dc.contributor.author | Reddington, CL | |
dc.contributor.author | Carslaw, KS | |
dc.contributor.author | Stier, P | |
dc.contributor.author | Schutgens, N | |
dc.contributor.author | Coe, H | |
dc.contributor.author | Liu, D | |
dc.contributor.author | Allan, J | |
dc.contributor.author | Browse, J | |
dc.contributor.author | Pringle, KJ | |
dc.contributor.author | Lee, LA | |
dc.contributor.author | Yoshioka, M | |
dc.contributor.author | Johnson, JS | |
dc.contributor.author | Regayre, LA | |
dc.contributor.author | Spracklen, DV | |
dc.contributor.author | Mann, GW | |
dc.contributor.author | Clarke, A | |
dc.contributor.author | Hermann, M | |
dc.contributor.author | Henning, S | |
dc.contributor.author | Wex, H | |
dc.contributor.author | Kristensen, TB | |
dc.contributor.author | Leaitch, WR | |
dc.contributor.author | Pöschl, U | |
dc.contributor.author | Rose, D | |
dc.contributor.author | Andreae, MO | |
dc.contributor.author | Schmale, J | |
dc.contributor.author | Kondo, Y | |
dc.contributor.author | Oshima, N | |
dc.contributor.author | Schwarz, JP | |
dc.contributor.author | Nenes, A | |
dc.contributor.author | Anderson, B | |
dc.contributor.author | Roberts, GC | |
dc.contributor.author | Snider, JR | |
dc.contributor.author | Leck, C | |
dc.contributor.author | Quinn, PK | |
dc.contributor.author | Chi, X | |
dc.contributor.author | Ding, A | |
dc.contributor.author | Jimenez, JL | |
dc.contributor.author | Zhang, Q | |
dc.date.accessioned | 2018-07-31T14:53:16Z | |
dc.date.issued | 2017-10-09 | |
dc.description.abstract | The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements. | en_GB |
dc.description.sponsorship | GASSP was funded by the Natural Environment Research Council (NERC) under Grants NE/J024252/1, NE/J022624/1, and NE/J023515/1; ACID-PRUF under Grants NE/I020059/1 and NE/I020148/1; the European Union BACCHUS project under Grant 603445-BACCHUS; ACTRIS under Grants 262254 and 654109; and by the UK–China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. We made use of the N8 HPC facility funded from the N8 consortium and an Engineering and Physical Sciences Research Council Grant to use ARCHER (EP/K000225/1) and the JASMIN facility (www.jasmin.ac.uk/) via the Centre for Environmental Data Analysis funded by NERC and the UK Space Agency and delivered by the Science and Technology Facilities Council. We acknowledge the following additional funding: the Royal Society Wolfson Merit Award (Carslaw); a doctoral training grant from the Natural Environment Research Council and a CASE studentship with the Met Office Hadley Centre (Regayre); the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement FP7-280025 (Stier); the Department of Energy under DE-SC0007178 (Zhang); the U.S. National Science Foundation under ATM-745986 (Snider); the NOAA Global Change Program (Nenes); NASA Global Tropospheric Experiment Program, the NASA Tropospheric Composition Program, the NASA Radiation Sciences Program, and the NASA Earth Venture Suborbital Project (Anderson); the NOAA Climate Program Office (Quinn); NSF Atmospheric Chemistry Program, the NASA Global Tropospheric Experiment, and NASA Earth Science Project Office (Clarke); German Federal Ministry of Education and Research (BMBF) CLOUD12 project Grant 01LK1222B (Kristensen); Swedish Research Council (VR), the Knut and Alice Wallenberg Foundation and the Swedish Polar Research Secretariat (SPRS) for access to the icebreaker Oden and logistical support (Leck); the Department of Energy (DE-SC0007178) and the Max Planck Society (Andreae, Poeschl); the global environment research fund of the Ministry of the Environment in Japan (2-1403), the Arctic Challenge for Sustainability (ArCS) project of the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) in Japan, and the Japan Society for the Promotion of Science (JSPS) KAKENHI (Grants JP16H01770, JP26701004, and JP26241003) (Kondo, Oshima); Lufthansa for enabling CARIBIC and the German Federal Ministry of Education and Research (BMBF) for financing the CARIBIC instruments operation as part of the Joint Project IAGOS-D (Hermann); the Collaborative Innovation Center of Climate Change supported by the Jiangsu provincial government and the JirLATEST supported by the Ministry of Education, China (Ding and Chi); the Max Planck Institute for Chemistry, Mainz, Germany (Schmale); the NOAA Atmospheric Composition and Climate Program, the NASA Radiation Sciences Program, and the NASA Upper Atmosphere Research Program supporting the NOAA SP2 BC data acquisition and analysis (Schwarz); DOE (BER/ASR) DE-SC0016559 and EPA STAR 83587701-0 (the EPA has not reviewed this manuscript and no endorsement should be inferred) (Jimenez); and Environment and Climate Change Canada (Leaitch). | en_GB |
dc.identifier.citation | Vol. 98, pp. 1857 - 1877 | en_GB |
dc.identifier.doi | 10.1175/BAMS-D-15-00317.1 | |
dc.identifier.uri | http://hdl.handle.net/10871/33610 | |
dc.language.iso | en | en_GB |
dc.publisher | American Meteorological Society | en_GB |
dc.rights | © 2018 The Author(s). Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. | en_GB |
dc.subject | model uncertainty | en_GB |
dc.subject | chemical measurements | en_GB |
dc.subject | microphysical measurements | en_GB |
dc.subject | in situ aerosol | en_GB |
dc.title | The global aerosol synthesis and science project (GASSP): Measurements and modeling to reduce uncertainty | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2018-07-31T14:53:16Z | |
dc.identifier.issn | 0003-0007 | |
dc.description | This is the final version of the article. Available from American Meteorological Society via the DOI in this record. | en_GB |
dc.identifier.journal | Bulletin of the American Meteorological Society | en_GB |