by differences in the impact on the lower tropospheric stability.
Richardson TB, Forster PM, Andrews T, et al., 2018, Carbon Dioxide Physiological Forcing Dominates Projected Eastern Amazonian Drying, Geophysical Research Letters, Vol: 45, Pages: 2815-2825, ISSN: 0094-8276
Future projections of east Amazonian precipitation indicate drying, but they are uncertain and poorly understood. In this study we analyze the Amazonian precipitation response to individual atmospheric forcings using a number of global climate models. Black carbon is found to drive reduced precipitation over the Amazon due to temperature-driven circulation changes, but the magnitude is uncertain. CO 2 drives reductions in precipitation concentrated in the east, mainly due to a robustly negative, but highly variable in magnitude, fast response. We find that the physiological effect of CO 2 on plant stomata is the dominant driver of the fast response due to reduced latent heating and also contributes to the large model spread. Using a simple model, we show that CO 2 physiological effects dominate future multimodel mean precipitation projections over the Amazon. However, in individual models temperature-driven changes can be large, but due to little agreement, they largely cancel out in the model mean.
Samset BH, Myhre G, Forster PM, et al., 2018, Weak hydrological sensitivity to temperature change over land, independent of climate forcing, npj Climate and Atmospheric Science, Vol: 1, ISSN: 2397-3722
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.
Stjern CW, Samset BH, Myhre G, et al., 2017, Rapid Adjustments Cause Weak Surface Temperature Response to Increased Black Carbon Concentrations, Journal of Geophysical Research: Atmospheres, Vol: 122, Pages: 462-481, ISSN: 2169-897X
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 nine global coupled-climate models, producing a model median effective radiative forcing of 0.82 (ranging from 0.41 to 2.91) W m−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 W m−2 based on five of the models) is countered by negative rapid adjustments (−0.64 W m−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 median global warming of 0.47 K per W m−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.
Shawki D, Field RD, Tippett MK, et al., 2017, Long-Lead Prediction of the 2015 Fire and Haze Episode in Indonesia, Geophysical Research Letters, Vol: 44, Pages: 9996-10005, ISSN: 0094-8276
We conducted a case study of National Centers for Environmental Prediction Climate Forecast System version 2 seasonal model forecast performance over Indonesia in predicting the dry conditions in 2015 that led to severe fire, in comparison to the non-El Niño dry season conditions of 2016. Forecasts of the Drought Code (DC) component of Indonesia's Fire Danger Rating System were examined across the entire equatorial Asia region and for the primary burning regions within it. Our results show that early warning lead times of high observed DC in September and October 2015 varied considerably for different regions. High DC over Southern Kalimantan and Southern New Guinea were predicted with 180 day lead times, whereas Southern Sumatra had lead times of up to only 60 days, which we attribute to the absence in the forecasts of an eastward decrease in Indian Ocean sea surface temperatures. This case study provides the starting point for longer-term evaluation of seasonal fire danger rating forecasts over Indonesia.
Saunois M, Bousquet P, Poulter B, et al., 2017, Variability and quasi-decadal changes in the methane budget over the period 2000-2012, Atmospheric Chemistry and Physics, Vol: 17, Pages: 11135-11161, ISSN: 1680-7316
Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric in
Myhre G, Forster PM, Samset BH, et al., 2017, PDRMIP A Precipitation Driver and Response Model Intercomparison Project-Protocol and Preliminary Results, Bulletin of the American Meteorological Society, Vol: 98, Pages: 1185-1198, ISSN: 0003-0007
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 intermodel 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 better quantifications are needed to improve precipitation predictions. Here, the authors 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 understanding of the causes of the present diversity in future climate projections.
Rabin SS, Melton JR, Lasslop G, et al., 2017, The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols with detailed model descriptions, GEOSCIENTIFIC MODEL DEVELOPMENT, Vol: 10, Pages: 1175-1197, ISSN: 1991-959X
The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over 2 decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. In this paper, we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. We have also created supplementary tables that describe, in thorough mathematical detail, the structure of each model.
