4.7 Article

THE GLOBAL AEROSOL SYNTHESIS AND SCIENCE PROJECT (GASSP): Measurements and Modeling to Reduce Uncertainty

Journal

BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
Volume 98, Issue 9, Pages 1857-1877

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/BAMS-D-15-00317.1

Keywords

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Funding

  1. Natural Environment Research Council (NERC) [NE/J024252/1, NE/J022624/1, NE/J023515/1]
  2. ACID-PRUF [NE/I020059/1, NE/I020148/1]
  3. European Union BACCHUS [603445-BACCHUS]
  4. ACTRIS [262254, 654109]
  5. Met Office Climate Science for Service Partnership (CSSP) China
  6. N8 consortium
  7. Engineering and Physical Sciences Research Council [EP/K000225/1]
  8. JASMIN via the Centre for Environmental Data Analysis - NERC
  9. UK Space Agency
  10. Royal Society
  11. Natural Environment Research Council
  12. CASE
  13. Met Office Hadley Centre
  14. European Research Council under the European Union's Seventh Framework Programme/ERC [FP7-280025]
  15. Department of Energy [DE-SC0007178]
  16. U.S. National Science Foundation [ATM-745986]
  17. NOAA
  18. NASA
  19. NOAA Climate Program Office
  20. NSF
  21. NASA Earth Science Project Office
  22. German Federal Ministry of Education and Research (BMBF) CLOUD12 [01LK1222B]
  23. Swedish Research Council (VR)
  24. Knut and Alice Wallenberg Foundation
  25. Swedish Polar Research Secretariat (SPRS)
  26. Max Planck Society
  27. Ministry of the Environment in Japan [2-1403]
  28. Arctic Challenge for Sustainability (ArCS) project of the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) in Japan
  29. Japan Society for the Promotion of Science (JSPS) KAKENHI [JP16H01770, JP26701004, JP26241003]
  30. Lufthansa for enabling CARIBIC
  31. German Federal Ministry of Education and Research (BMBF)
  32. Collaborative Innovation Center of Climate Change - Jiangsu provincial government
  33. JirLATEST - Ministry of Education, China
  34. Max Planck Institute for Chemistry, Mainz, Germany
  35. DOE (BER/ASR) [DE-SC0016559]
  36. EPA STAR [83587701-0]
  37. NASA Global Tropospheric Experiment
  38. Environment and Climate Change Canada
  39. Engineering and Physical Sciences Research Council [EP/K000225/1] Funding Source: researchfish
  40. Natural Environment Research Council [NE/D013690/1, NE/J010073/1, NE/I020148/1, NE/J022624/1, NE/J023515/1] Funding Source: researchfish
  41. EPSRC [EP/K000225/1] Funding Source: UKRI
  42. NERC [NE/I020148/1, NE/J022624/1, NE/J024252/1, NE/D013690/1, NE/J010073/1, NE/J023515/1, NE/F019874/1] Funding Source: UKRI
  43. U.S. Department of Energy (DOE) [DE-SC0007178] Funding Source: U.S. Department of Energy (DOE)
  44. Grants-in-Aid for Scientific Research [26701004, 26241003, 16H01770, 16H01772] Funding Source: KAKEN

Ask authors/readers for more resources

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.

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