Articles | Volume 16, issue 2
https://doi.org/10.5194/acp-16-1065-2016
https://doi.org/10.5194/acp-16-1065-2016
Research article
 | 
29 Jan 2016
Research article |  | 29 Jan 2016

The importance of temporal collocation for the evaluation of aerosol models with observations

N. A. J. Schutgens, D. G. Partridge, and P. Stier

Related authors

Assimilation of POLDER observations to estimate aerosol emissions
Athanasios Tsikerdekis, Otto P. Hasekamp, Nick A. J. Schutgens, and Qirui Zhong
Atmos. Chem. Phys., 23, 9495–9524, https://doi.org/10.5194/acp-23-9495-2023,https://doi.org/10.5194/acp-23-9495-2023, 2023
Short summary
Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation
Marine Bonazzola, Hélène Chepfer, Po-Lun Ma, Johannes Quaas, David M. Winker, Artem Feofilov, and Nick Schutgens
Geosci. Model Dev., 16, 1359–1377, https://doi.org/10.5194/gmd-16-1359-2023,https://doi.org/10.5194/gmd-16-1359-2023, 2023
Short summary
Satellite-based evaluation of AeroCom model bias in biomass burning regions
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022,https://doi.org/10.5194/acp-22-11009-2022, 2022
Short summary
Important role of stratospheric injection height for the distribution and radiative forcing of smoke aerosol from the 2019–2020 Australian wildfires
Bernd Heinold, Holger Baars, Boris Barja, Matthew Christensen, Anne Kubin, Kevin Ohneiser, Kerstin Schepanski, Nick Schutgens, Fabian Senf, Roland Schrödner, Diego Villanueva, and Ina Tegen
Atmos. Chem. Phys., 22, 9969–9985, https://doi.org/10.5194/acp-22-9969-2022,https://doi.org/10.5194/acp-22-9969-2022, 2022
Short summary
A quadcopter unmanned aerial system (UAS)-based methodology for measuring biomass burning emission factors
Roland Vernooij, Patrik Winiger, Martin Wooster, Tercia Strydom, Laurent Poulain, Ulrike Dusek, Mark Grosvenor, Gareth J. Roberts, Nick Schutgens, and Guido R. van der Werf
Atmos. Meas. Tech., 15, 4271–4294, https://doi.org/10.5194/amt-15-4271-2022,https://doi.org/10.5194/amt-15-4271-2022, 2022
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Tropospheric aerosols over the western North Atlantic Ocean during the winter and summer deployments of ACTIVATE 2020: life cycle, transport, and distribution
Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
Atmos. Chem. Phys., 25, 2087–2121, https://doi.org/10.5194/acp-25-2087-2025,https://doi.org/10.5194/acp-25-2087-2025, 2025
Short summary
Steady-state mixing state of black carbon aerosols from a particle-resolved model
Zhouyang Zhang, Jiandong Wang, Jiaping Wang, Nicole Riemer, Chao Liu, Yuzhi Jin, Zeyuan Tian, Jing Cai, Yueyue Cheng, Ganzhen Chen, Bin Wang, Shuxiao Wang, and Aijun Ding
Atmos. Chem. Phys., 25, 1869–1881, https://doi.org/10.5194/acp-25-1869-2025,https://doi.org/10.5194/acp-25-1869-2025, 2025
Short summary
Distinctive dust weather intensities in North China resulted from two types of atmospheric circulation anomalies
Qianyi Huo, Zhicong Yin, Xiaoqing Ma, and Huijun Wang
Atmos. Chem. Phys., 25, 1711–1724, https://doi.org/10.5194/acp-25-1711-2025,https://doi.org/10.5194/acp-25-1711-2025, 2025
Short summary
Biomass burning emission analysis based on MODIS aerosol optical depth and AeroCom multi-model simulations: implications for model constraints and emission inventories
Mariya Petrenko, Ralph Kahn, Mian Chin, Susanne E. Bauer, Tommi Bergman, Huisheng Bian, Gabriele Curci, Ben Johnson, Johannes W. Kaiser, Zak Kipling, Harri Kokkola, Xiaohong Liu, Keren Mezuman, Tero Mielonen, Gunnar Myhre, Xiaohua Pan, Anna Protonotariou, Samuel Remy, Ragnhild Bieltvedt Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Hailong Wang, Duncan Watson-Parris, and Kai Zhang
Atmos. Chem. Phys., 25, 1545–1567, https://doi.org/10.5194/acp-25-1545-2025,https://doi.org/10.5194/acp-25-1545-2025, 2025
Short summary
Quasi-weekly oscillation of regional PM2.5 transport over China driven by the synoptic-scale disturbance of the East Asian winter monsoon circulation
Yongqing Bai, Tianliang Zhao, Kai Meng, Yue Zhou, Jie Xiong, Xiaoyun Sun, Lijuan Shen, Yanyu Yue, Yan Zhu, Weiyang Hu, and Jingyan Yao
Atmos. Chem. Phys., 25, 1273–1287, https://doi.org/10.5194/acp-25-1273-2025,https://doi.org/10.5194/acp-25-1273-2025, 2025
Short summary

Cited articles

Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, 1989.
Anderson, T. E., Charlson, R. J., Winker, D. M., Ogren, J. A., and Holmen, K.: Mesoscale Variations of Tropospheric Aerosols, J. Atmos. Sci., 60, 119–136, 2003.
Angstrom, B. A.: Atmospheric turbidity , global illumination and planetary albedo of the earth, Tellus, XIV, 435–450, 1962.
Bellouin, N., Mann, G. W., Woodhouse, M. T., Johnson, C., Carslaw, K. S., and Dalvi, M.: Impact of the modal aerosol scheme GLOMAP-mode on aerosol forcing in the Hadley Centre Global Environmental Model, Atmos. Chem. Phys., 13, 3027–3044, https://doi.org/10.5194/acp-13-3027-2013, 2013.
Download
Short summary
When comparing models against observations, researchers often use long-term averages without due regard for the temporal sampling of the underlying data sets. We study the errors introduced by this practice and show they are often larger than observational errors and comparable to model errors. We further analyse what causes these errors and suggest best practices for eliminating them.
Share
Altmetrics
Final-revised paper
Preprint