Wu Y, Han Y, Voulgarakis A, et al., 2017, An agricultural biomass burning episode in eastern China: transport, optical properties, and impacts on regional air quality, Journal of Geophysical Research: Atmospheres, Vol: 122, Pages: 2304-2324, ISSN: 2169-897X
Agricultural biomass burning (ABB) has been of particular concern due to its influence on air quality and atmospheric radiation, as it produces large amounts of gaseous and aerosol emissions. This paper presents an integrated observation of a significant ABB episode in Nanjing, China, during early June 2011, using combined ground-based and satellite sensors (Moderate Resolution Imaging Spectroradiometer, Atmospheric Infrared Sounder, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), and Ozone Monitoring Instrument products). The time-height distribution, optical properties, sources and transport of smoke, and its impacts on air quality are investigated. Lidar profiles indicate that the smoke aerosols are confined to the planetary boundary layer (PBL) and have a depolarization ratio of less than 0.08. The aerosol optical depths increase from 0.5 to 3.0 at 500 nm, while the extinction-related Angstrom exponent increases from 1.1 to 1.6 at the wavelength pair of 440–870 nm. The single-scattering albedo becomes lower at 670–1020 nm following the ABB intrusion and particularly shows a decreasing tendency between wavelengths of 440 to 1020 nm. The absorption Angstrom exponent (0.7) is smaller than 1.0, which may indicate the aged smoke particles mixed or coated with the urban aerosols. Surface particular matter PM10 and PM2.5 show a dramatic increase, reaching hourly mean of 800 µg/m3 and 485 µg/m3, respectively, which results in a heavy air pollution event. The stagnant and high-moisture weather provides favorable conditions for the aerosols to accumulate near the surface. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) also illustrate that the large-scale aerosols are primarily present in the PBL and transported to the ocean, but some dense smoke plumes are misclassified as cloud or polluted dust. By comparing with the observations, we found that the
Badia A, Jorba O, Voulgarakis A, et al., 2017, Description and evaluation of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH) version 1.0: gas-phase chemistry at global scale, Geoscientific Model Development, Vol: 10, Pages: 609-638, ISSN: 1991-959X
This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH), formerly known as NMMB/BSC-CTM, that can be run on both regional and global domains. Here, we provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT). We also include an extensive discussion of our results in comparison to other state-of-the-art models. We note that in this study, we omitted aerosol processes and some natural emissions (lightning and volcano emissions).The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3–0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere.Nitrogen species are well represented in almost all locations, particularly NO2 in Europe (root mean square error – RMSE – below 5 ppb). The modeled vertical distributions of NOx and HNO3 are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO2 columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NOx from March to August, probably due to an underestimation of NOx emissions in the region. Overall, the comparison of the modeled CO and NO2 with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability).The
Voulgarakis A, Field R, Fromm M, 2017, Fire impacts on high-altitude atmospheric com-position, 13th International Conference on Meteorology, Climatology and Atmospheric Physics (COMECAP), Publisher: Springer International Publishing, Pages: 1231-1237, ISSN: 2194-5217
Fire emissions can strongly impact atmospheric abundances of trace gases and aerosols, in ways that vary strongly in time and space. There is emerging understanding that fires do not only influence areas in the lower troposphere, where the land-surface is in contact with the atmosphere, but can also have significant effects on the upper troposphere and even the stratosphere. Here, I will present example results from our ongoing global modelling studies investigating such effects. First, an overview of recent results will be presented, i.e. from (a) a case study on how high-altitude injections can influence stratospheric composition, and (b) a study that demonstrated how satellite observations can be used to understand the transport of fire pollution into the upper troposphere/lower stratosphere (UTLS), and how such measurements can be used to evaluate convective processes in composition-climate models. Subsequently, the role of typical low-injection fires in driving the interannual variability of UTLS composition will be discussed based on results from recent global model experiments, with a focus on impacts on CO and ozone. The findings show a major role of fire emissions in driving UTLS CO and a minor role in driving UTLS ozone interannual variability.
The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003–2012 decade, global methane emissions are estimated by top-down inversions at 558 Tg CH4 yr−1, range 540–568. About 60 % of global emissions are anthropogenic (range 50–65 %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher
Mangeon T, Voulgarakis A, Gilham R, et al., 2016, INFERNO: a fire and emissions scheme for the UK Met Office's Unified Model, Geoscientific Model Development, Vol: 9, Pages: 2685-2700, ISSN: 1991-9603
Warm and dry climatological conditions favour the occurrence of forest fires. These fires then become a significant emission source to the atmosphere. Despite this global importance, fires are a local phenomenon and are difficult to represent in a large-scale Earth System Model (ESM). To address this, the INteractive Fire and Emission algoRithm for Natural envirOnments (INFERNO) was developed. INFERNO follows a reduced complexity approach and is intended for decadal to centennial scale climate simulations and assessment models for policy making. Fuel flammability is simulated using temperature, relative humidity, fuel density as well as precipitation and soil moisture. Combining flammability with ignitions and vegetation, burnt area is diagnosed. Emissions of carbon and key species are estimated using the carbon scheme in the JULES land surface model. JULES also possesses fire index diagnostics which we document and compare with our fire scheme. Two meteorology datasets and three ignition modes are used to validate the model. INFERNO is shown to effectively diagnose global fire occurrence (R = 0.66) and emissions (R = 0.59) through an approach appropriate to the complexity of an ESM, although regional biases remain.
Kasoar M, Voulgarakis A, Lamarque J-F, et al., 2016, Regional and global temperature response to anthropogenic SO2 emissions from China in three climate models, Atmospheric Chemistry and Physics, Vol: 16, Pages: 9785-9804, ISSN: 1680-7324
We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against observat
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.
© Author(s) 2016. Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what lessons may be learned from FireMIP.
Myriokefalitakis S, Daskalakis N, Fanourgakis GS, et al., 2016, Ozone and carbon monoxide budgets over the Eastern Mediterranean, Science of the Total Environment, Vol: 563-564, Pages: 40-52, ISSN: 0048-9697
The importance of the long-range transport (LRT) on O3 and CO budgets over the Eastern Mediterranean has been investigated using the state-of-the-art 3-dimensional global chemistry-transport model TM4-ECPL. A 3-D budget analysis has been performed separating the Eastern from the Western basins and the boundary layer (BL) from the free troposphere (FT). The FT of the Eastern Mediterranean is shown to be a strong receptor of polluted air masses from the Western Mediterranean, and the most important source of polluted air masses for the Eastern Mediterranean BL, with about 40% of O3 and of CO in the BL to be transported from the FT aloft. Regional anthropogenic sources are found to have relatively small impact on regional air quality in the area, contributing by about 8% and 18% to surface levels of O3 and CO, respectively. Projections using anthropogenic emissions for the year 2050 but neglecting climate change calculate a surface O3 decrease of about 11% together with a surface CO increase of roughly 10% in the Eastern Mediterranean.
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