60 results found
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
Kasoar M, Shawki D, Voulgarakis A, 2018, Similar spatial patterns of global climate response to aerosols from different regions, npj Climate and Atmospheric Science, Vol: 1
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
Myhre G, Kramer RJ, Smith CJ, et al., 2018, Quantifying the Importance of Rapid Adjustments for Global Precipitation Changes, GEOPHYSICAL RESEARCH LETTERS, Vol: 45, Pages: 11399-11405, ISSN: 0094-8276
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-ATMOSPHERES, Vol: 123, Pages: 11585-11601, ISSN: 2169-897X
Nowack P, 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
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
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
Liu L, Shawki D, Voulgarakis A, et al., 2018, A PDRMIP Multimodel Study on the Impacts of Regional Aerosol Forcings on Global and Regional Precipitation, JOURNAL OF CLIMATE, Vol: 31, Pages: 4429-4447, ISSN: 0894-8755
Myhre G, Samset BH, Hodnebrog O, et al., 2018, Sensible heat has significantly affected the global hydrological cycle over the historical period, NATURE COMMUNICATIONS, Vol: 9, ISSN: 2041-1723
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.
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
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
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
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
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.
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, Pages: 40-52, ISSN: 0048-9697
Mangeon S, 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, ISSN: 1991-959X
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: 1680-7316
Mangeon S, Field R, Fromm M, et al., 2016, Satellite versus ground-based estimates of burned area: A comparison between MODIS based burned area and fire agency reports over North America in 2007, ANTHROPOCENE REVIEW, Vol: 3, Pages: 76-92, ISSN: 2053-0196
© 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.
Field RD, Luo M, Fromm M, et al., 2016, Simulating the Black Saturday 2009 smoke plume with an interactive composition-climate model: Sensitivity to emissions amount, timing, and injection height, JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, Vol: 121, Pages: 4296-4316, ISSN: 2169-897X
Samset BH, Myhre G, Forster PM, et al., 2016, Fast and slow precipitation responses to individual climate forcers: A PDRMIP multimodel study, GEOPHYSICAL RESEARCH LETTERS, Vol: 43, Pages: 2782-2791, ISSN: 0094-8276
Field RD, Luo M, Kim D, et al., 2015, Sensitivity of simulated tropospheric CO to subgrid physics parameterization: A case study of Indonesian biomass burning emissions in 2006, JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, Vol: 120, ISSN: 2169-897X
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