The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3-HAM2.3 global atmosphere-aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON-A (icon-aes-1.3.00) global atmosphere model to yield the new ICON-A-HAM2.3 atmosphere-aerosol model. The ICON-A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub-grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6-HAM2.3 two-moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICON-A-HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON-A-HAM2.3 and ECHAM6.3-HAM2.3, but the bias is larger in ICON-A-HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub-tropical oceans. ICON-A-HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON-A-HAM2.3 compared to standard ICON-A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON-A-HAM2.3 and in ECHAM6.3-HAM2.3. In the extra-tropics, a smaller multivariable bias is found for ICON-A-HAM2.3 than for ECHAM6.3-HAM2.3.
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http://dx.doi.org/10.1029/2021MS002699 | DOI Listing |
The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.
View Article and Find Full Text PDFSci Total Environ
June 2020
Institute of Meteorological Sciences of Jilin Province, Changchun 130062, China.
Geosci Model Dev
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NOAA/NWS National Centers for Environmental Prediction, College Park, MD, USA.
The NOAA National Centers for Environmental Prediction (NCEP) implemented NEMS GFS Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5 day dust forecasts at 1°×1° resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012.
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Atmospheric aerosols have important impacts on human health, the environment and the climate system. Micro Pulse Lidar (MPL) is a new effective tool for detecting atmosphere aerosol horizontal distribution. And the extinction coefficient inversion and error analysis are important aspects of data processing.
View Article and Find Full Text PDFSci Rep
July 2014
Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
Black carbon (BC), one of the major components of atmosphere aerosol, could be the second dominant driver of climate change. We reconstructed historical trend of BC fluxes in Sanjiang Plain (Northeast China) through peat record to better understand its long-term trend and relationship of this atmosphere aerosol with intensity of human activities. The BC fluxes in peatland were higher than other sedimentary archives.
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